An analytical framework for quantifying aquifer response time scales associated with transient boundary conditions

A major challenge in studying coupled groundwater and surface-water interactions arises from the considerable difference in the response time scales of groundwater and surface-water systems affected by external forcings. Although coupled models representing the interaction of groundwater and surface-water systems have been studied for over a century, most have focused on groundwater quantity or quality issues rather than response time. In this study, we present an analytical framework, based on the concept of mean action time (MAT), to estimate the time scale required for groundwater systems to respond to changes in surface-water conditions. MAT can be used to estimate the transient response time scale by analyzing the governing mathematical model. This framework does not require any form of transient solution (either numerical or analytical) to the governing equation, yet it provides a closed form mathematical relationship for the response time as a function of the aquifer geometry, boundary conditions, and flow parameters. Our analysis indicates that aquifer systems have three fundamental time scales: (i) a time scale that depends on the intrinsic properties of the aquifer; (ii) a time scale that depends on the intrinsic properties of the boundary condition, and; (iii) a time scale that depends on the properties of the entire system. We discuss two practical scenarios where MAT estimates provide useful insights and we test the MAT predictions using new laboratory-scale experimental data sets.

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

Reduced complexity on-line estimation of hidden Markov model parameters

In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

On-line estimation of Allan variance parameters

A new online method is presented for estimation of the angular random walk and rate random walk coefficients of IMU (inertial measurement unit) gyros and accelerometers. The online method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph. Allan variance graphs have large off-line computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of O(100) calculations per data sample.

On fundamental limitations for rudder roll stabilization of ships

The main purpose of the rudder in ships is course keeping. However, the rudder can also be used, in some cases, to reject undesirable wave produced rolling motions. From a fundamental point of view, the main issues associated with this problem are the presence of a nonminimum phase zero and the single input two output nature of the system. In this paper, the limitations imposed on the achievable closed loop performance due to these issues are analyzed. This gives a deeper understanding of the problem and leads to conclusions regarding the inherent design trade-offs which hold regardless of the control strategy used.

Thin films and nanostructures of niobium pentoxide : fundamental properties, synthesis methods and applications

As one of the transition metal oxides, niobium pentoxide (Nb2O5) offers a broad variety of properties that make it a potentially useful and highly applicable material in many different areas. In comparison to many other transition metal oxides, Nb2O5 has received relatively little attention, which presents a significant opportunity for future investigations aimed at fundamentally understanding this material and finding new and interesting applications for it. In this article, a general overview of Nb2O5 is presented which focuses on its fundamental properties, synthesis methods and recent applications, along with a discussion on future research directions relevant to this material.

The impact of incidents on macroscopic fundamental diagrams

The macroscopic fundamental diagram (MFD) traffic modelling method has been proved for large urban roads and freeway networks, but hysteresis and scatter have been found in both such networks. This paper investigates how incident variables affect the shape and scatter of the MFD using both simulated data and real data collected from the M3 Pacific motorway in Brisbane, Australia. Three key components of incidents are investigated based on the simulated data (i.e. incident location, incident duration and traffic demand). The results based on simulated data indicate that the diagram shape is a property not only of the network itself but also of the incident variables. Diagrams for three types of real incidents (crash, hazard and vehicle breakdown) are explored separately. The results based on the empirical data are consistent with the simulated results. The hysteresis phenomenon occurs both upstream and downstream of the incident location, but for opposite hysteresis loops. The gradient of the upstream diagram is greater than that downstream on the incident site, when traffic demand is for an off-peak period.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Porosity: Establishing the relationship between drying parameters and dried food quality [SpringerBriefs in Food, Health, and Nutrition]

The preservation technique of drying offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Variations in porosity are just one of the microstructural changes that take place during the drying of most food materials. Some studies found that there may be a relationship between porosity and the properties of dried foods. However, no conclusive relationship has yet been established in the literature. This paper presents an overview of the factors that influence porosity, as well as the effects of porosity on dried food quality attributes. The effect of heat and mass transfer on porosity is also discussed along with porosity development in various drying methods. After an extensive review of the literature concerning the study of porosity, it emerges that a relationship between process parameters, food qualities, and sample properties can be established. Therefore, we propose a hypothesis of relationships between process parameters, product quality attributes, and porosity.

Sealing the leak on classical NTRU signatures

Initial attempts to obtain lattice based signatures were closely related to reducing a vector modulo the fundamental parallelepiped of a secret basis (like GGH [9], or NTRUSign [12]). This approach leaked some information on the secret, namely the shape of the parallelepiped, which has been exploited on practical attacks [24]. NTRUSign was an extremely efficient scheme, and thus there has been a noticeable interest on developing countermeasures to the attacks, but with little success [6]. In [8] Gentry, Peikert and Vaikuntanathan proposed a randomized version of Babai’s nearest plane algorithm such that the distribution of a reduced vector modulo a secret parallelepiped only depended on the size of the base used. Using this algorithm and generating large, close to uniform, public keys they managed to get provably secure GGH-like lattice-based signatures. Recently, Stehlé and Steinfeld obtained a provably secure scheme very close to NTRUSign [26] (from a theoretical point of view). In this paper we present an alternative approach to seal the leak of NTRUSign. Instead of modifying the lattices and algorithms used, we do a classic leaky NTRUSign signature and hide it with gaussian noise using techniques present in Lyubashevky’s signatures. Our main contributions are thus a set of strong NTRUSign parameters, obtained by taking into account latest known attacks against the scheme, a statistical way to hide the leaky NTRU signature so that this particular instantiation of CVP-based signature scheme becomes zero-knowledge and secure against forgeries, based on the worst-case hardness of the O~(N1.5)-Shortest Independent Vector Problem over NTRU lattices. Finally, we give a set of concrete parameters to gauge the efficiency of the obtained signature scheme.