Contribution of individual, workplace, psychosocial and physiological factors to neck pain in female office workers

This study investigated the relative contribution of individual, workplace, psychosocial and physiological features associated with neck pain in female office workers towards developing appropriate intervention programs. Workers without disability (Neck Disability Index (NDI) score≤8, n=33); workers with neck pain and disability (NDI≥9/100, n=52) and 22 controls (women who did not work and without neck pain) participated in this study. Two logistic regression models were constructed to test the association between various measures in (1) workers with and without disability, and (2) workers without disability and controls. Measures included those found to be significantly associated with higher NDI in our previous studies: psychosocial domains; individual factors; task demands; quantitative sensory measures and measures of motor function. In the final model, higher score on negative affectivity scale (OR=4.47), greater activity in the neck flexors during cranio-cervical flexion (OR=1.44), cold hyperalgesia (OR=1.27) and longer duration of symptoms (OR=1.19) remained significantly associated with neck pain in workers. Workers without disability and controls could only be differentiated by greater muscle activity in the cervical flexors and extensors during a typing task. No psychosocial domains remained in either regression model. These results suggest that impairments in the sensory and motor system should be considered in any assessment of the office worker with neck pain and may have stronger influences on the presenting symptoms than workplace and psychosocial features.

The stress-buffering effects of control on task satisfaction and perceived goal attainment : an experimental study of the moderating influence of desire for control

The purpose of the present study was to examine the extent to which Desire for Control (DFC) interacts with experimental manipulations of demand and control, and the consequences of these interactions on task satisfaction and perceived goal attainment (i.e. task performance and task mastery). It was expected that the proposed stress-buffering effects of control would be evident only for individuals high in DFC. Moreover, it was anticipated that control may have a stress-exacerbating effect for those low in DFC. These hypotheses were tested on a sample of 137 first year psychology students who participated in an in-basket activity under low and high conditions of demand and control. Results revealed that the proposed stress-buffering effect of control was found only for those high in DFC and a stress-exacerbating effect of increased control was evident for those low in DFC on task performance and task mastery perceptions. Future research directions and the implications of these findings to applied settings are discussed.

Task-relationship-self : a framework for understanding service encounter behaviors

Research conducted over past decades has investigated selected service encounter behaviors from either a customer or service provider perspective. However, a comprehensive, dual-perspective framework is lacking. Such a framework is needed to organize knowledge of these behaviors, and thereby provide structure, clarity, and parsimony to the field. This paper describes a three-tier framework of service encounter behavior that was developed by applying grounded theory principles to interviews with customers, service employees, and other stakeholders. These informants described many ways in which they behave when executing service exchanges, dealing with service difficulties, and managing themselves in the process. Using an iterative inductive approach, a conceptual framework was developed in which specific (Tier 1) behaviors were placed within broader (Tier 2) categories, and these lower classification levels were, in turn, interpreted within a conceptual space defined by the (Tier 3) dimensions of task, relationship, and self. This framework was then elaborated and refined by reference to the psychology and marketing literature, a set of 157 audio-recorded service interactions, and an expert panel study. The paper includes comparisons between the framework and those previously proposed, propositions regarding service encounter processes and outcomes, and implications for future research and practice.

General self-efficacy influences affective task reactions during a work simulation : the temporal effects of changes in workload at different levels of control

This study investigated the effects of workload, control, and general self-efficacy on affective task reactions (i.e., demands-ability fit, active coping, and anxiety) during a work simulation. The main goals were: (1) to determine the extent general self-efficacy moderates the effects of demand and control on affective task reactions, and; (2) to determine if this varies as a function of changes in workload. Participants (N=141) completed an inbox activity under conditions of low or high control and within low and high workload conditions. The order of trials varied so that workload increased or decreased. Results revealed individuals with high general self-efficacy reported better demands-abilities fit and active coping as well as less anxiety. Three interactive effects were found. First, it was found that high control increased demands-abilities fit from trial 1 to trial 2, but only when workload decreased. Second, it was found that low efficacious individuals active coping increased in trial 2, but only under high control. Third, it was found that high control helped high efficacious individuals manage anxiety when workload decreased. However, for individuals with low general self-efficacy, neither high nor low control alleviated anxiety (i.e., whether workload increased or decreased over time).

Quantitative stem-loop RT-PCR for detection of microRNAs

Plant microRNAs (miRNAs) are a class of endogenous small RNAs that are essential for plant development and survival. They arise from larger precursor RNAs with a characteristic hairpin structure and regulate gene activity by targeting mRNA transcripts for cleavage or translational repression. Efficient and reliable detection and quantification of miRNA expression has become an essential step in understanding their specific roles. The expression levels of miRNAs can vary dramatically between samples and they often escape detection by conventional technologies such as cloning, northern hybridization and microarray analysis. The stem-loop RT-PCR method described here is designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. First, a miRNA-specific stem-loop RT primer is hybridized to the miRNA and then reverse transcribed. Next, the RT product is amplified and monitored in real time using a miRNA-specific forward primer and the universal reverse primer. This method enables miRNA expression profiling from as little as 10 pg of total RNA and is suitable for high-throughput miRNA expression analysis.

Object tracking via non-Euclidean geometry : a Grassmann approach

A robust visual tracking system requires an object appearance model that is able to handle occlusion, pose, and illumination variations in the video stream. This can be difficult to accomplish when the model is trained using only a single image. In this paper, we first propose a tracking approach based on affine subspaces (constructed from several images) which are able to accommodate the abovementioned variations. We use affine subspaces not only to represent the object, but also the candidate areas that the object may occupy. We furthermore propose a novel approach to measure affine subspace-to-subspace distance via the use of non-Euclidean geometry of Grassmann manifolds. The tracking problem is then considered as an inference task in a Markov Chain Monte Carlo framework via particle filtering. Quantitative evaluation on challenging video sequences indicates that the proposed approach obtains considerably better performance than several recent state-of-the-art methods such as Tracking-Learning-Detection and MILtrack.

Human breast cancer cell metastasis to long bone and soft organs of nude mice : a quantitative assay

Bone is a common metastatic site in human breast cancer (HBC). Since bone metastasis occurs very rarely from current spontaneous or experimental metastasis models of HBC cells in nude mice, an arterial seeding model involving the direct injection of the cells into the left ventricle has been developed to better understand the mechanisms involved in this process. We present here a sensitive polymerase chain reaction (PCR) method to detect and quantitate bone and soft organ metastasis in nude mice which have been intracardially inoculated with Lac Z transduced HBC cells. Amplification of genomically incorporated Lac Z sequences in MDA-MB-231-BAG HBC cells enables us to specifically detect these cells in mouse organs and bones. We have also created a competitive template to use as an internal standard in the PCR reactions, allowing us to better quantitate levels of HBC metastasis. The results of this PCR detection method correlate well with cell culture detection from alternate long bones from the same mice, and are more sensitive than gross Lac Z staining with X-gal or routine histology. Comparable qualitative results were obtained with PCR and culture in a titration experiment in which mice were inoculated with increasing numbers of cells, but PCR is more quantifiable, less time consuming, and less expensive. This assay can be employed to study the molecular and cellular aspects of bone metastasis, and could easily be used in conjunction with RT-PCR-based analyses of gene products which may be involved with HBC metastasis.

Using the Gini coefficient with BIOLOG substrate utilisation data to provide an alternative quantitative measure for comparing bacterial soil communities

A measure quantifying unequal use of carbon sources, the Gini coefficient (G), has been developed to allow comparisons of the observed functional diversity of bacterial soil communities. This approach was applied to the analysis of substrate utilisation data obtained from using BIOLOG microtiter plates in a study which compared decomposition processes in two contrasting plant substrates in two different soils. The relevance of applying the Gini coefficient as a measure of observed functional diversity, for soil bacterial communities is evaluated against the Shannon index (H) and average well colour development (AWCD), a measure of the total microbial activity. Correlation analysis and analysis of variance of the experimental data show that the Gini coefficient, the Shannon index and AWCD provided similar information when used in isolation. However, analyses based on the Gini coefficient and the Shannon index, when total activity on the microtiter plates was maintained constant (i.e. AWCD as a covariate), indicate that additional information about the distribution of carbon sources being utilised can be obtained. We demonstrate that the Lorenz curve and its measure of inequality, the Gini coefficient, provides not only comparable information to AWCD and the Shannon index but when used together with AWCD encompasses measures of total microbial activity and absorbance inequality across all the carbon sources. This information is especially relevant for comparing the observed functional diversity of soil microbial communities.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

An investigation of goethite-seeded Al(OH)3 precipitation using in situ X-ray diffraction and Rietveld-based quantitative phase analysis

An in situ X-ray diffraction investigation of goethite-seeded Al(OH)3 precipitation from synthetic Bayer liquor at 343 K has been performed. The presence of iron oxides and oxyhydroxides in the Bayer process has implications for alumina reversion, which causes significant process losses through unwanted gibbsite precipitation, and is also relevant for the nucleation and growth of scale on mild steel process equipment. The gibbsite, bayerite and nordstrandite polymorphs of Al(OH)3 precipitated from the liquor; gibbsite appeared to precipitate first, with subsequent formation of bayerite and nordstrandite. A Rietveld-based approach to quantitative phase analysis was implemented for the determination of absolute phase abundances as a function of time, from which kinetic information for the formation of the Al(OH)3 phases was determined.

Workflow patterns as a means to model task succession in games – a preliminary case study

Over about the last decade, people involved in game development have noted the need for more formal models and tools to support the design phase of games. It is argued that the present lack of such formal tools is currently hindering knowledge transfer among designers. Formal visual languages, on the other hand, can help to more effectively express, abstract and communicate game design concepts. Moreover, formal tools can assist in the prototyping phase, allowing designers to reason about and simulate game mechanics on an abstract level. In this paper we present an initial investigation into whether workflow patterns – which have already proven to be effective for modeling business processes – are a suitable way to model task succession in games. Our preliminary results suggest that workflow patterns show promise in this regard but some limitations, especially in regard to time constraints, currently restrict their potential.

Quantitative analysis of survivin in colorectal adenocarcinoma : increased expression and correlation with telomerase activity

The aims of the present study are to quantitatively analyze survivin expression, its clinicopathologic roles, and correlation with telomerase activity in a large cohort of patients with colorectal adenocarcinoma. Real-time polymerase chain reaction was used to quantitate expression level of survivin messenger RNA and human telomerase reverse transcriptase messenger RNA (telomerase activity) in 51 patients with colorectal adenocarcinomas. The findings were correlated with the clinicopathologic features of patients, which were prospectively collected into a computerized database. Survivin messenger RNA was expressed in all tumor samples. The level of expression in tumor tissues was increased in comparison with matched nontumor mucosa in the same patient (P = .01). The level of expression of survivin was significantly correlated with the level of human telomerase reverse transcriptase expression (P = .008) and size of the colorectal adenocarcinomas (P = .004). Survival of the patients with colorectal adenocarcinoma was associated with the TNM stages (P = .001) and not with the level of expression of survivin. Thus, survivin activity was altered in colorectal adenocarcinoma. The high prevalence of survivin expression and correlation with telomerase activity are important factors for consideration in gene targeting therapy for colorectal adenocarcinoma.

Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task

This paper presents our system to address the CogALex-IV 2014 shared task of identifying a single word most semantically related to a group of 5 words (queries). Our system uses an implementation of a neural language model and identifies the answer word by finding the most semantically similar word representation to the sum of the query representations. It is a fully unsupervised system which learns on around 20% of the UkWaC corpus. It correctly identifies 85 exact correct targets out of 2,000 queries, 285 approximate targets in lists of 5 suggestions.

Understanding the quantitative skill base on introductory statistics : a case study from business statistics

Basic mathematical skills are critical to a student’s ability to successfully undertake an introductory statistics course. Yet in business education this vitally important area of mathematics and statistics education is under-researched. The question therefore arises as to what level of mathematical skill a typical business studies student will possess as they enter the tertiary environment, and whether there are any common deficiencies that we can identify with a view to tackling the problem. This paper will focus on a study designed to measure the level of mathematical ability of first year business students. The results provide timely insight into a growing problem faced by many tertiary educators in this field.