Development of polymeric drug delivery vehicles for targeted cancer therapy

The aim of my Ph. D. thesis is to generalize a method for targeted anti-cancer drug delivery. Hydrophilic polymer-drug conjugates involve complicated synthesis; drug-encapsulated polymeric nanoparticles limit the loading capability of payloads. This thesis introduces the concept of nanoconjugates to overcome difficulties in synthesis and formulation. Drugs with hydroxyl group are able to initiate polyester synthesis in a regio- and chemo- selective way, with the mediation of ligand-tunable Zinc catalyst. Herein, three anti-cancer drugs are presented to demonstrate the high efficiency and selectivity in the method (Chapter 2-4). The obtained particles are stable in salt solution, releasing drugs over weeks in controlled manner. With the conjugation of aptamer, particles are capable to target prostate cancer cells in vitro. These results open the gateway to evaluate the in vivo efficacy of nanoconjugates for target cancer therapy (Chapter 5). Mechanism study of the polymerization leads to the discovery of chemosite selective synthesis of prodrugs with acrylate functional groups. Functional copolymer-drug conjugates will expand the scope of nanoconjugates (Chapter 6). Liposome-aptamer targeting drug delivery vehicle is well studied to achieve reversible cell-specific delivery of non-hydoxyl drugs e.g. cisplatin (Chapter 7). New monomers and polymerization mechanisms are explored for polyester in order to synthesize nanoconjugates with variety on properties (Chapter 8). Initial efforts to apply this type of prodrugs will be focused on the preparation of hydrogels for stem cell research (Chapter 9).

An explanatory model of underwater adaptation

The underwater environment is an extreme environment that requires a process of human adaptation with specific psychophysiological demands to ensure survival and productive activity. From the standpoint of existing models of intelligence, personality and performance, in this explanatory study we have analyzed the contribution of individual differences in explaining the adaptation of military personnel in a stressful environment. Structural equation analysis was employed to verify a model representing the direct effects of psychological variables on individual adaptation to an adverse environment, and we have been able to confirm, during basic military diving courses, the structural relationships among these variables and their ability to predict a third of the variance of a criterion that has been studied very little to date. In this way, we have confirmed in a sample of professionals (N = 575) the direct relationship of emotional adjustment, conscientiousness and general mental ability with underwater adaptation, as well as the inverse relationship of emotional reactivity. These constructs are the psychological basis for working under water, contributing to an improved adaptation to this environment and promoting risk prevention and safety in diving activities.

A surface plasmon resonance system for the underwater detection of domoic acid

Over the past decade Surface Plasmon Resonance (SPR) techniques have been applied to the measurement of numerous analytes. In this article, an SPR biosensor system deployed from an oceanographic vessel was used to measure dissolved domoic acid (DA), a common and harmful phycotoxin produced by certain microalgae species belonging to the genus Pseudo-nitzschia. During the biosensor deployment, concentrations of Pseudo-nitzschia cells were very low over the study area and measured DA concentrations were below detection. However, the in situ operational detection limit of the system was established using calibrated seawater solutions spiked with DA. The system could detect the toxin at concentrations as low as 0.1 ng mL−1 and presented a linear dynamic range from 0.1 ng mL−1 to 2.0 ng mL−1. This sensor showed promise for in situ detection of DA.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

International workshop on "Different survey methods for coral reef fish, including methods based on underwater video"

In September 2013, staff from the University of the South Pacific (USP) Honiara campus, the Secretariat of the Pacific Community (SPC) and IFREMER (UR LEADNC, AMBIO project) in New Caledonia, and the French Institute for Pacific Coral Reefs (IRCP) in Moorea, French Polynesia, co-facilitated a workshop entitled “Different survey methods of coral reef fish, including the methods based on underwater video”. The workshop was attended by students from USP, NGO and fisheries officers. They were trained to several underwater visual census techniques and to the STAVIRO video-based technique, including both field work and data analysis.

A Ride-Sharing System with High Capacity Vehicles and Flexible Meeting Points

In many major cities, fixed route transit systems such as bus and rail serve millions of trips per day. These systems have people collect at common locations (the station or stop), and board at common times (for example according to a predetermined schedule or headway). By using common service locations and times, these modes can consolidate many trips that have similar origins and destinations or overlapping routes. However, the routes are not sensitive to changing travel patterns, and have no way of identifying which trips are going unserved, or are poorly served, by the existing routes. On the opposite end of the spectrum, personal modes of transportation, such as a private vehicle or taxi, offer service to and from the exact origin and destination of a rider, at close to exactly the time they desire to travel. Despite the apparent increased convenience to users, the presence of a large number of small vehicles results in a disorganized, and potentially congested road network during high demand periods. The focus of the research presented in this paper is to develop a system that possesses both the on-demand nature of a personal mode, with the efficiency of shared modes. In this system, users submit their request for travel, but are asked to make small compromises in their origin and destination location by walking to a nearby meeting point, as well as slightly modifying their time of travel, in order to accommodate other passengers. Because the origin and destination location of the request can be adjusted, this is a more general case of the Dial-a-Ride problem with time windows. The solution methodology uses a graph clustering algorithm coupled with a greedy insertion technique. A case study is presented using actual requests for taxi trips in Washington DC, and shows a significant decrease in the number of vehicles required to serve the demand.

Projeto e Construção de um Veleiro Autónomo, utilizando materiais compósitos, Impressão a 3D e Aprendizagem Máquina

Este trabalho consistiu no projeto e construção de um veleiro autónomo de pequena escala. No início do trabalho, é feito um estudo acerca dos diferentes tipos de veículos autónomos, dando mais enfase aos veleiros. Em seguida, é iniciado o projeto do casco do veleiro, aplicando conceitos básicos de Arquitetura Naval. A forma do casco é desenhada com recurso ao programa DELFT Ship Free, onde são realizados estudos hidrodinâmicos do mesmo. Posteriormente é retratado a construção do casco projetado, com recurso a materiais compósitos e impressão 3D de componentes do veleiro. São ainda descritos os sensores, controladores, atuadores e programação desenvolvida para o veleiro. É também realizado um estudo sumário da estimativa de consumos e autonomia do sistema. No final, encontram-se os resultados obtidos das provas de mar efetuadas ao veleiro.

Libs in cultural heritage: recognition and identification of objects in an underwater archaeological shipwreck

Nowadays, one of the most important areas of interest in archeology is the characterization of the submersed cultural heritage. Mediterranean Sea is rich in archaeological findings due to storms, accidents and naval battles since prehistoric times. Chemical analysis of submerged materials is an extremely valuable source of information on the origin and precedence of the wrecks, and also the raw materials employed during the manufacturing of the objects found in these sites. Nevertheless, sometimes it is not possible to extract the archaeological material from the marine environment due to size of the sample, the legislation or preservation purposes. In these cases, the in-situ analysis turns into the only alternative for obtaining information. In spite of this demand, no analytical techniques are available for the in-situ chemical characterization of underwater materials. The versatility of laser-induced breakdown spectroscopy (LIBS) has been successfully tested in oceanography 1. Advantages such as rapid and in situ analysis with no sample preparation make LIBS a suitable alternative for field measurements. To further exploit the inherent advantages of the technology, a mobile fiber-based LIBS platform capable of performing remote measurements up to 50 meters range has been designed for the recognition and identification of artworks in underwater archaeological shipwrecks. The LIBS prototype featured both single-pulse (SP-LIBS) and multi-pulse excitation (MP-LIBS) 2. The use of multi-pulse excitation allowed an increased laser beam energy (up to 95 mJ) transmitted through the optical fiber. This excitation mode results in an improved performance of the equipment in terms of extended range of analysis (to a depth of 50 m) and a broader variety of samples to be analyzed (i.e., rocks, marble, ceramics and concrete). In the present work, the design and construction considerations of the instrument are reported and its performance is discussed on the basis of the spectral response, the remote irradiance achieved upon the range of analysis and its influence on plasma properties, as well as the effect of the laser pulse duration and purge gas to the LIBS signal. Also, to check the reliability and reproducibility of the instrument for field analysis several robustness tests were performed outside the lab. Finally, the capability of this instrument was successfully demonstrated in an underwater archaeological shipwreck (San Pedro de Alcántara, Malaga).

MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES

Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are researching on hybrid electric vehicles where two different power devices are used to propel a vehicle. This research studies the development and testing of a dynamic model for Prius 2010 Hybrid Synergy Drive (HSD), a power-split device. The device was modeled and integrated with a hybrid vehicle model. To add an electric only mode for vehicle propulsion, the hybrid synergy drive was modified by adding a clutch to carrier 1. The performance of the integrated vehicle model was tested with UDDS drive cycle using rule-based control strategy. The dSPACE Hardware-In-the-Loop (HIL) simulator was used for HIL simulation test. The HIL simulation result shows that the integration of developed HSD dynamic model with a hybrid vehicle model was successful. The HSD model was able to split power and isolate engine speed from vehicle speed in hybrid mode.

IMPACT OF PLUG-IN ELECTRIC VEHICLES AND WIND GENERATORS ON HARMONIC DISTORTION OF ELECTRIC DISTRIBUTION SYSTEMS

Harmonic distortion on voltages and currents increases with the increased penetration of Plug-in Electric Vehicle (PEV) loads in distribution systems. Wind Generators (WGs), which are source of harmonic currents, have some common harmonic profiles with PEVs. Thus, WGs can be utilized in careful ways to subside the effect of PEVs on harmonic distortion. This work studies the impact of PEVs on harmonic distortions and integration of WGs to reduce it. A decoupled harmonic three-phase unbalanced distribution system model is developed in OpenDSS, where PEVs and WGs are represented by harmonic current loads and sources respectively. The developed model is first used to solve harmonic power flow on IEEE 34-bus distribution system with low, moderate, and high penetration of PEVs, and its impact on current/voltage Total Harmonic Distortions (THDs) is studied. This study shows that the voltage and current THDs could be increased upto 9.5% and 50% respectively, in case of distribution systems with high PEV penetration and these THD values are significantly larger than the limits prescribed by the IEEE standards. Next, carefully sized WGs are selected at different locations in the 34-bus distribution system to demonstrate reduction in the current/voltage THDs. In this work, a framework is also developed to find optimal size of WGs to reduce THDs below prescribed operational limits in distribution circuits with PEV loads. The optimization framework is implemented in MATLAB using Genetic Algorithm, which is interfaced with the harmonic power flow model developed in OpenDSS. The developed framework is used to find optimal size of WGs on the 34-bus distribution system with low, moderate, and high penetration of PEVs, with an objective to reduce voltage/current THD deviations throughout the distribution circuits. With the optimal size of WGs in distribution systems with PEV loads, the current and voltage THDs are reduced below 5% and 7% respectively, which are within the limits prescribed by IEEE.

Unmanned Aerial Vehicle: tecnologie e prospettive future

Partendo dalla definizione di UAV e UAS, arrivando a quella di drone, nella tesi saranno definiti i termini precedenti, ossia un sistema aereo senza pilota a bordo, la nascita del termine drone e le tendenze attuali. Dopo una precisa classificazione nelle quattro categorie principali (droni per hobbisti, commerciali e militari di me- dia grandezza, militari specifici di grandi dimensioni e stealth da combattimento) saranno descritti gli ambiti di utilizzo: da un lato quello militare e della sicurezza, dall’altro quello civile e scientifico. I capitoli centrali della tesi saranno il cuore dell’opera: l’architettura dell’UAV sarà descritta analizzando la totalità delle sue componenti, sia hardware che software. Verranno, quindi, analizzati i problemi relativi alla sicurezza, focalizzandosi sull’hacking di un UAV, illustrandone le varie tecniche e contromisure (tra cui anche come nascondersi da un drone). Il lavoro della tesi prosegue nei capitoli successivi con un’attenta trattazione della normativa vigente e dell’etica dei droni (nonché del diritto ad uccidere con tali sistemi). Il capitolo relativo alla tecnologia stealth sarà importante per capire le modalità di occultamento, le tendenze attuali e i possibili sviluppi futuri degli UAV militari da combattimento. Il capitolo finale sugli sviluppi futuri esporrà le migliorie tecnologiche e gli obiettivi degli UAV negli anni a venire, insieme ad eventuali utilizzi sia militari che civili. La ricerca sarà orientata verso sistemi miniaturizzati, multiple UAV e swarming.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Underwater survey of ichthyofauna of eastern Atlantic seamounts: Gettysburg and Ormond (Gorringe Bank)

Gettysburg and Ormond are seamounts belonging to the Gorringe Bank, which is located on the Europen-African plate boundary. Given the importance of these oceanic features for understanding marine biodiversity patterns, two surveys were carried out in 1998 (Gettysburg) and 1999 (Ormond) using diving, photography and video for species identification and abundance evaluation. Of the 9 fish species found at Gettysburg and 11 at Ormond, 6 were common to both sites and these included the dominant species: the oceanic and commercially important, Seriola rivoliana, and the coastal, typically Atlantic-Mediterranean Coris julis and Anthias anthias. The strong representation of coastal, demersal and Atlantic-Mediterranean species in the Gorringe Bank region and the presence of Abudefduf luridus, an endemic Macaronesian species, at Gettysburg suggests that the upper part of these seamounts may have acted and still act as “stepping stones” for the dispersal of coastal species.

Modelling and Optimization of Energy Management Strategies for Hybrid Vehicles

In the last decades the automotive sector has seen a technological revolution, due mainly to the more restrictive regulation, the newly introduced technologies and, as last, to the poor resources of fossil fuels remaining on Earth. Promising solution in vehicles’ propulsion are represented by alternative architectures and energy sources, for example fuel-cells and pure electric vehicles. The automotive transition to new and green vehicles is passing through the development of hybrid vehicles, that usually combine positive aspects of each technology. To fully exploit the powerful of hybrid vehicles, however, it is important to manage the powertrain’s degrees of freedom in the smartest way possible, otherwise hybridization would be worthless. To this aim, this dissertation is focused on the development of energy management strategies and predictive control functions. Such algorithms have the goal of increasing the powertrain overall efficiency and contextually increasing the driver safety. Such control algorithms have been applied to an axle-split Plug-in Hybrid Electric Vehicle with a complex architecture that allows more than one driving modes, including the pure electric one. The different energy management strategies investigated are mainly three: the vehicle baseline heuristic controller, in the following mentioned as rule-based controller, a sub-optimal controller that can include also predictive functionalities, referred to as Equivalent Consumption Minimization Strategy, and a vehicle global optimum control technique, called Dynamic Programming, also including the high-voltage battery thermal management. During this project, different modelling approaches have been applied to the powertrain, including Hardware-in-the-loop, and diverse powertrain high-level controllers have been developed and implemented, increasing at each step their complexity. It has been proven the potential of using sophisticated powertrain control techniques, and that the gainable benefits in terms of fuel economy are largely influenced by the chose energy management strategy, even considering the powerful vehicle investigated.