Measuring load of phosphate in the environment by passive sampling techniques: An introduction

Phosphorus has a number of indispensable biochemical roles, but its natural deposition and the low solubility of phosphates as well as their rapid transformation to insoluble forms make the element commonly the growth-limiting nutrient, particularly in aquatic ecosystems. Famously, phosphorus that reaches water bodies is commonly the main cause of eutrophication. This undesirable process can severely affect many aquatic biotas in the world. More management practices are proposed but long-term monitoring of phosphorus level is necessary to ensure that the eutrophication won't occur. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing flow proportional load as well as representative average of concentrations of phosphorus in the environment. Although some types of passive samplers are commercially available, their uses are still scarcely reported in the literature. In Japan, there is limited application of passive sampling technique to monitor phosphorus even in the field of agricultural environment. This paper aims to introduce the relatively new P-sampling techniques and their potential to use in environmental monitoring studies.

Applications of passive sampling techniques in monitoring organic pollutants in the environment

As there are a myriad of micro organic pollutants that can affect the well-being of human and other organisms in the environment the need for an effective monitoring tool is eminent. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing time-integrated load as well as representative average of concentrations of pollutants in the environment. Those techniques have been applied to monitor many pollutants caused by agricultural activities, i.e. residues of pesticides, veterinary drugs and so on. Several types of passive samplers are commercially available and their uses are widely accepted. However, not many applications of those techniques have been found in Japan, especially in the field of agricultural environment. This paper aims to introduce the field of passive sampling and then to describe some applications of passive sampling techniques in environmental monitoring studies related to the agriculture industry.

Raman spectroscopy techniques for detection of energetic materials at high and low concentration

This thesis presents the development of a rapid, sensitive and reproducible spectroscopic method for the detection of TNT in forensic and environmental applications. Simple nano sensors prepared by cost effective methods were utilized as sensitive platforms for the detection of TNT by surface enhanced Raman spectroscopy. The optimization of the substrate and the careful selection of a suitable recognition molecule contributed to the significant improvements of sensitive and selective targeting over current detection methods. The work presented in this thesis paves the way for effective detection and monitoring of explosives residues in law enforcement and environmental health applications.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

State-formation, teaching techniques, and globalization as aporia

Eleanor Smith [pseudonym], teacher : I was talking to the kids about MacDonalds*/I forget exactly what the context was*/I said ‘‘ah, the Americans call them French fries, and, you know, MacDonalds is an American chain and they call them French fries because the Americans call them French fries’’, and this little Australian kid in the front row, very Australian child, said to me, ‘‘I call them French fries!’’ . . . Um, a fourth grade boy whom I taught in 1993 at this school, the world basketball championships were on . . . Americans were playing their dream machine and the Boomers were up against them . . . and, ah, this boy was very interested in basketball . . . but it’s not in my blood, not in the way cricket is for example . . . Um, Um, and I said to this fellow, ‘‘um, well’’, I said, ‘‘Australia’s up against Dream Machine tomorrow’’. He [Jason, pseudonym] said, ‘‘Ah, you know, Boomers probably won’t win’’. . . . I said, ‘‘Well that’s sport, mate’’. I said, ‘‘You never know in sport. Australia might win’’. And he looked at me and he said, ‘‘I’m not going for Australia, I’m going for America’’. This is from an Australian boy! And I thought so strong is the hype, so strong is the, is the, power of the media, etc., that this boy is not [pause], I can’t tell you how outraged I was. Here’s me as an Australian and I don’t even support basketball, it’s not even my sport, um, but that he would respond like that because of the power of the American machine that’s converting kids’ minds, the way they think, where they’re putting their loyalties, etc. I was just appalled, but that’s where he was. And when I asked kids for their favourite place, he said Los Angeles.

Extended Kalman filters using explicit and derivative-free local linearizations

We propose three variants of the extended Kalman filter (EKF) especially suited for parameter estimations in mechanical oscillators under Gaussian white noises. These filters are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDE-s). Besides a basic linearization of the non-linear drift functions via one-term replacements, linearizations using replacements through explicit Euler and Newmark expansions are also attempted in order to ensure higher closeness of true solutions with the linearized ones. Thus, unlike the conventional EKF, the proposed filters do not need computing derivatives (tangent matrices) at any stage. The measurements are synthetically generated by corrupting with noise the numerical solutions of the SDE-s through implicit versions of these linearizations. In order to demonstrate the effectiveness and accuracy of the proposed methods vis-à-vis the conventional EKF, numerical illustrations are provided for a few single degree-of-freedom (DOF) oscillators and a three-DOF shear frame with constant parameters.

Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Simulated systems optimization through response surface techniques [Optimización de sistemas simulados a través de técnicas de superficie de respuesta]

The purpose of this article is to show the applicability and benefits of the techniques of design of experiments as an optimization tool for discrete simulation models. The simulated systems are computational representations of real-life systems; its characteristics include a constant evolution that follows the occurrence of discrete events along the time. In this study, a production system, designed with the business philosophy JIT (Just in Time) is used, which seeks to achieve excellence in organizations through waste reduction in all the operational aspects. The most typical tool of JIT systems is the KANBAN production control that seeks to synchronize demand with flow of materials, minimize work in process, and define production metrics. Using experimental design techniques for stochastic optimization, the impact of the operational factors on the efficiency of the KANBAN / CONWIP simulation model is analyzed. The results show the effectiveness of the integration of experimental design techniques and discrete simulation models in the calculation of the operational parameters. Furthermore, the reliability of the methodologies found was improved with a new statistical consideration.

Linear filtering in DCT IV/DST IV and MDCT/MDST domain

In this paper, expressions for convolution multiplication properties of DCT IV and DST IV are derived starting from equivalent DFT representations. Using these expressions methods for implementing linear filtering through block convolution in the DCT IV and DST IV domain are proposed. Techniques developed for DCT IV and DST IV are further extended to MDCT and MDST where the filter implementation is near exact for symmetric filters and approximate for non-symmetric filters. No additional overlapping is required for implementing the symmetric filtering in the MDCT domain and hence the proposed algorithm is computationally competitive with DFT based systems. Moreover, inherent 50% overlap between the adjacent frames used for MDCT/MDST domain reduces the blocking artifacts due to block processing or quantization. The techniques are computationally efficient for symmetric filters and provides a new alternative to DFT based convolution.

Study of electron states of solids by techniques of electron spectroscopy

Studies of valence bands and core levels of solids by photoelectron spectroscopy are described at length. Satellite phenomena in the core level spectra have been discussed in some detail and it has been pointed out that the intensity of satellites appearing next to metal and ligand core levels critically depends on the metal-ligand overlap. Use of photoelectron spectroscopy in investigating metal-insulator transitions and spin-state transitions in solids is examined. It is shown that relative intensities of metal Auger lines in transition metal oxides and other systems provide valuable information on the valence bands. Occurrence of interatomic Auger transitions in competition with intraatomic transitions is discussed. Applications of electron energy loss spectroscopy and other techniques of electron spectroscopy in the study of gas-solid interactions are briefly presented.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Collision avoidance between UAV clusters using swarm intelligence techniques

In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.

Adolescent writing development: Improving succinctness using the extended noun phrase

This study examined an aspect of adolescent writing development, specifically whether teaching secondary school students to use strategies to enhance succinctness in their essays changed the grammatical sophistication of their sentences. A quasi-experimental intervention was used to compare changes in syntactic complexity and lexical density between one-draft and polished essays. No link was demonstrated between the intervention and the changes. A thematic analysis of teacher interviews explored links between changes to student texts and teaching approaches. The study has implications for making syntactic complexity an explicit goal of student drafting.

Image reconstruction with laterally truncated projections in helical cone-beam CT: Linear prediction based projection completion techniques

Lateral or transaxial truncation of cone-beam data can occur either due to the field of view limitation of the scanning apparatus or iregion-of-interest tomography. In this paper, we Suggest two new methods to handle lateral truncation in helical scan CT. It is seen that reconstruction with laterally truncated projection data, assuming it to be complete, gives severe artifacts which even penetrates into the field of view. A row-by-row data completion approach using linear prediction is introduced for helical scan truncated data. An extension of this technique known as windowed linear prediction approach is introduced. Efficacy of the two techniques are shown using simulation with standard phantoms. A quantitative image quality measure of the resulting reconstructed images are used to evaluate the performance of the proposed methods against an extension of a standard existing technique.

Using simulation techniques to investigate methods to determine resistance of helminths to anthelmintic treatment

The widespread and increasing resistance of internal parasites to anthelmintic control is a serious problem for the Australian sheep and wool industry. As part of control programmes, laboratories use the Faecal Egg Count Reduction Test (FECRT) to determine resistance to anthelmintics. It is important to have confidence in the measure of resistance, not only for the producer planning a drenching programme but also for companies investigating the efficacy of their products. The determination of resistance and corresponding confidence limits as given in anthelmintic efficacy guidelines of the Standing Committee on Agriculture (SCA) is based on a number of assumptions. This study evaluated the appropriateness of these assumptions for typical data and compared the effectiveness of the standard FECRT procedure with the effectiveness of alternative procedures. Several sets of historical experimental data from sheep and goats were analysed to determine that a negative binomial distribution was a more appropriate distribution to describe pre-treatment helminth egg counts in faeces than a normal distribution. Simulated egg counts for control animals were generated stochastically from negative binomial distributions and those for treated animals from negative binomial and binomial distributions. Three methods for determining resistance when percent reduction is based on arithmetic means were applied. The first was that advocated in the SCA guidelines, the second similar to the first but basing the variance estimates on negative binomial distributions, and the third using Wadley’s method with the distribution of the response variate assumed negative binomial and a logit link transformation. These were also compared with a fourth method recommended by the International Co-operation on Harmonisation of Technical Requirements for Registration of Veterinary Medicinal Products (VICH) programme, in which percent reduction is based on the geometric means. A wide selection of parameters was investigated and for each set 1000 simulations run. Percent reduction and confidence limits were then calculated for the methods, together with the number of times in each set of 1000 simulations the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been said to occur. These simulations provide the basis for setting conditions under which the methods could be recommended. The authors show that given the distribution of helminth egg counts found in Queensland flocks, the method based on arithmetic not geometric means should be used and suggest that resistance be redefined as occurring when the upper level of percent reduction is less than 95%. At least ten animals per group are required in most circumstances, though even 20 may be insufficient where effectiveness of the product is close to the cut off point for defining resistance.