Responses of calves to acute stress: Individual consistency and relations between behavioral and physiological measures

The present study examined the consistency over time of individual differences in behavioral and physiological responsiveness of calves to intuitively alarming test situations as well as the relationships between behavioral and physiological measures. Twenty Holstein Friesian heifer calves were individually subjected to the same series of two behavioral and two hypothalamo-pituitary-adrenocortical (HPA) axis reactivity tests at 3, 13 and 26 weeks of age. Novel environment (open field, OF) and novel object (NO) tests involved measurement of behavioral, plasma cortisol and heart rate responses. Plasma ACTH and/or cortisol response profiles were determined after administration of exogenous CRH and ACTH, respectively, in the HPA axis reactivity tests. Principal component analysis (PCA) was used to condense correlated measures within ages into principal components reflecting independent dimensions underlying the calves' reactivity. Cortisol responses to the OF and NO tests were positively associated with the latency to contact and negatively related to the time spent in contact with the NO. Individual differences in scores of a principal component summarizing this pattern of inter-correlations, as well as differences in separate measures of adrenocortical and behavioral reactivity in the OF and NO tests proved highly consistent over time. The cardiac response to confinement in a start box prior to the OF test was positively associated with the cortisol responses to the OF and NO tests at 26 weeks of age. HPA axis reactivity to ACTH or CRH was unrelated to adrenocortical and behavioral responses to novelty. These findings strongly suggest that the responsiveness of calves was mediated by stable individual characteristics. Correlated adrenocortical and behavioral responses to novelty may reflect underlying fearfulness, defining the individual's susceptibility to the elicitation of fear. Other independent characteristics mediating reactivity may include activity or coping style (related to locomotion) and underlying sociality (associated with vocalization). (c) 2005 Elsevier Inc. All rights reserved.

Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer

The main curative therapy for patients with nonsmall cell lung cancer is surgery. Despite this, the survival rate is only 50%, therefore it is important to more efficiently diagnose and predict prognosis for lung cancer patients. Raman spectroscopy is useful in the diagnosis of malignant and premalignant lesions. The aim of this study is to investigate the ability of Raman microscopy to diagnose lung cancer from surgically resected tissue sections, and predict the prognosis of these patients. Tumor tissue sections from curative resections are mapped by Raman microscopy and the spectra analzsed using multivariate techniques. Spectra from the tumor samples are also compared with their outcome data to define their prognostic significance. Using principal component analysis and random forest classification, Raman microscopy differentiates malignant from normal lung tissue. Principal component analysis of 34 tumor spectra predicts early postoperative cancer recurrence with a sensitivity of 73% and specificity of 74%. Spectral analysis reveals elevated porphyrin levels in the normal samples and more DNA in the tumor samples. Raman microscopy can be a useful technique for the diagnosis and prognosis of lung cancer patients receiving surgery, and for elucidating the biochemical properties of lung tumors. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3323088]

Statistical-based monitoring of multivariate non-Gaussian systems

The monitoring of multivariate systems that exhibit non-Gaussian behavior is addressed. Existing work advocates the use of independent component analysis (ICA) to extract the underlying non-Gaussian data structure. Since some of the source signals may be Gaussian, the use of principal component analysis (PCA) is proposed to capture the Gaussian and non-Gaussian source signals. A subsequent application of ICA then allows the extraction of non-Gaussian components from the retained principal components (PCs). A further contribution is the utilization of a support vector data description to determine a confidence limit for the non-Gaussian components. Finally, a statistical test is developed for determining how many non-Gaussian components are encapsulated within the retained PCs, and associated monitoring statistics are defined. The utility of the proposed scheme is demonstrated by a simulation example, and the analysis of recorded data from an industrial melter.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Kids’ Life and Times: using an Internet survey to measure children’s health-related quality of life

Objective
To examine the psychometric properties of an internet version of a children and young person's quality of life measure originally designed as a paper questionnaire.

Methods
Participants were 3,440 10 and 11 year old children in Northern Ireland who completed the KIDSCREEN-27 online as part of a general attitudinal survey. The questionnaire was animated using cartoon characters that are familiar to most children and the questions appeared on screen and were read aloud by actors.

Results
Exploratory principal component analysis of the online version of the questionnaire supported the existence of five components in line with the paper version. The items loaded on the components that would be expected based on previous findings with five domains - physical well-being,psychological well-being, autonomy and parents, social support and peers and school environment.Internal consistency reliability of the five domains was measured using Cronbach's alpha and the results suggested that the scale scores were reliable. The domain scores were similar to those reported in the literature for the paper version.

Conclusions
These results suggest that the factor structure and internal consistency reliability scores of the KIDSCREEN-27 embedded within an online survey are comparable to those reported in the literature for the paper version.

Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

In this paper, a novel motion-tracking scheme using scale-invariant features is proposed for automatic cell motility analysis in gray-scale microscopic videos, particularly for the live-cell tracking in low-contrast differential interference contrast (DIC) microscopy. In the proposed approach, scale-invariant feature transform (SIFT) points around live cells in the microscopic image are detected, and a structure locality preservation (SLP) scheme using Laplacian Eigenmap is proposed to track the SIFT feature points along successive frames of low-contrast DIC videos. Experiments on low-contrast DIC microscopic videos of various live-cell lines shows that in comparison with principal component analysis (PCA) based SIFT tracking, the proposed Laplacian-SIFT can significantly reduce the error rate of SIFT feature tracking. With this enhancement, further experimental results demonstrate that the proposed scheme is a robust and accurate approach to tackling the challenge of live-cell tracking in DIC microscopy.

Metabolic profile changes in the testes of mice with streptozotocin-induced type 1 diabetes mellitus

Contrary to the traditional view, recent studies suggest that diabetes mellitus has an adverse influence on male reproductive function. Our aim was to determine the effect of diabetes on the testicular environment by identifying and then assessing perturbations in small molecule metabolites. Testes were obtained from control and streptozotocin-induced diabetic C57BL/6 mice, 2, 4 and 8 weeks post-treatment. Diabetic status was confirmed by glycated haemoglobin, non-fasting blood glucose, physiological condition and body weight. A novel extraction procedure was utilized to obtain protein free, low-molecular weight, water soluble extracts which were then assessed using H-1 nuclear magnetic resonance spectroscopy. Principal component analysis of the derived profiles was used to classify any variations, and specific metabolites were identified based on their spectral pattern. Characteristic metabolite profiles were identified for control and type 1 diabetic animals with the most distinctive being from mice with the largest physical deterioration and loss of body weight. Eight streptozotocin-treated animals did not develop diabetes and displayed profiles similar to controls. Diabetic mice had decreases in creatine, choline and carnitine and increases in lactate, alanine and myo-inositol. Betaine levels were found to be increased in the majority of diabetic mice but decreased in a few animals with severe loss of body weight and physical condition. The association between perturbations in a number of small molecule metabolites known to be influential in sperm function, with diabetic status and physiological condition, adds further impetus to the proposal that diabetes influences important spermatogenic pathways and mechanisms in a subtle and previously unrecognized manner.

Application of Nonlinear PCA for Fault Detection in Polymer Extrusion Processes

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Dietary patterns and bone mineral status in young adults: the Northern Ireland Young Hearts Project

Studies of individual nutrients or foods have revealed much about dietary influences on bone. Multiple food or nutrient approaches, such as dietary pattern analysis, could offer further insight but research is limited and largely confined to older adults. We examined the relationship between dietary patterns, obtained by a posteriori and a priori methods, and bone mineral status (BMS; collective term for bone mineral content (BMC) and bone mineral density (BMD)) in young adults (20-25 years; n 489). Diet was assessed by 7 d diet history and BMD and BMC were determined at the lumbar spine and femoral neck (FN). A posteriori dietary patterns were derived using principal component analysis (PCA) and three a priori dietary quality scores were applied (dietary diversity score (DDS), nutritional risk score and Mediterranean diet score). For the PCA-derived dietary patterns, women in the top compared to the bottom fifth of the 'Nuts and Meat' pattern had greater FN BMD by 0.074 g/cm(2) (P=0.049) and FN BMC by 0.40 g (P=0.034) after adjustment for confounders. Similarly, men in the top compared to the bottom fifth of the 'Refined' pattern had lower FN BMC by 0.41 g (P-0.049). For the a priori DDS, women in the top compared to the bottom third had lower FN BMD by 0.05 g/cm(2) after adjustments (P=0.052), but no other relationships with BMS were identified. In conclusion, adherence to a 'Nuts and Meat' dietary pattern may be associated with greater BMS in young women and a 'Refined' dietary pattern may be detrimental for bone health in young men.

2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.

A posteriori-derived dietary patterns and retinal vessel caliber in an elderly population

Purpose. To examine the association between a posteriori–derived dietary patterns (DP) and retinal vessel caliber in an elderly population.

Methods. This was a cross-sectional study of 288 elderly adults (>65 years) who participated in the European Eye study (EUREYE) Northern Irish cohort. DP were extracted using principal component analysis from completed food frequency questionnaires. Semi-automated computer grading was used to determine the mean retinal vessel diameters (central retinal arteriole equivalent [CRAE] and central retinal venule equivalent [CRVE]) from digitized visual field one images using a standard measurement protocol.

Results. Three major DP were identified in this population, which accounted for 21% of the total variance: a “healthy” pattern with high factor loadings for oily fish, fruits and vegetables, and olive oil; an “unhealthy” pattern with high factor loadings for red and processed meat, refined grains, eggs, butter, sugar and sweets; and a “snack and beverage” pattern with high factor loading for pizza, nuts, and coffee. Multivariable linear regression analysis indicated no significant association between major identified DP and mean CRAE or CRVE in all models.

Conclusions. This is the first study to investigate associations between a posteriori–derived DP and retinal vessel caliber. There was no evidence of a relationship between extracted DP and retinal vessel measurements in this population. However, it is possible that potentially important relationships exist between single nutrients or foods and vessel diameters that cannot be identified using a DP approach. Further studies to examine the role of dietary factors in the microcirculation are required.

Evaluation of quality of life and priorities of patients with glaucoma

PURPOSE: To investigate the quality of life and priorities of patients with glaucoma.

METHODS: Patients diagnosed with glaucoma and no other ocular comorbidity were consecutively recruited. Clinical information was collected. Participants were asked to complete three questionnaires: EuroQuol (EQ-5D), time tradeoff (TTO), and choice-based conjoint analysis. The latter used five-attribute outcomes: (1) reading and seeing detail, (2) peripheral vision, (3) darkness and glare, (4) household chores, and (5) outdoor mobility. Visual field loss was estimated by using binocular integrated visual fields (IVFs).

RESULTS: Of 84 patients invited to participate, 72 were enrolled in the study. The conjoint utilities showed that the two main priorities were "reading and seeing detail" and "outdoor mobility." This rank order was stable across all segmentations of the data by demographic or visual state. However, the relative emphasis of these priorities changed with increasing visual field loss, with concerns for central vision increasing, whereas those for outdoor mobility decreased. Two subgroups of patients with differing priorities on the two main attributes were identified. Only 17% of patients (those with poorer visual acuity) were prepared to consider TTO. A principal component analysis revealed relatively independent components (i.e., low correlations) between the three different methodologies for assessing quality of life.

CONCLUSIONS: Assessments of quality of life using different methodologies have been shown to produce different outcomes with low intercorrelations between them. Only a minority of patients were prepared to trade time for a return to normal vision. Conjoint analysis showed two subgroups with different priorities. Severity of glaucoma influenced the relative importance of priorities.

Fault Diagnostics for Internal Combustion Engines – Current and Future Techniques

The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

Behavioural and physiological responses of heifer calves to acute stressors: long-term consistency and relationship with adult reactivity to milking

The present study investigated the long-term consistency of individual differences in dairy cattles’ responses in tests of behavioural and hypothalamo–pituitary–adrenocortical (HPA) axis reactivity, as well as the relationship between responsiveness in behavioural tests and the reaction to first milking. Two cohorts of heifer calves, Cohorts 1 (N = 25) and 2 (N = 16), respectively, were examined longitudinally from the rearing period until adulthood. Cohort 1 heifers were subjected to open field (OF), novel object (NO), restraint, and response to a human tests at 7 months of age, and were again observed in an OF test during first pregnancy between 22 and 24 months of age. Subsequently, inhibition of milk ejection and stepping and kicking behaviours were recorded in Cohort 1 heifers during their first machine milking. Cohort 2 heifers were individually subjected to OF and NO tests as well as two HPA axis reactivity tests (determining ACTH and/or cortisol response profiles after administration of exogenous CRH and ACTH, respectively) at 6 months of age and during first lactation at approximately 29 months of age. Principal component analysis (PCA) was used to condense correlated response measures (to behavioural tests and to milking) within ages into independent dimensions underlying heifers’ reactivity. Heifers demonstrated consistent individual differences in locomotion and vocalisation during an OF test from rearing to first pregnancy (Cohort 1) or first lactation (Cohort 2). Individual differences in struggling in a restraint test at 7 months of age reliably predicted those in OF locomotion during first pregnancy in Cohort 1 heifers. Cohort 2 animals with high cortisol responses to OF and NO tests and high avoidance of the novel object at 6 months of age also exhibited enhanced cortisol responses to OF and NO tests at 29 months of age. Measures of HPA axis reactivity, locomotion, vocalisation and adrenocortical and behavioural responses to novelty were largely uncorrelated, supporting the idea that stress responsiveness in dairy cows is mediated by multiple independent underlying traits. Inhibition of milk ejection and stepping and kicking behaviours during first machine milking were not related to earlier struggling during restraint, locomotor responses to OF and NO tests, or the behavioural interaction with a novel object. Heifers with high rates of OF and NO vocalisation and short latencies to first contact with the human at 7 months of age exhibited better milk ejection during first machine milking. This suggests that low underlying sociality might be implicated in the inhibition of milk ejection at the beginning of lactation in heifers.