Survey Metode Formal Dalam Verifikasi Dan Validasi

Paper ini ditujukan untuk mensurvey metode formal yang digunakan orang baik itu dalam USAha mengembangkan software & harware, atau dalam USAha melakukan verifikasi dan validasi. Beberapa metode formal yang hendak ditinjau adalah CPN, PFSA, Actor Model, Rebeca, LTL, ACTL, CTL, UML, Hybrid Automata dan ASM. Pada setiap tinjauan, dijelaskan motivasi dan gagasan dasar metode formal bersangkutan secara intuitif dan implementasi-implementasinya yang merujuk pada berbagai paper-paper penelitian yang telah dilakukan orang menyangkut metode formal bersangkutan

Molecules with multiple personalities: how switchable materials could revolutionise chemical sensing

Worldwide, the demand for sensing devices that can conform with the requirements of large-scale wireless sensor network (WSN) deployments is rising exponentially. Typically, sensors should be very low cost, low power (essentially self-sustaining), yet very rugged and reliable. At present, functioning WSN deployments involve physical transducers only, such as thermistors, accelerometers, photodetectors, or flow meters, to monitor quantities like temperature, movement, light level and liquid level/flow. Remote, widely distributed monitoring of molecular targets remains relatively unexplored, except in the case of targets that can be detected directly using ‘non-contact’ techniques like spectroscopy. This paper will address the issues inhibiting the close integration of chemical sensing with WSNs and suggest strategies based on fundamental materials science that may offer routes to new sensing surfaces that can switch between different modes of behaviour (e.g. active-passive, expand-contract)

Workshop on Modelling of Objects, Components, and Agents, Aarhus, Denmark, August 27-28, 2001

This booklet contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'01), August 27-28, 2001. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark and the "Theoretical Foundations of Computer Science" Group at the University of Hamburg, Germany. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop01

Toward Accessible Multilevel Modeling in Systems Biology: A Rule-based Language Concept

Promoted by advanced experimental techniques for obtaining high-quality data and the steadily accumulating knowledge about the complexity of life, modeling biological systems at multiple interrelated levels of organization attracts more and more attention recently. Current approaches for modeling multilevel systems typically lack an accessible formal modeling language or have major limitations with respect to expressiveness. The aim of this thesis is to provide a comprehensive discussion on associated problems and needs and to propose a concrete solution addressing them

Identification of Micro- and Submicron (Nano) Plastics in Water Sources and the Impact of COVID-19 on Plastic Pollution

One of the most significant environmental issues that our society may deal with this century could be plastics. The world's water bodies, as well as land and air, are becoming more and more contaminated by plastic due to the ongoing and expanding manufacturing of these synthetic materials, as well as the lack of an effective strategy for managing plastic waste. The fact that plastics break down into smaller particles (micro and nanoplastics) by action of environmental physical and chemical reactions, and do not degrade biologically in a reasonable time, is a cause of concern as plastics are believed to cause harm in animals, plants and humans.To identify the types of plastics prevalent in aquatic habitats, a number of procedures have been developed, from sampling to identification. After a water body has been sampled using nets, pumps, or other tools, depending on the type of sample taken, it is usually necessary to treat the samples for separation and purification. The next stage is to employ analytical techniques to identify the synthetic contaminants. The most common approaches are microscopy, spectroscopy, and thermal analysis. This thesis gives an overview of where in the environment microplastics (MPs) and nanoplastics (NPs) can be found and summarizes the most important technologies applied to analyse the importance of plastics as a contaminant in water bodies. The development of standardised analytical procedures is still necessary as most of them are not suitable for the identification of particles below 50 μm due to resolution limitations. The preparation and analysis of samples are usually time-consuming factors that shall be considered. Particularly for MP and NP analysis in aqueous samples, thermal analysis methods based on sample degradation are generally not considered to be the most effective approach. Nevertheless, Pyrolysis - Gas Chromatography Time-of-Flight Mass Spectrometry (Py-GCToFMS) is used in this thesis to propose a novel approach as due to its unique detection abilities, and with a novel filtration methodology for collection, it enables the identification of tiny particle sizes (>0.1 μm) in water samples.PTFE membranes were selected to filter the liquid samples using a glass filtration system. This way, the synthetic particles will be deposited on the membranes and will allow the study and analysis of the precipitated material. PTFE is a readily available, reasonably priced, and adaptable product that makes sample preparation quick and simple.The three plastics under study—polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC)—can be identified from complex samples at trace levels thanks to the employment of these widely used membranes and the identification of various and specific (marker) ions. The technique was examined against a range of standards samples that contained predetermined concentrations of MPs and NPs. Detection levels were then determined for PVC and PS and were found to be below <50 μg/ L, with repeatable data showing good precision (RSD <20 %). The examination of a complex matrix sample taken from a nearby river contributed to further validate this innovative methodology; the results indicated the existence of PS with a semi-quantifiable result of 250.23 g/L. Because of this, PY-GCToFMS appears to be a method that is appropriate for the task of identifying MPs and NPs from complex mixtures.This thesis also focuses on the environmental challenge that disposable plastic face masks (DPFMs) pose, which has been made significantly worse due to the COVID-19 pandemic. By the time this thesis was written, the production of disposable plastic facemasks had reached to approximately 200 million a day, in a global effort to tackle the spread of the new SARS-CoV-2 virus. This thesis investigates the emissions of pollutants from several different DPFM brands (medical and non-medical) that were submerged in water to replicate the conditions in the environment after these DPFMs have been discarded. The DPFM leachates were filtered using inorganic membranes type and characterized using Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS), Light/Optical Microscopy (LM/OM), Inductively coupled plasma mass spectrometry (ICP-MS) and Liquid chromatography–mass spectrometry (LC-MS). Micro and nano scale polymeric fibres, particles, siliceous fragments and leachable inorganic and organic chemicals were observed from all of the tested DPFMs. For non-medical DPFMs, traces of concerning heavy metals were detected in association with silicon containing fragments (i.e. lead up to 6.79 μg/L). ICP-MS also confirmed the presence of other leachable metals like cadmium (up to 1.92 μg/L), antimony (up to 3.93 μg/L) and copper (up to 4.17 μg/L). LC-MS analysis identified organic species related to plastic additives; polyamide-66 monomer and oligomers (nylon-66 synthesis), surfactant molecules, and dye-like molecules were all tentatively identified in the leachate. The question of whether DPFMs are safe to use daily and what implications may be anticipated after their disposal into the environment is brought up by the toxicity of some of the chemicals discovered.The previous approach is expanded to medical DPFMs with the utilisation of Field Emission Gun Scanning Electron Microscope (FEG-SEM) in order to get high resolution images of the micro and nanoparticles deposited on the membranes. It is also incorporated the use of 0.02 μm pore size inorganic membranes to better identify the nanoparticles released.Separated aqueous samples were also obtained by submerging medical DPFMs for 24 hours to be analysed using ICP-MS and LC-MS.Both particles and fibres in the micro and nano scale were found in all 6 DPFMs brands of this study. EDS analysis revealed the presence of particles containing different heavy metals like lead, mercury, and arsenic among others. ICP-MS analysis results confirmed traces of heavy metals (antimony up to 2.41 μg/L and copper up to 4.68 μg/L). LC-MS analysis results identified organic species related to plastic additives and contaminants; polyamide-66 monomer and oligomers (nylon-66 synthesis), surfactant molecules, and polyethylene glycol were all tentatively identified in the leachate. The toxicity of some of the chemicals found raises the question of whether DPFMs are safe to be used on a daily basis and what consequences are to be expected after their disposal into the environment

Advanced reliability analysis of polymer electrolyte membrane fuel cells in automotive applications

Hydrogen fuel cells have the potential to dramatically reduce emissions from the energy sector, particularly when integrated into an automotive application. However, there are three main hurdles to the commercialisation of this promising technology; one of which is reliability. Cur- rent standards require an automotive fuel cell to last around 5000 h of operation (equivalent to around 150,000 miles), which has proven difficult to achieve to date. This hurdle can be overcome through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA), Fault Tree Analysis (FTA) and Petri-net simulation. This research has found that the reliability field regarding hydrogen fuel cells is still in its infancy, and needs development, if the current standards are to be achieved. In this research, a detailed reliability study of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) is undertaken. The results of which are a qualitative and quantitative analysis of a PEMFC. The FMEA and FTA are the most up to date assessments of failure in fuel cells developed using a comprehensive literature review and expert opinion. Advanced modelling of fuel cell degradation logic was developed using Petri-net modelling techniques. 20 failure modules were identfied that represented the interactions of all failure modes and operational parameters in a PEMFC. Petri-net simulation was used to overcome key pitfalls observed in FTA to provide a verfied degradation model of a PEMFC in an automotive application, undergoing a specific drive cycle, however any drive cycle can be input to this model. Overall results show that the modeled fuel cell's lifetime would reach 34 hours before falling below the industry standard degradation rate of more than 5%. The degradation model has the capability to simulate fuel cell degradation under any drive cycle and with any operating parameters. A fuel cell test rig was also developed that was used to verify the simulated degradation. The rig is capable of testing single cells or stacks from 0-470W power. The results from the verification experimentation agreed strongly with the degradation model, giving confidence in the accuracy of the developed Petri-net degradation model. This research contributes greatly to the field of reliability of PEMFCs through the most up-to-date and comprehensive FMEA and FTA presented. Additionally, a degradation model based upon Petri-nets is the first degradation model to encompass a 1D performance model to predict fuel cell life time under specific drive cycles

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Investigating Post-Translational Modification of the Net Protein Superfamily

The Net protein superfamily represents a group of actin binding proteins contain a novel actin binding domain at their N termini. The aim of this project was to investigate post-translational modification of these proteins in order to explore how the interaction of these proteins with actin is regulated. A bioinformatics-based approach was used to predict sites for multiple types of modification, with a focus on phosphorylation, that were conserved between members of the superfamily. It became clear that there was some level of conservation of predicted post-translational modification sites at the C-terminus in multiple Net families. Net4B was identified as having a high probability of being phosphorylated at the C-terminus and predicted to have its N- and C-termini proximal to one another in its tertiary structure, and following this mutant forms of the protein were created to investigate how its actin binding activity would be affected if one site, S509, was phosphorylated or dephosphorylated. The mutants were transiently expressed in Nicotania benthamiana and the appearance of the leaf cells assessed. Whilst phosphomimicry of S509 resulted in no appreciable change in the appearance of the GFP-tagged protein, mutation to a residue imitating a non-phosphorylatable serine resulted in the formation of punctae, in some cases much like the ‘beads-on-a-string’ seen in other members of the Net superfamily. This finding may have implications for the regulation of actin binding in other Net proteins and for other proteins outside of the superfamily. Two models are presented in both of these contexts. This project may also provide groundwork for future experiments concerning phosphorylation and acylation, and may illuminate the mechanism by which Net proteins interact with actin and with the membranes with which they are respectively localised

Complex event types for agent-based simulation

This thesis presents a novel formal modelling language, complex event types (CETs), to describe behaviours in agent-based simulations. CETs are able to describe behaviours at any computationally represented level of abstraction. Behaviours can be specified both in terms of the state transition rules of the agent-based model that generate them and in terms of the state transition structures themselves. Based on CETs, novel computational statistical methods are introduced which allow statistical dependencies between behaviours at different levels to be established. Different dependencies formalise different probabilistic causal relations and Complex Systems constructs such as ‘emergence’ and ‘autopoiesis’. Explicit links are also made between the different types of CET inter-dependency and the theoretical assumptions they represent. With the novel computational statistical methods, three categories of model can be validated and discovered: (i) inter-level models, which define probabilistic dependencies between behaviours at different levels; (ii) multi-level models, which define the set of simulations for which an inter-level model holds; (iii) inferred predictive models, which define latent relationships between behaviours at different levels. The CET modelling language and computational statistical methods are then applied to a novel agent-based model of Colonic Cancer to demonstrate their applicability to Complex Systems sciences such as Systems Biology. This proof of principle model provides a framework for further development of a detailed integrative model of the system, which can progressively incorporate biological data from different levels and scales as these become available