29,529 research outputs found
Analysis of reliable deployment of TDOA local positioning architectures
.Local Positioning Systems (LPS) are supposing an attractive research topic over the last few years. LPS are ad-hoc deployments of wireless sensor networks for particularly adapt to the environment characteristics in harsh environments. Among LPS, those based on temporal measurements stand out for their trade-off among accuracy, robustness and costs. But, regardless the LPS architecture considered, an optimization of the sensor distribution is required for achieving competitive results. Recent studies have shown that under optimized node distributions, time-based LPS cumulate the bigger error bounds due to synchronization errors. Consequently, asynchronous architectures such as Asynchronous Time Difference of Arrival (A-TDOA) have been recently proposed. However, the A-TDOA architecture supposes the concentration of the time measurement in a single clock of a coordinator sensor making this architecture less versatile. In this paper, we present an optimization methodology for overcoming the drawbacks of the A-TDOA architecture in nominal and failure conditions with regards to the synchronous TDOA. Results show that this optimization strategy allows the reduction of the uncertainties in the target location by 79% and 89.5% and the enhancement of the convergence properties by 86% and 33% of the A-TDOA architecture with regards to the TDOA synchronous architecture in two different application scenarios. In addition, maximum convergence points are more easily found in the A-TDOA in both configurations concluding the benefits of this architecture in LPS high-demanded applicationS
Exploring the effects of spinal cord stimulation for freezing of gait in parkinsonian patients
Dopaminergic replacement therapies (e.g. levodopa) provide limited to no response for axial motor symptoms including gait dysfunction and freezing of gait (FOG) in Parkinsonâs disease (PD) and Richardsonâs syndrome progressive supranuclear palsy (PSP-RS) patients. Dopaminergic-resistant FOG may be a sensorimotor processing issue that does not involve basal ganglia (nigrostriatal) impairment. Recent studies suggest that spinal cord stimulation (SCS) has positive yet variable effects for dopaminergic-resistant gait and FOG in parkinsonian patients. Further studies investigating the mechanism of SCS, optimal stimulation parameters, and longevity of effects for alleviating FOG are warranted. The hypothesis of the research described in this thesis is that mid-thoracic, dorsal SCS effectively reduces FOG by modulating the sensory processing system in gait and may have a dopaminergic effect in individuals with FOG. The primary objective was to understand the relationship between FOG reduction, improvements in upper limb visual-motor performance, modulation of cortical activity and striatal dopaminergic innervation in 7 PD participants. FOG reduction was associated with changes in upper limb reaction time, speed and accuracy measured using robotic target reaching choice tasks. Modulation of resting-state, sensorimotor cortical activity, recorded using electroencephalography, was significantly associated with FOG reduction while participants were OFF-levodopa. Thus, SCS may alleviate FOG by modulating cortical activity associated with motor planning and sensory perception. Changes to striatal dopaminergic innervation, measured using a dopamine transporter marker, were associated with visual-motor performance improvements. Axial and appendicular motor features may be mediated by non-dopaminergic and dopaminergic pathways, respectively. The secondary objective was to demonstrate the short- and long-term effects of SCS for alleviating dopaminergic-resistant FOG and gait dysfunction in 5 PD and 3 PSP-RS participants without back/leg pain. SCS programming was individualized based on which setting best improved gait and/or FOG responses per participant using objective gait analysis. Significant improvements in stride velocity, step length and reduced FOG frequency were observed in all PD participants with up to 3-years of SCS. Similar gait and FOG improvements were observed in all PSP-RS participants up to 6-months. SCS is a promising therapeutic option for parkinsonian patients with FOG by possibly influencing cortical and subcortical structures involved in locomotion physiology
Development of an Electrodialysis (ED) Desalination System Using Cement Mortar-Structured Zeolite Membranes from Corn Stover (Zea Mays) Ash
Zeolite A was synthesized from corn (Zea Mays) stover ash using a hydrothermal method. The corn stover ash and synthesized zeolite A were characterized by X-ray fluorescence (XRF), thermogravimetry (TG-DTA), Brunauer-Emmert-Teller (BET), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). The effects of calcination time, fusion ratios, and curing time were examined. The yield and cation exchange capacity (CEC) of the synthesized zeolite A were investigated using statistical test via the Response Surface Methodology employing a Central Composite Design through the multiple objective optimizations with desirability function. The obtained optimum parameters for the maximum % yield (75.08%) and CEC (2.282 meq/g) were as follows: calcination temperature (534.5oC), fusion ratios (1:1.708), and curing time (10.50 hours). The maximum overall desirability of 0.5970 was attained.
Response surface methodology by a two-level full factorial central composite design optimized the binder ratios, applied voltage and cell pair for cement mortar-structured zeolite membrane employing synthesized zeolite A in hydrogen form (zeolite HA) in an electrodialysis (ED) desalination system. All of the variables examined, specifically the binder ratio (15.00%), the applied voltage (15.00V), and the number of stacked cell pairs (3 pairs) were found to have an influence on sodium ion removal (80.68%). The developed model enables prediction of the separation percentage of an ED cell under various operating conditions.
In summary, an ED desalination system built on corn stover-based cement mortar-structured zeolite membranes was proven to be an efficient alternative method for treating saltwater or brackish water and ultimately producing fresh water. The study successfully demonstrated its aim to develop a technology application that is novel and is a potent alternative for an ED desalination system that is simple, economical, and readily available for rural communities to gain access to clean and freshwater
Interactive Sonic Environments: Sonic artwork via gameplay experience
The purpose of this study is to investigate the use of video-game technology in the design and implementation of interactive sonic centric artworks, the purpose of which is to create and contribute to the discourse and understanding of its effectiveness in electro-acoustic composition highlighting the creative process. Key research questions include: How can the language of electro-acoustic music be placed in a new framework derived from videogame aesthetics and technology? What new creative processes need to be considered when using this medium? Moreover, what aspects of 'play' should be considered when designing the systems? The findings of this study assert that composers and sonic art practitioners need little or no coding knowledge to create exciting applications and the myriad of options available to the composer when using video-game technology is limited only by imagination. Through a cyclic process of planning, building, testing and playing these applications the project revealed advantages and unique sonic opportunities in comparison to other sonic art installations. A portfolio of selected original compositions, both fixed and open are presented by the author to complement this study. The commentary serves to place the work in context with other practitioners in the field and to provide compositional approaches that have been taken
Anytime algorithms for ROBDD symmetry detection and approximation
Reduced Ordered Binary Decision Diagrams (ROBDDs) provide a dense and memory efficient representation of Boolean functions. When ROBDDs are applied in logic synthesis, the problem arises of detecting both classical and generalised symmetries. State-of-the-art in symmetry detection is represented by Mishchenko's algorithm. Mishchenko showed how to detect symmetries in ROBDDs without the need for checking equivalence of all co-factor pairs. This work resulted in a practical algorithm for detecting all classical symmetries in an ROBDD in O(|G|Âł) set operations where |G| is the number of nodes in the ROBDD. Mishchenko and his colleagues subsequently extended the algorithm to find generalised symmetries. The extended algorithm retains the same asymptotic complexity for each type of generalised symmetry. Both the classical and generalised symmetry detection algorithms are monolithic in the sense that they only return a meaningful answer when they are left to run to completion. In this thesis we present efficient anytime algorithms for detecting both classical and generalised symmetries, that output pairs of symmetric variables until a prescribed time bound is exceeded. These anytime algorithms are complete in that given sufficient time they are guaranteed to find all symmetric pairs. Theoretically these algorithms reside in O(nÂł+n|G|+|G|Âł) and O(nÂł+nÂČ|G|+|G|Âł) respectively, where n is the number of variables, so that in practice the advantage of anytime generality is not gained at the expense of efficiency. In fact, the anytime approach requires only very modest data structure support and offers unique opportunities for optimisation so the resulting algorithms are very efficient. The thesis continues by considering another class of anytime algorithms for ROBDDs that is motivated by the dearth of work on approximating ROBDDs. The need for approximation arises because many ROBDD operations result in an ROBDD whose size is quadratic in the size of the inputs. Furthermore, if ROBDDs are used in abstract interpretation, the running time of the analysis is related not only to the complexity of the individual ROBDD operations but also the number of operations applied. The number of operations is, in turn, constrained by the number of times a Boolean function can be weakened before stability is achieved. This thesis proposes a widening that can be used to both constrain the size of an ROBDD and also ensure that the number of times that it is weakened is bounded by some given constant. The widening can be used to either systematically approximate an ROBDD from above (i.e. derive a weaker function) or below (i.e. infer a stronger function). The thesis also considers how randomised techniques may be deployed to improve the speed of computing an approximation by avoiding potentially expensive ROBDD manipulation
Adaptive task selection using threshold-based techniques in dynamic sensor networks
Sensor nodes, like many social insect species, exist in harsh environments in large groups, yet possess very limited amount of resources. Lasting for as long as possible, and fulfilling the network purposes are the ultimate goals of sensor networks. However, these goals are inherently contradictory. Nature can be a great source of inspiration for mankind to find methods to achieve both extended survival, and effective operation. This work aims at applying the threshold-based action selection mechanisms inspired from insect societies to perform action selection within sensor nodes. The effect of this micro-model on the macro-behaviour of the network is studied in terms of durability and task performance quality. Generally, this is an example of using bio-inspiration to achieve adaptivity in sensor networks
3D printed Microneedles for Transdermal Drug Delivery
3D printing is a revolutionary manufacturing and prototyping technology that has altered the outlooks of numerous industrial and scientific fields since its introduction. Recently, it has attracted attention for its potential as a manufacturing tool for transdermal microneedles for drug delivery. In the present thesis, the 3D printability of solid and hollow microneedles via photopolymerisation-based 3D printing was investigated, aiming at establishing robust manufacturing strategies for reproducible, mechanically strong and versatile microneedles. The developed microneedles were employed as drug delivery systems for the treatment of diabetes via insulin administration.
Solid microneedles featuring different geometries were designed and 3D printed. It was demonstrated that the printing and post-printing parameters affected the printed quality, a finding that was employed to optimise the manufacturing strategy. Microneedle geometry was also found to have an impact on the piercing and fracture behaviour; however all microneedle designs were found to be mechanically safe upon application. The solid microneedles were subsequently coated with insulin-polymer films, using a 2D inkjet printing technology. The coating process achieved spatial control of the drug deposition, with quantitative accuracy. The microneedle geometry was shown to influence the morphology of the coating film, an effect that was pronounced during in the in vitro delivery studies of insulin to porcine skin.
Furthermore, hollow microneedles were designed and 3D printed, featuring different heights. Two photopolymerisation-based technologies were studied, and their performance was compared. The key influential parameters of the printing outcome and microneedle quality were identified to be the printing angle and the size of the microneedle opening. The hollow microneedles were found to be effective in piercing porcine skin without structural damaging. The hollow microneedles were incorporated into complex patches with internal microfluidic structures for the provision and distribution of drug-containing solutions. The developed complex hollow microneedle patches were coupled with a microelectromechanical system to create a novel platform device for controlled, personalised transdermal drug delivery. Advanced imaging techniques revealed that the device achieved distribution of the liquid within porcine skin tissue without the creation of depots that would delay absorption. The device was evaluated for its efficacy to transdermally deliver a model dye and insulin in vitro. In vivo trials were also conducted using diabetic rodents, with the device achieving faster onset of insulin action and sustained glycemic control, in comparison to subcutaneous injections.
Overall, the findings of the present research are anticipated to elucidate key problematic areas associated with the application of 3D printing for microneedle manufacturing and propose feasible solutions. The outermost goal of this work is to contribute to the advancement of knowledge in the field of 3D printed transdermal drug delivery systems, in order to bring them one step closer to their adoption in the clinical setting
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Optimal strategies of automakers with demand and credit price disruptions under the dual-credit policy
In this paper, a production and pricing decision model for automakers under the dual-credit policy is formulated. Then, with consideration of demand and credit price disruptions, a nonlinear programming model that maximizes automakersâ profit and constrains the production of fuel vehicles (FVs) and new energy vehicles (NEVs) is investigated. Furthermore, four strategies that involve adjusting the production or price of FVs and NEVs are proposed, and four optimal solutions for each strategy are obtained. Finally, 16 scenarios are comprehensively analyzed, and a case study involving demand and credit price disruptions is conducted. The results show that the dual-credit policy has a positive impact on the development of NEVs, especially in early stages of NEV development. The FV credit coefficient has a significantly positive impact on the probability of automakers adopting adjustment strategies, while the NEV credit coefficient has almost no such impact. Moreover, automakers are inclined to adjust the prices of NEVs or the production of FVs to cope with demand and credit price disruptions
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From data to knowledge: integrating observational data to trace phytoplankton dynamics in a changing world
Phytoplankton are a fundamental component of marine systems. They are involved in the global regulation and functioning of biogeochemical and trophic processes and are strictly connected to human health and well-being through the provision of essential ecosystem services. Despite their fundamental importance, there is still no broad consensus on the mechanisms underlying their seasonal and interannual variability, while even less is known about the ecology of individual species and their response to climate variability given the scarcity of comprehensive long-term observation sets. Here, by taking advantage of high- frequency oceanographic and biological data collected over more than 25 years in a coastal pelagic Mediterranean site, I applied a set of statistical methods in order to investigate different aspects of community and individual speciesâ ecology, with a particular emphasis on the environmental factors and the mechanisms underlying phytoplankton phenology. Further, I analyzed long-term meteorological variations in the area and their relationships to large-scale climatic oscillation in order to address their impact on the planktonic system during the different seasons of the year. Finally, I integrated the data from 10 worldwide- distributed coastal time-series and investigated the adaptive potential of ubiquitous phytoplankton species to local conditions using a niche-based approach. The results of these analyses highlighted an impressive regularity in the annual occurrence of phytoplankton community and individual taxa despite a highly variable environment. Light was the predominant factor regulating species turnover and replacement and seemed to regulate endogenous biological processes associated with species-specific phenological patterns. Over the time series, a considerable stability was shown by individual species and the whole community, while the effects of climate fluctuation on the abiotic and biotic components revealed a strong dependence on the season. The comparison of phytoplankton niches across diverse biogeographical regions supported the idea of evolutionary adaptation, further emphasizing the importance of long-term ecological observations in the context of climate change. Overall, the results of these studies highlight the considerable resilience and the active role that phytoplankton plays under different environmental constraints, which contrasts the view of these organisms as passively undergoing external changes that occur at different temporal scales in their habitat, and show how, under certain conditions, endogenous biological processes prevail over environmental forcing
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