An application of data mining to fruit and vegetable sample identification using Gas Chromatography-Mass Spectrometry

One of the uses of Gas Chromatography-Mass Spectrometry (GC-MS) is in the detection of pesticide residues in fruit and vegetables. In a high throughput laboratory there is the potential for sample swaps or mislabelling, as once a sample has been pre-processed to be injected into the GC-MS analyser, it is no longer distinguishable by eye. Possible consequences of such mistakes can be the destruction of large amounts of actually safe produce or pesticide-contaminated produce reaching the consumer. For the purposes of food safety and traceability, it can also be extremely valuable to know the source (country of origin) of a food product. This can help uncover fraudulent attempts of trying to sell food originating from countries deemed unsafe. In this study, we use the workflow environment ADAMS to examine whether we can determine the fruit/vegetable, and the country of origin of a sample from a GC-MS chromatogram. A workflow is used to generate data sets using different data pre-processing methods, and data representations from a database of over 8000 GC-MS chromatograms, consisting of more than 100 types of fruit and vegetables from more than 120 countries. A variety of classification algorithms are evaluated using the WEKA data mining workbench. We demonstrate excellent results, both for the determination of fruit/vegetable type and for the country of origin, using a histogram of ion counts, and Classification by Regression using Random Regression Forest with PLS-transformed data

Predicting polycyclic aromatic hydrocarbon concentrations in soil and water samples

Polycyclic Aromatic Hydrocarbons (PAHs) are compounds found in the environment that can be harmful to humans. They are typically formed due to incomplete combustion and as such remain after burning coal, oil, petrol, diesel, wood, household waste and so forth. Testing laboratories routinely screen soil and water samples taken from potentially contaminated sites for PAHs using Gas Chromatography Mass Spectrometry (GC-MS). A GC-MS device produces a chromatogram which is processed by an analyst to determine the concentrations of PAH compounds of interest. In this paper we investigate the application of data mining techniques to PAH chromatograms in order to provide reliable prediction of compound concentrations. A workflow engine with an easy-to-use graphical user interface is at the heart of processing the data. This engine allows a domain expert to set up workflows that can load the data, preprocess it in parallel in various ways and convert it into data suitable for data mining toolkits. The generated output can then be evaluated using different data mining techniques, to determine the impact of preprocessing steps on the performance of the generated models and for picking the best approach. Encouraging results for predicting PAH compound concentrations, in terms of correlation coefficients and root-mean-squared error are demonstrated

A multi-object spectral imaging instrument

We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the CCD for wavelength. A CMOS camera on the front port of the microscope allows the full image of the sample to be displayed and can also be used for particle tracking, providing spectra of multiple particles moving in the sample. We demonstrate the system by recording the spectra of multiple fluorescent beads in aqueous solution and from multiple points along a microscope sample channel containing a mixture of red and blue dye

Profiles of Temperament and Perfectionism in High Ability College Students

Different physical, mental, and motivational outcomes for perfectionistic strivings and perfectionistic concerns indicate that individuals have different experiences of perfectionism. Although research has focused on parenting practices as a factor related to these differences, little research has examined the impact of temperamental differences on perfectionism. In the current study, 434 high ability undergraduate students completed perfectionism, adult temperament, and personality measures. Latent class analysis that examined the patterns among the relationships between self-oriented perfectionism, socially prescribed perfectionism, and four dimensions of adult temperament (negative affect, effortful control, extraversion, orienting sensitivity) revealed three distinct subgroups. Although the largest subgroup demonstrated patterns consistent with prior research on perfectionism (e.g., perfectionism associated with negative affect), two other subgroups revealed separate patterns that were inconsistent with prior research (e.g., one subgroup had negative relationships between negative affect and both types of perfectionism). Our results demonstrate that temperament may play an important role in explaining the heterogeneity among perfectionists

Image classification using class-agnostic object detection

Human-in-the-loop interfaces for machine learning provide a promising way to reduce the annotation effort required to obtain an accurate machine learning model, particularly when it is used with transfer learning to exploit existing knowledge gleaned from another domain. This paper explores the use of a human-in-the-loop strategy that is designed to build a deep-learning image classification model iteratively using successive batches of images that the user labels. Specifically, we examine whether class-agnostic object detection can improve performance by providing a focus area for image classification in the form of a bounding box. The goal is to reduce the amount of effort required to label a batch of images by presenting the user with the current predictions of the model on a new batch of data and only requiring correction of those predictions. User effort is measured in terms of the number of corrections made. Results show that the use of bounding boxes always leads to fewer corrections. The benefit of a bounding box is that it also provides feedback to the user because it indicates whether or not the classification of the deep learning model is based on the appropriate part of the image. This has implications for the design of user interfaces in this application scenario

The role of precuneus and left inferior frontal cortex during source memory episodic retrieval

The posterior medial parietal cortex and left prefrontal cortex (PFC) have both been implicated in the recollection of past episodes. In a previous study, we found the posterior precuneus and left lateral inferior frontal cortex to be activated during episodic source memory retrieval. This study further examines the role of posterior precuneal and left prefrontal activation during episodic source memory retrieval using a similar source memory paradigm but with longer latency between encoding and retrieval. Our results suggest that both the precuneus and the left inferior PFC are important for regeneration of rich episodic contextual associations and that the precuneus activates in tandem with the left inferior PFC during correct source retrieval. Further, results suggest that the left ventro-lateral frontal region/ frontal operculum is involved in searching for task-relevant information (BA 47) and subsequent monitoring or scrutiny (BA 44/45) while regions in the dorsal inferior frontal cortex are important for information selection (BA 45/46). (C) 2005 Elsevier Inc. All rights reserved.NIGMS NIH HHS [2 T32 GM 07266]info:eu-repo/semantics/publishedVersio

Theories of identity and the analysis of face

This paper explores the insights that theories of identity can offer for the conceptualisation and analysis of face. It argues that linguists will benefit from taking a multidisciplinary approach, and that by drawing on theory and research in other disciplines, especially in social psychology, they will gain a clearer and deeper understanding of face. The paper starts by examining selected theories of identity, focusing in particular on Simon's (2004) self-respect model of identity and Brewer and Gardner's (1996) theory of levels of identity. Key features from these theories are then applied to the conceptualisation and analysis of face. With the help of authentic examples, the paper demonstrates how inclusion of these multiple perspectives can offer a richer and more comprehensive understanding of face and the frameworks needed for analysing it

The Conservation Ideological State Apparatus

This article considers Louis Althusser's theory of the ideological state apparatuses (ISAs) for advancing political ecology scholarship on the functioning of the state in violent environments. I reflect on a series of events in which a state forest department in South India attempted to recast violent conflicts between themselves and local communities over access to natural resources and a protected area as a debate over human-wildlife conflicts. Through the example of conservation as ideology in Wayanad, Kerala, I show how the ISAs articulate the functioning of ideology within the state apparatuses in order for us to understand the larger mechanics of the state apparatus and the reproduction of the relations of production necessary for the reproduction of capitalism. Revisiting the ISAs as a theoretical framework for studies in political ecology and conservation is timely given the resurgence of militarised conservation tactics, the emancipatory aims of Althusser's theory, and political ecology's turn towards praxis

A Comprehensive Three-Dimensional Model of the Cochlea

The human cochlea is a remarkable device, able to discern extremely small amplitude sound pressure waves, and discriminate between very close frequencies. Simulation of the cochlea is computationally challenging due to its complex geometry, intricate construction and small physical size. We have developed, and are continuing to refine, a detailed three-dimensional computational model based on an accurate cochlear geometry obtained from physical measurements. In the model, the immersed boundary method is used to calculate the fluid-structure interactions produced in response to incoming sound waves. The model includes a detailed and realistic description of the various elastic structures present. In this paper, we describe the computational model and its performance on the latest generation of shared memory servers from Hewlett Packard. Using compiler generated threads and OpenMP directives, we have achieved a high degree of parallelism in the executable, which has made possible several large scale numerical simulation experiments that study the interesting features of the cochlear system. We show several results from these simulations, reproducing some of the basic known characteristics of cochlear mechanics.Comment: 22 pages, 5 figure

Growth variations and scattering mechanisms in metamorphic In0.75Ga0.25As/In-0.75 Al0.25As quantum wells grown by molecular beam epitaxy

Modulation doped metamorphic In0.75Ga0.25As/In0.75Al0.25As quantum wells (QW) were grown on GaAs substrates by molecular beam epitaxy (MBE) with step-graded buffer layers. The electron mobility of the QWs has been improved by varying the MBE growth conditions, including substrate temperature, arsenic over pressure and modulation doping level. By applying a bias voltage to SiO2 insulated gates, the electron density in the QW can be tuned from 1×1011 to 5.3×1011 cm−2. A peak mobility of 4.3×105 cm2V−1s−1 is obtained at 3.7×1011 cm−2 at 1.5 K before the onset of second subband population. To understand the evolution of mobility, transport data is fitted to a model that takes into account scattering from background impurities, modulation doping, alloy disorder and interface roughness. According to the fits, scattering from background impurities is dominant while that from alloy disorder becomes more significant at high carrier density