Optimizing Automata Learning via Monads

Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence optimizations that enable learning of compact representations are important. This paper exploits monads, both as a mathematical structure and a programming construct, to design, prove correct, and implement a wide class of such optimizations. The former perspective on monads allows us to develop a new algorithm and accompanying correctness proofs, building upon a general framework for automata learning based on category theory. The new algorithm is parametric on a monad, which provides a rich algebraic structure to capture non-determinism and other side-effects. We show that our approach allows us to uniformly capture existing algorithms, develop new ones, and add optimizations. The latter perspective allows us to effortlessly translate the theory into practice: we provide a Haskell library implementing our general framework, and we show experimental results for two specific instances: non-deterministic and weighted automata

Learning automata with side-effects

Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence optimizations that enable learning of compact representations are important. This paper exploits monads, both as a mathematical structure and a programming construct, to design and prove correct a wide class of such optimizations. Monads enable the development of a new learning algorithm and correctness proofs, building upon a general framework for automata learning based on category theory. The new algorithm is parametric on a monad, which provides a rich algebraic structure to capture non-determinism and other side-effects. We show that this allows us to uniformly capture existing algorithms, develop new ones, and add optimizations

Learning Pomset Automata.

We extend the L⋆ algorithm to learn bimonoids recognising pomset languages. We then identify a class of pomset automata that accepts precisely the class of pomset languages recognised by bimonoids and show how to convert between bimonoids and automata

Disciplina de biologia: aprendizagem de estudantes do ensino médio

Anais do II Seminário Seminário Estadual PIBID do Paraná: tecendo saberes / organizado por Dulcyene Maria Ribeiro e Catarina Costa Fernandes — Foz do Iguaçu: Unioeste; Unila, 2014O conhecimento das noções dos estudantes a respeito de uma determinada área do saber é fundamental para que o professor possa identificar os conhecimentos prévios e propor práticas pedagógicas mais eficientes. O presente estudo teve como objetivo compreender quais conteúdos da Biologia estudantes do ensino médio sentem mais facilidade e dificuldade em aprender. A metodologia desta pesquisa é qualitativa. Para a coleta de dados foi aplicado um questionário aberto. As respostas foram classificadas por meio de Unidades de Registro, elaboradas previamente, as mesmas foram baseadas nos conteúdos estruturantes propostos pelas Diretrizes Curriculares de Biologia. Compreendemos que todos os conteúdos são interdependentes, não hierarquizáveis e precisam ser discutidos no ambiente escola

Stable Differences in Intrinsic Mitochondrial Membrane Potential of Tumor Cell Subpopulations Reflect Phenotypic Heterogeneity

Heterogeneity among cells that constitute a solid tumor is important in determining disease progression. Our previous work established that, within a population of metastatic colonic tumor cells, there are minor subpopulations of cells with stable differences in their intrinsic mitochondrial membrane potential (ΔΨm), and that these differences in ΔΨm are linked to tumorigenic phenotype. Here we expanded this work to investigate primary mammary, as well as colonic, tumor cell lines. We show that within a primary mammary tumor cell population, and in both primary and metastatic colonic tumor cell populations, there are subpopulations of cells with significant stable variations in intrinsic ΔΨm. In each of these 3 tumor cell populations, cells with relatively higher intrinsic ΔΨm exhibit phenotypic properties consistent with promotion of tumor cell survival and expansion. However, additional properties associated with invasive potential appear in cells with higher intrinsic ΔΨm only from the metastatic colonic tumor cell line. Thus, it is likely that differences in the intrinsic ΔΨm among cells that constitute primary mammary tumor populations, as well as primary and metastatic colonic tumor populations, are markers of an acquired tumor phenotype which, within the context of the tumor, influence the probability that particular cells will contribute to disease progression

Canonical Automata via Distributive Law Homomorphisms

The classical powerset construction is a standard method converting a non-deterministic automaton into a deterministic one recognising the same language. Recently, the powerset construction has been lifted to a more general framework that converts an automaton with side-effects, given by a monad, into a deterministic automaton accepting the same language. The resulting automaton has additional algebraic properties, both in the state space and transition structure, inherited from the monad. In this paper, we study the reverse construction and present a framework in which a deterministic automaton with additional algebraic structure over a given monad can be converted into an equivalent succinct automaton with side-effects. Apart from recovering examples from the literature, such as the canonical residual finite-state automaton and the átomaton, we discover a new canonical automaton for a regular language by relating the free vector space monad over the two element field to the neighbourhood monad. Finally, we show that every regular language satisfying a suitable property parametric in two monads admits a size-minimal succinct acceptor

Tree Automata as Algebras: Minimisation and Determinisation

We study a categorical generalisation of tree automata, as algebras for a fixed endofunctor endowed with initial and final states. Under mild assumptions about the base category, we present a general minimisation algorithm for these automata. We then build upon and extend an existing generalisation of the Nerode equivalence to a categorical setting and relate it to the existence of minimal automata. Finally, we show that generalised types of side-effects, such as non-determinism, can be captured by this categorical framework, leading to a general determinisation procedure

Intrinsic Mitochondrial Membrane Potential and Associated Tumor Phenotype Are Independent of MUC1 Over-Expression

We have established previously that minor subpopulations of cells with stable differences in their intrinsic mitochondrial membrane potential (Δψm) exist within populations of mammary and colonic carcinoma cells and that these differences in Δψm are linked to tumorigenic phenotypes consistent with increased probability of participating in tumor progression. However, the mechanism(s) involved in generating and maintaining stable differences in intrinsic Δψm and how they are linked to phenotype are unclear. Because the mucin 1 (MUC1) oncoprotein is over-expressed in many cancers, with the cytoplasmic C-terminal fragment (MUC1 C-ter) and its integration into the outer mitochondrial membrane linked to tumorigenic phenotypes similar to those of cells with elevated intrinsic Δψm, we investigated whether endogenous differences in MUC1 levels were linked to stable differences in intrinsic Δψm and/or to the tumor phenotypes associated with the intrinsic Δψm. We report that levels of MUC1 are significantly higher in subpopulations of cells with elevated intrinsic Δψm derived from both mammary and colonic carcinoma cell lines. However, using siRNA we found that down-regulation of MUC1 failed to significantly affect either the intrinsic Δψm or the tumor phenotypes associated with increased intrinsic Δψm. Moreover, whereas pharmacologically mediated disruption of the Δψm was accompanied by attenuation of tumor phenotype, it had no impact on MUC1 levels. Therefore, while MUC1 over-expression is associated with subpopulations of cells with elevated intrinsic Δψm, it is not directly linked to the generation or maintenance of stable alterations in intrinsic Δψm, or to intrinsic Δψm associated tumor phenotypes. Since the Δψm is the focus of chemotherapeutic strategies, these data have important clinical implications in regard to effectively targeting those cells within a tumor cell population that exhibit stable elevations in intrinsic Δψm and are most likely to contribute to tumor progression

A Potent Lead Induces Apoptosis in Pancreatic Cancer Cells

Pancreatic cancer is considered a lethal and treatment-refractory disease. To obtain a potent anticancer drug, the cytotoxic effect of 2-(benzo[d]oxazol-3(2H)-ylmethyl)- 5-((cyclohexylamino)methyl)benzene-1,4-diol, dihydrochloride (NSC48693) on human pancreatic cancer cells CFPAC-1, MiaPaCa-2, and BxPC-3 was assessed in vitro. The proliferation of CFPAC-1, MiaPaCa-2, and BxPC-3 is inhibited with IC50 value of 12.9±0.2, 20.6±0.3, and 6.2±0.6 µM at 48 h, respectively. This discovery is followed with additional analysis to demonstrate that NSC48693 inhibition is due to induction of apoptosis, including Annexin V staining, chromatins staining, and colony forming assays. It is further revealed that NSC48693 induces the release of cytochrome c, reduces mitochondrial membrane potential, generates reactive oxygen species, and activates caspase. These results collectively indicate that NSC48693 mainly induces apoptosis of CFPAC-1, MiaPaCa-2, and BxPC-3 cells by the mitochondrial-mediated apoptotic pathway. Excitingly, the study highlights an encouraging inhibition effect that human embryonic kidney (HEK-293) and liver (HL-7702) cells are more resistant to the antigrowth effect of NSC48693 compared to the three cancer cell lines. From this perspective, NSC48693 should help to open up a new opportunity for the treatment of patients with pancreatic cancer

Axillary Dissection and Nodal Irradiation Can Be Avoided for Most Node-positive Z0011-eligible Breast Cancers : a Prospective Validation Study of 793 Patients

OBJECTIVE: To determine rates of axillary dissection (ALND) and nodal recurrence in patients eligible for ACOSOG Z0011. BACKGROUND: Z0011 demonstrated that patients with cT1-2N0 breast cancers and 1 to 2 involved sentinel lymph nodes (SLNs) having breast-conserving therapy had no difference in locoregional recurrence or survival after SLN biopsy alone or ALND. The generalizability of the results and importance of nodal radiotherapy (RT) is unclear. METHODS: Patients eligible for Z0011 had SLN biopsy alone. Prospectively defined indications for ALND were metastases in 653 SLNs or gross extracapsular extension. Axillary imaging was not routine. SLN and ALND groups and radiation fields were compared with chi-square and t tests. Cumulative incidence of recurrences was estimated with competing risk analysis. RESULTS: From August 2010 to December 2016, 793 patients met Z0011 eligibility criteria and had SLN metastases. Among them, 130 (16%) had ALND; ALND did not vary based on age, estrogen receptor, progesterone receptor, or HER2 status. Five-year event-free survival after SLN alone was 93% with no isolated axillary recurrences. Cumulative 5-year rates of breast\u200a+\u200anodal and nodal\u200a+\u200adistant recurrence were each 0.7%. In 484 SLN-only patients with known RT fields (103 prone, 280 supine tangent, 101 breast\u200a+\u200anodes) and follow-up 6512 months, the 5-year cumulative nodal recurrence rate was 1% and did not differ significantly by RT fields. CONCLUSIONS: We confirm that even without preoperative axillary imaging or routine use of nodal RT, ALND can be avoided in a large majority of Z0011-eligible patients with excellent regional control. This approach has the potential to spare substantial numbers of women the morbidity of ALND