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Group announcement logic (GAL) and coalition announcement logic (CAL) allow us to reason about whether it is possible for groups and coalitions of agents to achieve their desired epistemic goals through truthful public communication. The difference between groups and coalitions in such a context is that the latter make their announcements in the presence of possible adversarial counter-announcements. As epistemic goals may involve some agents remaining ignorant, counter-announcements may preclude coalitions from reaching their goals. We study the relative expressivity of GAL and CAL and provide some results involving their more well-known sibling APAL. We also discuss how the presence of memory alters the relationship between groups and coalition. [ABSTRACT FROM AUTHOR]

In mining, manufacturing and industrial process industries, maintenance procedures are used as an aid to guide technicians through complex manual tasks. These procedures are not machine-readable, and cannot support reasoning in digitally integrated manufacturing systems. Procedure documents contain unstructured text and are stored in a variety of formats. The aim of this work is to query information held in real industrial maintenance procedures. To achieve this, we develop an ontology for maintenance procedures using the OWL 2 description language. We leverage classes and object properties from the ISO 15926 Part 14 Upper Ontology and create a domain ontology. The key contribution of this paper is a demonstration of trade-offs required when modelling an existing engineering artifact, where an abstraction of its contents is given a-priori. We provide an ontologically rigorous abstraction of notions captured in procedure documentation to a set of classes, relations and axioms that allow reasoning over the contents. Validation of the ontology is performed via a series of competency questions based on queries relevant to technicians, engineers and schedulers in industry. The ontology is applied to real world maintenance procedures from two industrial organisations. [ABSTRACT FROM AUTHOR]

Background Homologous recombination deficiency (HRD) is a phenotype that is characterized by the inability of a cell to effectively repair DNA double-strand breaks using the homologous recombination repair (HRR) pathway. Loss-of-function genes involved in this pathway can sensitize tumors to poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibitors and platinum-based chemotherapy, which target the destruction of cancer cells by working in concert with HRD through synthetic lethality. However, to identify patients with these tumors, it is vital to understand how to best measure homologous repair (HR) status and to characterize the level of alignment in these measurements across different diagnostic platforms. A key current challenge is that there is no standardized method to define, measure, and report HR status using diagnostics in the clinical setting. Methods Friends of Cancer Research convened a consortium of project partners from key healthcare sectors to address concerns about the lack of consistency in the way HRD is defined and methods for measuring HR status. Results This publication provides findings from the group's discussions that identified opportunities to align the definition of HRD and the parameters that contribute to the determination of HR status. The consortium proposed recommendations and best practices to benefit the broader cancer community. Conclusion Overall, this publication provides additional perspectives for scientist, physician, laboratory, and patient communities to contextualize the definition of HRD and various platforms that are used to measure HRD in tumors. [ABSTRACT FROM AUTHOR]

Various extensions of public announcement logic have been proposed with quantification over announcements. The best-known extension is called arbitrary public announcement logic, APAL. It contains a primitive language construct ...φ intuitively expressing that \after every public announcement of a formula, formula φ is true". The logic APAL is undecidable and it has an infinitary axiomatization. Now consider restricting the APAL quantification to public announcements of Boolean formulas only, such that ...φ intuitively expresses that \after every public announcement of a Boolean formula, formula φ is true". This logic can therefore be called Boolean arbitrary public announcement logic, BAPAL. The logic BAPAL is the subject of this work. Unlike APAL it has a infinitary axiomatization. Also, BAPAL is not at least as expressive as APAL. A further claim that BAPAL is decidable is deferred to a companion paper. [ABSTRACT FROM AUTHOR]

Arbitrary public announcement logic ( APAL ) reasons about how the knowledge of a set of agents changes after true public announcements and after arbitrary announcements of true epistemic formulas. We consider a variant of arbitrary public announcement logic called positive arbitrary public announcement logic ( A P A L + ), which restricts arbitrary public announcements to announcement of positive formulas. Positive formulas prohibit statements about the ignorance of agents. The positive formulas correspond to the universal fragment in first-order logic. As two successive announcements of positive formulas need not correspond to the announcement of a positive formula, A P A L + is rather different from APAL . We show that A P A L + is more expressive than public announcement logic PAL , and that A P A L + is incomparable with APAL . We also provide a sound and complete infinitary axiomatisation. [ABSTRACT FROM AUTHOR]

RoCTL* was proposed to model and specify the robustness of reactive systems. RoCTL* extended CTL* with the addition of Obligatory and Robustly operators, which quantify over failure-free paths and paths with one more failure, respectively. This article gives an axiomatization for all the operators of RoCTL* with the exception of the Until operator; this fragment is able to express similar contrary-to-duty obligations to the full RoCTL* logic. We call this formal system NORA, and give a completeness proof. We also consider the fragments of the language containing only path quantifiers but where atoms are dependent on histories. We examine semantic properties and potential axiomatizations for these fragments. [ABSTRACT FROM AUTHOR]

Programmable logic controllers (PLCs) are computers that are hardened for industrial environments and have I/O that are used to monitor and control a physical process. Learning automata specifications from PLCs provides an interface to verification tools that use an automata language, such as Uppaal. This paper introduces the time delay Mealy machine and demonstrates that it is sufficiently expressive to model PLC software. Using the LearnLib library, we implement a custom learning method to learn models from several industrial examples and analyze the efficiency. We show that the method is able to learn from simple PLC software, but the time required to learn increases rapidly with the scale of the software. [ABSTRACT FROM AUTHOR]

FGFR1 amplification occurs in ~20% of sqNSCLC and trials with FGFR inhibitors have selected FGFR1 amplified patients by FISH. Lung cancer cell lines were profiled for sensitivity to AZD4547, a potent, selective inhibitor of FGFRs 1–3. Sensitivity to FGFR inhibition was associated with but not wholly predicted by increased FGFR1 gene copy number. Additional biomarker assays evaluating expression of FGFRs and correlation between amplification and expression in clinical tissues are therefore warranted. We validated nanoString for mRNA expression analysis of 194 genes, including FGFRs, from clinical tumour tissue. In a panel of sqNSCLC tumours 14.4% (13/90) were FGFR1 amplified by FISH. Although mean FGFR1 expression was significantly higher in amplified samples, there was significant overlap in the range of expression levels between the amplified and non-amplified cohorts with several non-amplified samples expressing FGFR1 to levels equivalent to amplified samples. Statistical analysis revealed increased expression of FGFR1 neighboring genes on the 8p12 amplicon (BAG4, LSM1 and WHSC1L1) in FGFR1 amplified tumours, suggesting a broad rather than focal amplicon and raises the potential for codependencies. High resolution aCGH analysis of pre-clinical and clinical samples supported the presence of a broad and heterogeneous amplicon around the FGFR1 locus. In conclusion, the range of FGFR1 expression levels in both FGFR1 amplified and non-amplified NSCLC tissues, together with the breadth and intra-patient heterogeneity of the 8p amplicon highlights the need for gene expression analysis of clinical samples to inform the understanding of determinants of response to FGFR inhibitors. In this respect the nanoString platform provides an attractive option for RNA analysis of FFPE clinical samples. [ABSTRACT FROM AUTHOR]

The paper presents a new efficient algorithm for computing worst case execution time (WCET) of systems modelled as timed automata (TA). The algorithm uses a set of abstraction techniques that improve significantly the efficiency of WCET analysis of TA models with cyclic behaviour. We show that the proposed abstractions are exact with respect to the WCET problem in the sense that the WCET computed in the abstract model is equal to the one computed in the concrete model. We also compare our algorithm with the one implemented in the model checker UPPAAL which shows that when infinite cycles exist (i.e. cycles that can be run infinitely often), UPPAAL's algorithm may not terminate, and when largely repetitive finite cycles exist (i.e. cycles that can be run a large number of times but finite), UPPAAL's algorithm suffers from the state space explosion, thus leading to a low efficiency or resource exhaustion. [ABSTRACT FROM AUTHOR]

This paper compares the recently proposed Robust Full Computational Tree Logic (RoCTL*) to model robustness in concurrent systems with other computational tree logic (CTL*)-based logics. RoCTL* extends CTL* with the addition of the operators Obligatory and Robustly, which quantify over failure-free paths and paths with one more failure respectively. This paper focuses on examining the succinctness and expressiveness of RoCTL* by presenting translations to and from RoCTL*. The core result of this paper is to show that RoCTL* is expressively equivalent to CTL* but is non-elementarily more succinct. That is, RoCTL* does not add any expressive power over CTL*, but can represent some properties using vastly reduced formulae. We present a translation from RoCTL* into CTL* that preserves truth but may result in non-elementary growth in the length of the translated formula, as each nested Robustly operator may result in an extra exponential blowup. However, we show that this translation is optimal in the sense that any equivalence-preserving translation will require an extra exponential growth per nested Robustly. Note that this result has to do with the length of the translated formula. It has not been proved that there is no elementary decision procedure for RoCTL*; it is only known that RoCTL* must be at least as hard as CTL* (i.e., double exponential). We also compare RoCTL* to Quantified CTL* (QCTL*) and hybrid logics. [ABSTRACT FROM PUBLISHER]

We offer a partial articulation of the threats and opportunities posed by the so-called Dark Web (DW). We go on to propose a novel DW attack detection and prediction model. Signalling aspects are considered wherein the DW is seen to comprise a low cost signaling environment. This holds inherent dangers as well as rewards for investigators as well as those with criminal intent. Suspected DW perpetrators typically act entirely in their own self-interest (e.g. illicit financial gain, terrorism, propagation of extremist views, extreme forms of racism, pornography, and politics; so-called 'radicalisation'). DW investigators therefore need to be suitably risk aware such that the construction of a credible legally admissible, robust evidence trail does not expose investigators to undue operational or legal risk. [ABSTRACT FROM AUTHOR]

We examine various logics that combine knowledge, awareness, and change of awareness. An agent can become aware of propositional propositions but also of other agents or of herself. The dual operation to becoming aware, forgetting, can also be modelled. Our proposals are based on a novel notion of structural similarity that we call awareness bisimulation, the obvious notion of modal similarity for structures encoding knowledge and awareness. [ABSTRACT FROM AUTHOR]

Targeted therapies provide clinical benefit and improved therapeutic index. They have a growing prominence in patient management and focus in drug development. Their development is fuelled by our deepening knowledge of complex disease phenotypes and the need for improvement in new therapeutic efficacy. Extrapolation of the biological discovery through to new therapy targeting the causal biological variants to drive clinical gain is challenging. Here, we review the impact of germline mutations on targeted therapies. Historically, germline changes have contributed most to our understanding of disease mechanisms, drug metabolism and exposure, the latter of which has enabled safer positioning of therapies, such as clopidogrel and irinotecan. Similarly, prescreening for germline variants can avoid potentially fatal hypersensitivity reactions with abacavir. However, germline mutations continue to emerge as a central player in targeting therapeutics; ivacaftor drives partial restoration of mucus secretion in cystic fibrosis patients harbouring specific mutations, and treatment with olaparib exploits germline mutations in BRCA genes to drive synthetic lethality as an anti-cancer mechanism. Central is definition of the causal link, association or contribution to the biological variance - and that we believe it is drugable for therapeutic gain. The demand for better therapies to treat modern diseases provides the appetite for continued investigation of the biological variance associated with germline mutations, inevitably leading to increased impact on the development of targeted therapeutics. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A test case prioritization technique reschedules test cases for regression testing in an order to achieve specific goals like early fault detection. Currently, black box testing of web applications requires manual prioritization of test cases which is very time consuming. We propose a new two level prioritization approach to prioritize test cases for web applications as a whole. Our approach selects modified functionalities in a web application and automatically executes test cases on the basis of the impact of modified functionalities. We suggest several new prioritization strategies for web applications and examine whether these prioritization strategies improve the rate of fault detection for web applications. We propose a new test suite prioritization model for web applications that detects modified functionalities, selects test cases related to those functionalities and reschedules them to detect faults early in test suite execution. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present a process model for developing usable cross-cultural websites. Compatible with ISO 13407, the process model documents an abstraction of the design process focusing on cultural issues in development. It provides a framework in which a variety of user-based and expert-based techniques for analysis and design are placed within the life-cycle of website development. In developing the model, we relate practical approaches to design with theories and models of culture and discuss the relevance of such theories to the practical design process. In particular we focus on four key concerns: how an audit of local website attractors can inform the design process; the concept of a cultural fingerprint to contrast websites with the cultural needs of local users; the problems associated with user evaluation; and cross-cultural team development. We then show their relation to our process model. We conclude by summarising our contribution to date within the field. [Copyright &y& Elsevier]

XCSR is an accuracy-based learning classifier system which can handle classification problems with real-value features. However, as the number of features increases, a high classification accuracy comes at the cost of more resources: larger population sizes and longer computational running times. In this paper we investigate PCA-XCSR (a sequential application of PCA and XCSR) in three environments with different characteristics: a discrete and imbalanced environment (KDD'99 network intrusion), a continuous and highly symmetric environment (MiniBooNE), and a highly discrete, highly imbalanced environment (Census/Income (KDD)). These experiments show that in the three different environments, PCA-XCSR, in addition to being able to reduce the computational resources and time requirements of XCSR by approximately 50 %, is able to consistently maintain its high accuracy. In addition to that, it reduces the required population size needed by XCSR. Also, we suggest heuristics for selecting the number of principal components to use when using PCA-XCSR. [ABSTRACT FROM AUTHOR]

Fraud is a serious problem that costs the worldwide economy billions of dollars annually. However, fraud detection is difficult as perpetrators actively attempt to mask their actions, among typically overwhelming large volumes of, legitimate activity. In this paper, we investigate the fraud detection problem and examine how learning classifier systems can be applied to it. We describe the common properties of fraud, introducing an abstract problem which can be tuned to exhibit those characteristics. We report experiments on this abstract problem with a popular real-time learning classifier system algorithm; results from our experiments demonstrating that this approach can overcome the difficulties inherent to the fraud detection problem. Finally we apply the algorithm to a real-world problem and show that it can achieve good performance in this domain. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment. Methods: We applied a new unsupervised, iterative approach to stratify CRC tumor samples into subtypes based on genome-wide mRNA expression data. By applying this stratification to several CRC cell line panels and integrating pharmacological response data, we generated hypotheses regarding the targeted treatment of different subtypes. Results: In agreement with earlier studies, the two dominant CRC subtypes are highly correlated with a gene expression signature of epithelial-mesenchymal-transition (EMT). Notably, further dividing these two subtypes using iNMF (iterative Non-negative Matrix Factorization) revealed five subtypes that exhibit activation of specific signaling pathways, and show significant differences in clinical and molecular characteristics. Importantly, we were able to validate the stratification on independent, published datasets comprising over 1600 samples. Application of this stratification to four CRC cell line panels comprising 74 different cell lines, showed that the tumor subtypes are well represented in available CRC cell line panels. Pharmacological response data for targeted inhibitors of SRC, WNT, GSK3b, aurora kinase, PI3 kinase, and mTOR, showed significant differences in sensitivity across cell lines assigned to different subtypes. Importantly, some of these differences in sensitivity were in concordance with high expression of the targets or activation of the corresponding pathways in primary tumor samples of the same subtype. Conclusions: The stratification presented here is robust, captures important features of CRC, and offers valuable insight into functional differences between CRC subtypes. By matching the identified subtypes to cell line panels that have been pharmacologically characterized, it opens up new possibilities for the development and application of targeted therapies for defined CRC patient sub-populations. [ABSTRACT FROM AUTHOR]

Motivation: Understanding key biological processes (bioprocesses) and their relationships with constituent biological entities and pharmaceutical agents is crucial for drug design and discovery. One way to harvest such information is searching the literature. However, bioprocesses are difficult to capture because they may occur in text in a variety of textual expressions. Moreover, a bioprocess is often composed of a series of bioevents, where a bioevent denotes changes to one or a group of cells involved in the bioprocess. Such bioevents are often used to refer to bioprocesses in text, which current techniques, relying solely on specialized lexicons, struggle to find.Results: This article presents a range of methods for finding bioprocess terms and events. To facilitate the study, we built a gold standard corpus in which terms and events related to angiogenesis, a key biological process of the growth of new blood vessels, were annotated. Statistics of the annotated corpus revealed that over 36% of the text expressions that referred to angiogenesis appeared as events. The proposed methods respectively employed domain-specific vocabularies, a manually annotated corpus and unstructured domain-specific documents. Evaluation results showed that, while a supervised machine-learning model yielded the best precision, recall and F1 scores, the other methods achieved reasonable performance and less cost to develop.Availability: The angiogenesis vocabularies, gold standard corpus, annotation guidelines and software described in this article are available at http://text0.mib.man.ac.uk/~mbassxw2/angiogenesis/Contact: xinglong.wang@gmail.com [ABSTRACT FROM AUTHOR]