Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.

Formulations and Metaheuristics for combinatorial optimization problems

Combinatorial optimization problems have been strongly addressed throughout history. Their study involves highly applied problems that must be solved in reasonable times. This doctoral Thesis addresses three Operations Research problems: the first deals with the Traveling Salesman Problem with Pickups and Delivery with Handling cost, which was approached with two metaheuristics based on Iterated Local Search; the results show that the proposed methods are faster and obtain good results respect to the metaheuristics from the literature. The second problem corresponds to the Quadratic Multiple Knapsack Problem, and polynomial formulations and relaxations are presented for new instances of the problem; in addition, a metaheuristic and a matheuristic are proposed that are competitive with state of the art algorithms. Finally, an Open-Pit Mining problem is approached. This problem is solved with a parallel genetic algorithm that allows excavations using truncated cones. Each of these problems was computationally tested with difficult instances from the literature, obtaining good quality results in reasonable computational times, and making significant contributions to the state of the art techniques of Operations Research.

The three-dimensional single-bin-size bin packing problem: combining metaheuristic and machine learning approaches

The Three-Dimensional Single-Bin-Size Bin Packing Problem is one of the most studied problem in the Cutting & Packing category. From a strictly mathematical point of view, it consists of packing a finite set of strongly heterogeneous “small” boxes, called items, into a finite set of identical “large” rectangles, called bins, minimizing the unused volume and requiring that the items are packed without overlapping. The great interest is mainly due to the number of real-world applications in which it arises, such as pallet and container loading, cutting objects out of a piece of material and packaging design. Depending on these real-world applications, more objective functions and more practical constraints could be needed. After a brief discussion about the real-world applications of the problem and a exhaustive literature review, the design of a two-stage algorithm to solve the aforementioned problem is presented. The algorithm must be able to provide the spatial coordinates of the placed boxes vertices and also the optimal boxes input sequence, while guaranteeing geometric, stability, fragility constraints and a reduced computational time. Due to NP-hard complexity of this type of combinatorial problems, a fusion of metaheuristic and machine learning techniques is adopted. In particular, a hybrid genetic algorithm coupled with a feedforward neural network is used. In the first stage, a rich dataset is created starting from a set of real input instances provided by an industrial company and the feedforward neural network is trained on it. After its training, given a new input instance, the hybrid genetic algorithm is able to run using the neural network output as input parameter vector, providing as output the optimal solution. The effectiveness of the proposed works is confirmed via several experimental tests.

Crystal engineering strategies against antimicrobial resistance: a solid contribution to a contemporary problem

This PhD thesis sets its goal in the application of crystal engineering strategies to the design, formulation, synthesis, and characterization of innovative materials obtained by combining well established biologically active molecules and/or GRAS (generally recognized as safe) compounds with co-formers able to modulate specific properties of the molecule of interest. The solid-state association, via non-covalent interactions, of an active ingredient with another molecular component, a metal salt or a complex, may alter in a useful way the physicochemical properties of the active ingredient and/or may allow to explore new ways to enhance, in a synergistic way, the overall biological performance. More specifically this thesis will address the threat posed by the increasing antimicrobial resistance (AMR) developed by microorganisms, which call for novel therapeutic strategies. Crystal engineering provides new tools to approach this crisis in a greener and cost-effective way. This PhD work has been developed along two main research lines aiming to contribute to the search for innovative solutions to the AMR problem. Design, preparation and characterization of novel metal-based antimicrobials, whereby organic molecules with known antimicrobial properties are combined with metal atoms also known to exert antimicrobial action. Design, preparation and characterization of co-crystals obtained by combining antibacterial APIs (active pharmaceutical ingredients) with natural antimicrobials.

Extending the 2P-Kt ecosystem: CLP and Labelled LP

The ability to create hybrid systems that blend different paradigms has now become a requirement for complex AI systems usually made of more than a component. In this way, it is possible to exploit the advantages of each paradigm and exploit the potential of different approaches such as symbolic and non-symbolic approaches. In particular, symbolic approaches are often exploited for their efficiency, effectiveness and ability to manage large amounts of data, while symbolic approaches are exploited to ensure aspects related to explainability, fairness, and trustworthiness in general. The thesis lies in this context, in particular in the design and development of symbolic technologies that can be easily integrated and interoperable with other AI technologies. 2P-Kt is a symbolic ecosystem developed for this purpose, it provides a logic-programming (LP) engine which can be easily extended and customized to deal with specific needs. The aim of this thesis is to extend 2P-Kt to support constraint logic programming (CLP) as one of the main paradigms for solving highly combinatorial problems given a declarative problem description and a general constraint-propagation engine. A real case study concerning school timetabling is described to show a practical usage of the CLP(FD) library implemented. Since CLP represents only a particular scenario for extending LP to domain-specific scenarios, in this thesis we present also a more general framework: Labelled Prolog, extending LP with labelled terms and in particular labelled variables. The designed framework shows how it is possible to frame all variations and extensions of LP under a single language reducing the huge amount of existing languages and libraries and focusing more on how to manage different domain needs using labels which can be associated with every kind of term. Mapping of CLP into Labeled Prolog is also discussed as well as the benefits of the provided approach.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part A)

In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.

Albumin Is Synthesized In Epididymis And Aggregates In A High Molecular Mass Glycoprotein Complex Involved In Sperm-egg Fertilization.

The epididymis has an important role in the maturation of sperm for fertilization, but little is known about the epididymal molecules involved in sperm modifications during this process. We have previously described the expression pattern for an antigen in epididymal epithelial cells that reacts with the monoclonal antibody (mAb) TRA 54. Immunohistochemical and immunoblotting analyses suggest that the epitope of the epididymal antigen probably involves a sugar moiety that is released into the epididymal lumen in an androgen-dependent manner and subsequently binds to luminal sperm. Using column chromatography, SDS-PAGE with in situ digestion and mass spectrometry, we have identified the protein recognized by mAb TRA 54 in mouse epididymal epithelial cells. The ∼65 kDa protein is part of a high molecular mass complex (∼260 kDa) that is also present in the sperm acrosomal vesicle and is completely released after the acrosomal reaction. The amino acid sequence of the protein corresponded to that of albumin. Immunoprecipitates with anti-albumin antibody contained the antigen recognized by mAb TRA 54, indicating that the epididymal molecule recognized by mAb TRA 54 is albumin. RT-PCR detected albumin mRNA in the epididymis and fertilization assays in vitro showed that the glycoprotein complex containing albumin was involved in the ability of sperm to recognize and penetrate the egg zona pellucida. Together, these results indicate that epididymal-derived albumin participates in the formation of a high molecular mass glycoprotein complex that has an important role in egg fertilization.

Effects Of Partial Inhibition Of Respiratory Complex I On H2o 2 Production By Isolated Brain Mitochondria In Different Respiratory States.

The aim of this work was to characterize the effects of partial inhibition of respiratory complex I by rotenone on H2O2 production by isolated rat brain mitochondria in different respiratory states. Flow cytometric analysis of membrane potential in isolated mitochondria indicated that rotenone leads to uniform respiratory inhibition when added to a suspension of mitochondria. When mitochondria were incubated in the presence of a low concentration of rotenone (10 nm) and NADH-linked substrates, oxygen consumption was reduced from 45.9 ± 1.0 to 26.4 ± 2.6 nmol O2 mg(-1) min(-1) and from 7.8 ± 0.3 to 6.3 ± 0.3 nmol O2 mg(-1) min(-1) in respiratory states 3 (ADP-stimulated respiration) and 4 (resting respiration), respectively. Under these conditions, mitochondrial H2O2 production was stimulated from 12.2 ± 1.1 to 21.0 ± 1.2 pmol H2O2 mg(-1) min(-1) and 56.5 ± 4.7 to 95.0 ± 11.1 pmol H2O2 mg(-1) min(-1) in respiratory states 3 and 4, respectively. Similar results were observed when comparing mitochondrial preparations enriched with synaptic or nonsynaptic mitochondria or when 1-methyl-4-phenylpyridinium ion (MPP(+)) was used as a respiratory complex I inhibitor. Rotenone-stimulated H2O2 production in respiratory states 3 and 4 was associated with a high reduction state of endogenous nicotinamide nucleotides. In succinate-supported mitochondrial respiration, where most of the mitochondrial H2O2 production relies on electron backflow from complex II to complex I, low rotenone concentrations inhibited H2O2 production. Rotenone had no effect on mitochondrial elimination of micromolar concentrations of H2O2. The present results support the conclusion that partial complex I inhibition may result in mitochondrial energy crisis and oxidative stress, the former being predominant under oxidative phosphorylation and the latter under resting respiration conditions.

A New Platinum Complex With Tryptophan: Synthesis, Structural Characterization, Dft Studies And Biological Assays In Vitro Over Human Tumorigenic Cells.

A new platinum(II) complex with the amino acid L-tryptophan (trp), named Pt-trp, was synthesized and characterized. Elemental, thermogravimetric and ESI-QTOF mass spectrometric analyses led to the composition [Pt(C11H11N2O2)2]⋅6H2O. Infrared spectroscopic data indicate the coordination of trp to Pt(II) through the oxygen of the carboxylate group and also through the nitrogen atom of the amino group. The (13)C CP/MAS NMR spectroscopic data confirm coordination through the oxygen atom of the carboxylate group, while the (15)N CP/MAS NMR data confirm coordination of the nitrogen of the NH2 group to the metal. Density functional theory (DFT) studies were applied to evaluate the cis and trans coordination modes of trp to platinum(II). The trans isomer was shown to be energetically more stable than the cis one. The Pt-trp complex was evaluated as a cytotoxic agent against SK-Mel 103 (human melanoma) and Panc-1 (human pancreatic carcinoma) cell lines. The complex was shown to be cytotoxic over the considered cells.

Ecological Literacy And Beyond: Problem-based Learning For Future Professionals.

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

Synthesis, characterization, DFT and Td-dfT study of the [Fe(mnt)(L)(t-BuNC) 2] octahedral complex (L = phen, bipy)

FeBr2 has reacted with an equivalent of mnt2- (mnt = cis-1,2-dicyanoethylene-1,2-dithiolate) and the α-diimine L (L = 1,10'-phenantroline, 2,2'-bipyridine) in THF solution, and followed by adding of t-butyl-isocyanide to give [Fe(mnt)(L)(t-BuNC)2] neutral compound. The products were characterized by infrared, UV-visible and Mössbauer spectroscopy, besides thermogravimetric and conductivity data. The geometry in the equilibrium was calculated by the density functional theory and the electronic spectrum by the time-dependent. The experimental and theoretical results in good agreement have defined an octahedral geometry with two isocyanide neighbours. The π→π* intraligand electronic transition was not observed for cis-isomers in the near-IR spectral region.

O jogo de futebol : investigação de sua estrutura, de seus modelos e da inteligencia de jogo, do ponto de vista da complexidade

Universidade Estadual de Campinas . Faculdade de Educação Física

Procedimentos pedagogicos para o ensino das lutas : contextos e possibilidades

Universidade Estadual de Campinas . Faculdade de Educação Física