Identifying major contributing sources to odour annoyance using a non-specific gas sensor array

Identification of major contributors to odour annoyance in areas with multiple emission sources is necessary to address and resolve odour disputes. In an effort to develop an appropriate tool for this task, odour samples were collected on-site at a piggery and an abattoir (the major odour sources in the area) and at surrounding off-site areas, then analysed using a commercial non-specific chemical sensor array to develop an odour fingerprint database. The developed odour fingerprint database was analysed using two pattern recognition algorithms including a partial least squares-discriminant analysis (PLS-DA) and a Kohonen self-organising map (KSOM). The KSOM model could identify odour samples sourced from the piggery shed 15, piggery pond 8, piggery pond 9, abattoir, motel and others with mean percentage values of 77.5, 65.0, 90.2, 75.7, 44.8 and 64.6%, respectively.

Deviant near-infrared spectra identifies Corymbia hybrids

The study examined the potential of Near Infrared Reflectance (NIR) spectroscopy for field diagnosis of hybrids between Corymbia (formerly Eucalyptus) species. NIR profiles were generated by scanning foliage from a total of 383 hybrid and 533 parental seedlings grown in a common garden and partial least squares discriminant analysis was used to test three-way model power to assign individuals to their appropriate taxon; either a parental or F1 hybrid class. Using the optimised conditions, fresh foliage from eight-month-old seedlings and a handheld NIR instrument (950–1800 nm), the mean assignment rates for the three hybrid groups ranged from 76% to 90%. Hybrid-parent contrast of NIR spectra deviated more so than parent–parent contrast. The F1 taxon assignment rates were usually higher than those for parents at 100% and 72%, respectively. Hybrid resolution was even greater for 2nd generation backcross hybrids. Similar to studies of morphology, taxon assignments tended to be more accurate for hybrid groups in which the parental taxa were more divergent. The practical application of this technique for hybrid diagnosis of seedlings in the nursery will require careful attention to control environmental factors because seedling age and storage effects influenced the ability of NIR to identify hybrids. The technique may also necessitate the generation of comparable reference populations, although exclusions approaches to analysis may circumvent the need for reference populations. The application of NIR in field diagnosis will be further complicated by the need to generate global models across environments but such models have been obtained for reliable prediction of chemistries in other situations.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

Större frihet - bättre lokalt anpassad service? : Förvaltningsreformer och kommunernas service för utvecklingsstörda 1994-2000

In the beginning of the 1990s the legislation regarding the municipalities and the system of central government transfers were reformed in Finland. This resulted in a move from detailed governmental control to increased municipal autonomy. The purpose of this decentralization was to enable the municipalities to better adapt their administration and service supply to local needs. The aim of this study was to explore the effects of the increased municipal autonomy on the organization of services for people with intellectual disabilities. Did the increased autonomy cause the municipalities to alter their service supply and production and did the services become more adapted to local needs? The data consists of statistical information on service use and production, and also of background data such as demographics, economics and political elections on 452 municipalities in Finland from the years 1994 and 2000. The methods used are cluster analysis, discriminant analysis and factor analysis. The municipalities could be grouped in two categories: those which offered mainly one kind of residential services and others which had more varied mixes of services. The use of institutional care had decreased and municipalities which used institutional care as their primary form of service were mostly very small municipalities in 2000. The situation had changed from 1994, when institutional care was the primary service for municipalities of all sizes. Also the service production had become more differentiated and the municipalities had started using more varied ways of production. More municipalities had started producing their own services and private production had increased as well. Furthermore, the increase in local autonomy had opened up possibilities for local politics to influence both the service selection and methods of production. The most significant motive for changes in the service structure was high unemployment and an increasing share of elderly people in the population, particularly in sparsely populated areas. Municipalities with a low level of resources had made more changes in their service organization while those with more resources had been able to carry on as before. Key words: service structure, service for people with intellectual disabilities, municipalities, contingency theory, New Public Management

How many inpatients in our hospitals have foot complications? The foot disease in inpatients study

Background Foot complications have been found to affect large proportions of hospital in patients with diabetes. However, no studies have investigated the proportion of foot complications affecting all people in general inpatient populations. The aims of this cross-sectional study were to investigate the point-prevalence of different foot complications in general inpatient populations, analyse differences in diabetes and non-diabetes sub-groups, and examine characteristics of people primarily admitted for a foot complication. Methods Eligible participants were all adults admitted overnight, for any reason, into five diverse hospitals on one day; excluding maternity, mental health and cognitively impaired patients. All participants underwent a physical foot examination, by trained podiatrists using validated measures, to clinically diagnose different foot complications; including foot wounds, infections, deformity, peripheral arterial disease (PAD) and peripheral neuropathy (PN). Data were also collected on participants' primary reason for admission and a range of demographic, social determinant, medical history, foot complication history, self-care and footwear risk factors. Results Overall, 733 participants consented (83% of eligible participants); mean(±SD) age 62(±19) years, 480 (55.8%) male and 172 (23.5%) had diabetes. Foot complication prevalence included: wounds 9.0% (95% CI) (5.1-8.7), infections 3.3% (2.2-4.9), deformity 22.4% (19.5-26.7), PAD 21.0% (18.2-24.1) and PN 22.0% (19.1-25.1). Diabetes populations had significantly more foot complications than non-diabetes (p < 0.01); wounds (15.7% vs 7.0%), infections (7.1% vs 2.2%), deformity (30.5% vs 19.9%), PAD (35.1% vs 16.7%) and PN (43.3% vs 15.4%). Foot complications were the primary reason for admission in 7.4% (95% CI) (5.7-9.5) of all participants. In a backwards stepwise multivariate analysis having a foot complication as the primary reason for admission was independently associated (OR (95% CI) with foot wounds (18.9 (7.3-48.7)), foot infections (6.0 (1.6-22.4)), history of amputation (4.7 (1.3-17.0) and PAD (2.9 (1.3-6.6)). Conclusions Findings of this study indicate one in every ten hospital inpatients had an active foot wound or infection. In patients with diabetes had significantly higher proportions of foot complications than non-diabetes inpatients. Remarkably one in every thirteen inpatients in this study were primarily hospitalised for a foot complication. Further research and policy is required to tackle this seemingly large inpatient foot complication burden.

Mobility impairment and bad feet … who'd of guessed? The Foot Disease in Inpatients Study (FDIS)

Background Foot complications have been found to be predictors of mobility impairment and falls in community dwelling elderly patients. However, fewer studies have investigated the link between foot complications and mobility impairment in hospital in patient populations. The aim of this paper was to investigate the associations between mobility impairment and various foot complications in general inpatient populations. Methods Eligible participants were all adults admitted overnight, for any reason, into five diverse hospitals on one day; excluding maternity, mental health and cognitively impaired patients. Participants underwent a foot examination to clinically diagnose different foot complications; including foot wounds, infections, deformity, peripheral arterial disease and peripheral neuropathy. They were also surveyed on social determinant, medical history, self-care, footwear, foot complication history risk factors, and, mobility impairment defined as requiring a mobility aid for mobilisation prior to hospitalisation. Results Overall, 733 participants consented; mean(±SD) age 62(±19) years, 408 (55.8%) male, 172 (23.5%) diabetes. Mobility impairment was present in 242 (33.2%) participants; diabetes populations reported more mobility impairment than non-diabetes populations (40.7% vs 30.9%, p < 0.05). In a backwards stepwise multivariate analysis, and controlling for other risk factors, those people with mobility impairment were independently associated with increasing years of age (OR = 1.04 (95% CI) (1.02-1.05)), male gender (OR = 1.7 (1.2-2.5)), being born in Australia (OR = 1.7 (1.1-2.8), vision impairment (2.0 (1.2-3.1)), peripheral neuropathy (OR = 3.1 (2.0-4.6) and foot deformity (OR = 2.0 (1.3-3.0). Conclusions These findings support the results of other large studies investigating community dwelling elderly patients that peripheral neuropathy and foot deformity are independently associated with mobility impairment and potentially falls. Furthermore the findings suggest routine clinical diagnosis of foot complications as defined by national diabetic foot guidelines were sufficient to determine these associated foot complication risk factors for mobility impairment. Further research is required to establish if these foot complication risk factors for mobility impairment are predictors of actual falls in the inpatient environment.

Observation of single top quark production and measurement of |Vtb| with CDF

We report the observation of electroweak single top quark production in 3.2  fb-1 of pp̅ collision data collected by the Collider Detector at Fermilab at √s=1.96  TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3-0.5+0.6(stat+sys)  pb, extract the value of the Cabibbo-Kobayashi-Maskawa matrix element |Vtb|=0.91-0.11+0.11(stat+sys)±0.07  (theory), and set a lower limit |Vtb|>0.71 at the 95% C.L., assuming mt=175  GeV/c2.

Observation of single top quark production and measurement of |Vtb| with CDF

We report the observation of electroweak single top quark production in 3.2 fb-1 of ppbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3+0.6-0.5(stat+sys) pb, extract the CKM matrix element value |Vtb|=0.91+0.11-0.11 (stat+sys)+-0.07(theory), and set a lower limit |Vtb|>0.71 at the 95% confidence level, assuming m_t=175 GeVc^2.

Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

Kiinnostusta vai ahdistusta? : Opettajaksi opiskelevien akateemiset tunteet, motivaatio ja opiskelun ongelmat suhteessa hyvinvointiin ja menestykseen aktivoivalla luentokurssilla

Previous studies indicate that positive learning experiences are related to academic achievement as well as to well-being. On the other hand, emotional and motivational problems in studying may pose a risk for both academic achievement and well-being. Thus, emotions and motivation have an increasing role in explaining university students learning and studying. The relations between emotions, motivation, study success and well-being have been less frequently studied. The aim of this study was to investigate what kind of academic emotions, motivational factors and problems in studying students experienced five days before an exam of an activating lecture course, and the relations among these factors as well as their relation to self-study time and study success. Furthermore, the effect of all these factors on well-being, flow experience and academic achievement was examined. The term academic emotion was defined as emotion experienced in academic settings and related to studying. In the present study the theoretical background to motivational factors was based on thinking strategies and attributions, flow experience and task value. Problems in studying were measured in terms of exhaustion, anxiety, stress, lack of interest, lack of self-regulation and procrastination. The data were collected in December 2009 in an activating educational psychology lecture course by using a questionnaire. The participants (n=107) were class and kindergarten teacher students from the University of Helsinki. Most of them were first year students. The course grades were also gathered. Correlations and stepwise regression analysis were carried out to find out the factors that were related to or explained study success. The clusters that presented students´ problems in studying as well as thinking strategies and attributions, were found through hierarchical cluster analysis. K-means cluster analysis was used to form the final groups. One-way analysis of variance, Kruskal-Wallis test and crosstabs were conducted to see whether the students in different clusters varied in terms of study success, academic emotions, task value, flow, and background variables. The results indicated that academic emotions measured five days before the exam explained about 30 % of the variance of the course grade; exhaustion and interest positively, and anxiety negatively. In addition, interest as well as the self-study time best explained study success on the course. The participants were classified into three clusters according to their problems in studying as well as their thinking strategies and attributions: 1) ill-being, 2) carefree, and 3) committed and optimistic students. Ill-being students reported most negative emotions, achieved the worst grades, experienced anxiety rather than flow and were also the youngest. Carefree students, on the other hand, expressed the least negative emotions and spent the least time on self-studying, and like committed students, experienced flow. In addition, committed students reported positive emotions the most often and achieved the best grades on the course. In the future, more in-depth understanding how and why especially young first year students experience their studying hard is needed, because early state of the studies is shown to predict later study success.

Chemical communication in Ropalidia marginata: Dufour's gland contains queen signal that is perceived across colonies and does not contain colony signal

Queens of the primitively eusocial wasp Ropalidia marginata appear to maintain reproductive monopoly through pheromone rather than through physical aggression. Upon queen removal, one of the workers (potential queen, PQ) becomes extremely aggressive but drops her aggression immediately upon returning the queen. If the queen is not returned, the PQ gradually drops her aggression and becomes the next queen of the colony. In a previous study, the Dufour's gland was found to be at least one source of the queen pheromone. Queen-worker classification could be done with 100% accuracy in a discriminant analysis, using the compositions of their respective Dufour's glands. In a bioassay, the PQ dropped her aggression in response to the queen's Dufour's gland macerate, suggesting that the queen's Dufour's gland contents mimicked the queen herself. In the present study, we found that the PQ also dropped her aggression in response to the macerate of a foreign queen's Dufour's gland. This suggests that the queen signal is perceived across colonies. This also suggests that the Dufour's gland in R. marginata does not contain information about nestmateship, because queens are attacked when introduced into foreign colonies, and hence PQ is not expected to reduce her aggression in response to a foreign queen's signal. The latter conclusion is especially significant because the Dufour's gland chemicals are adequate to classify individuals correctly not only on the basis of fertility status (queen versus worker) but also according to their colony membership, using discriminant analysis. This leads to the additional conclusion (and precaution) that the ability to statistically discriminate organisms using their chemical profiles does not necessarily imply that the organisms themselves can make such discrimination. (C) 2010 Elsevier Ltd. All rights reserved.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Classification of Myopathies on Molecular basis in Drosophila using Raman spectroscopy

Myopathies are muscular diseases in which muscle fibers degenerate due to many factors such as nutrient deficiency, infection and mutations in myofibrillar etc. The objective of this study is to identify the bio-markers to distinguish various muscle mutants in Drosophila (fruit fly) using Raman Spectroscopy. Principal Components based Linear Discriminant Analysis (PC-LDA) classification model yielding >95% accuracy was developed to classify such different mutants representing various myopathies according to their physiopathology.

Classification of Myopathies on Molecular basis in Drosophila using Raman spectroscopy

Myopathies are muscular diseases in which muscle fibers degenerate due to many factors such as nutrient deficiency, infection and mutations in myofibrillar etc. The objective of this study is to identify the bio-markers to distinguish various muscle mutants in Drosophila (fruit fly) using Raman Spectroscopy. Principal Components based Linear Discriminant Analysis (PC-LDA) classification model yielding >95% accuracy was developed to classify such different mutants representing various myopathies according to their physiopathology.