title: Incremental system verification and synthesis of minimally restrictive behaviours

authors: Malik, Robi

abstract: An incremental approach to system verification is proposed, for system behaviours and safety properties described by means of finite-string languages and finite-state automata. Properties are verified with respect to subsystems of the overall system, nevertheless allowing assertions to be made about the entire system satisfying such properties. The proposed approach considers satisfaction of properties, controllability, and synthesis as successive verification steps. Furthermore, it allows the incremental augmentation of the system to be verified: after each verification step, either the desired property is verified, or a counter example is obtained, which, together with heuristics, provides the basis for the augmentation of a given subsystem for the next verification step.

text: Incremental system verification and synthesis of minimally restrictive behaviours An incremental approach to system verification is proposed, for system behaviours and safety properties described by means of finite-string languages and finite-state automata. Properties are verified with respect to subsystems of the overall system, nevertheless allowing assertions to be made about the entire system satisfying such properties. The proposed approach considers satisfaction of properties, controllability, and synthesis as successive verification steps. Furthermore, it allows the incremental augmentation of the system to be verified: after each verification step, either the desired property is verified, or a counter example is obtained, which, together with heuristics, provides the basis for the augmentation of a given subsystem for the next verification step.

year: 2000

title: Biosensing-by-Learning Direct Targeting Strategy for Enhanced Tumor Sensitization

authors: Chen, Yifan

subjects: Science & Technology

abstract: We propose a novel iterative-optimization-inspired direct targeting strategy (DTS) for smart nanosystems, which harness swarms of externally manipulable nanoswimmers assembled by magnetic nanoparticles (MNPs) for knowledge-aided tumor sensitization and targeting. We aim to demonstrate through computational experiments that the proposed DTS can significantly enhance the accumulation of MNPs in the tumor site, which serve as a contrast agent in various medical imaging modalities, by using the shortest possible physiological routes and with minimal systemic exposure. The epicenter of a tumor corresponds to the global maximum of an externally measurable objective function associated with an in vivo tumor-triggered biological gradient; the domain of the objective function is the tissue region at a high risk of malignancy; swarms of externally controllable magnetic nanoswimmers for tumor sensitization are modeled as the guess inputs. The objective function may be resulted from a passive phenomenon such as reduced blood flow or increased kurtosis of microvasculature due to tumor angiogenesis; otherwise, the objective function may involve an active phenomenon such as the fibrin formed during the coagulation cascade activated by tumor-targeted “activator” nanoparticles. Subsequently, the DTS can be interpreted from the iterative optimization perspective: guess inputs (i.e., swarms of nanoswimmers) are continuously updated according to the gradient of the objective function in order to find the optimum (i.e., tumor) by moving through the domain (i.e., tissue under screening). Along this line of thought, we propose the computational model based on the gradient descent (GD) iterative method to describe the GD-inspired DTS, which takes into account the realistic in vivo propagation scenario of nanoswimmers. By means of computational experiments, we show that the GD-inspired DTS yields higher probabilities of tumor sensitization and more significant dose accumulation compared to the “brute-force” search, which corresponds to the systemic targeting scenario where drug nanoparticles attempt to target a tumor by enumerating all possible pathways in the complex vascular network. The knowledge-aided DTS has potential to enhance the tumor sensitization and targeting performance remarkably by exploiting the externally measurable, tumor-triggered biological gradients. We believe that this work motivates a novel biosensing-by-learning framework facilitated by externally manipulable, smart nanosystems.

text: Biosensing-by-Learning Direct Targeting Strategy for Enhanced Tumor Sensitization We propose a novel iterative-optimization-inspired direct targeting strategy (DTS) for smart nanosystems, which harness swarms of externally manipulable nanoswimmers assembled by magnetic nanoparticles (MNPs) for knowledge-aided tumor sensitization and targeting. We aim to demonstrate through computational experiments that the proposed DTS can significantly enhance the accumulation of MNPs in the tumor site, which serve as a contrast agent in various medical imaging modalities, by using the shortest possible physiological routes and with minimal systemic exposure. The epicenter of a tumor corresponds to the global maximum of an externally measurable objective function associated with an in vivo tumor-triggered biological gradient; the domain of the objective function is the tissue region at a high risk of malignancy; swarms of externally controllable magnetic nanoswimmers for tumor sensitization are modeled as the guess inputs. The objective function may be resulted from a passive phenomenon such as reduced blood flow or increased kurtosis of microvasculature due to tumor angiogenesis; otherwise, the objective function may involve an active phenomenon such as the fibrin formed during the coagulation cascade activated by tumor-targeted “activator” nanoparticles. Subsequently, the DTS can be interpreted from the iterative optimization perspective: guess inputs (i.e., swarms of nanoswimmers) are continuously updated according to the gradient of the objective function in order to find the optimum (i.e., tumor) by moving through the domain (i.e., tissue under screening). Along this line of thought, we propose the computational model based on the gradient descent (GD) iterative method to describe the GD-inspired DTS, which takes into account the realistic in vivo propagation scenario of nanoswimmers. By means of computational experiments, we show that the GD-inspired DTS yields higher probabilities of tumor sensitization and more significant dose accumulation compared to the “brute-force” search, which corresponds to the systemic targeting scenario where drug nanoparticles attempt to target a tumor by enumerating all possible pathways in the complex vascular network. The knowledge-aided DTS has potential to enhance the tumor sensitization and targeting performance remarkably by exploiting the externally measurable, tumor-triggered biological gradients. We believe that this work motivates a novel biosensing-by-learning framework facilitated by externally manipulable, smart nanosystems.

year: 2019

title: Responsive socio-cultural contexts: Supporting five year olds to become literate in a second language.

authors: Berryman, Mere

subjects: bilingual learners

abstract: Learning one's own indigenous language and culture as a second language learner within formal mainstream education settings can pose many challenges, especially for students who have been raised in the dominant first language and who are just beginning school. This paper discusses a Māori language resource used by a Māori immersion teacher to respond to these challenges. This resource utilises community support to develop students' phonological awareness while simultaneously increasing their oral language. This study shows that within a relatively short period of time, students' phonological knowledge improved along with their confidence and ability to speak in Māori. With these skills they were then able to progress more successfully to becoming literate in Māori, their second language.

text: Responsive socio-cultural contexts: Supporting five year olds to become literate in a second language. Learning one's own indigenous language and culture as a second language learner within formal mainstream education settings can pose many challenges, especially for students who have been raised in the dominant first language and who are just beginning school. This paper discusses a Māori language resource used by a Māori immersion teacher to respond to these challenges. This resource utilises community support to develop students' phonological awareness while simultaneously increasing their oral language. This study shows that within a relatively short period of time, students' phonological knowledge improved along with their confidence and ability to speak in Māori. With these skills they were then able to progress more successfully to becoming literate in Māori, their second language.

year: 2012