Segmentation Variables Research Articles

Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI-radiomic features.

The use of radiomic features as biomarkers of treatment response and outcome or as correlates to genomic variations requires that the computed features are robust and reproducible. Segmentation, a crucial step in radiomic analysis, is a major source of variability in the computed radiomic features. Therefore, we studied the impact of tumor segmentation variability on the robustness of MRI radiomic features. Fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced T1-weighted (T1WICE ) MRI of 90 patients diagnosed with glioblastoma were segmented using a semiautomatic algorithm and an interactive segmentation with two different raters. We analyzed the robustness of 108 radiomic features from five categories (intensity histogram, gray-level co-occurrence matrix, gray-level size-zone matrix (GLSZM), edge maps, and shape) using intra-class correlation coefficient (ICC) and Bland and Altman analysis. Our results show that both segmentation methods are reliable with ICC≥0.96 and standard deviation (SD) of mean differences between the two raters (SDdiffs )≤30%. Features computed from the histogram and co-occurrence matrices were found to be the most robust (ICC≥0.8 and SDdiffs ≤30% for most features in these groups). Features from GLSZM were shown to have mixed robustness. Edge, shape, and GLSZM features were the most impacted by the choice of segmentation method with the interactive method resulting in more robust features than the semiautomatic method. Finally, features computed from T1WICE and FLAIR images were found to have similar robustness when computed with the interactive segmentation method. Semiautomatic and interactive segmentation methods using two raters are both reliable. The interactive method produced more robust features than the semiautomatic method. We also found that the robustness of radiomic features varied by categories. Therefore, this study could help motivate segmentation methods and feature selection in MRI radiomic studies.

User-dependent variability in mitral valve segmentation and its impact on CFD-computed hemodynamic parameters.

While novel tools for segmentation of the mitral valve are often based on automatic image processing, they mostly require manual interaction by a proficient user. Those segmentations are essential for numerical support of mitral valve treatment using computational fluid dynamics, where the reconstructed geometry is incorporated into a simulation domain. To quantify the uncertainty and reliability of hemodynamic simulations, it is crucial to examine the influence of user-dependent variability in valve segmentation. Previously, the inter-user variability of landmarks in mitral valve segmentation was investigated. Here, the inter-user variability of geometric parameters of the mitral valve, projected orifice area (OA) and projected annulus area (AA), is investigated for 10 mitral valve geometries, each segmented by three users. Furthermore, the propagation of those variations into numerically calculated hemodynamics, i.e., the blood flow velocity, was investigated. Among the three geometric valve parameters, AA was least user-dependent. Almost all deviations to the mean were below 10%. Larger variations were observed for OA. Variations observed for the numerically calculated hemodynamics were in the same order of magnitude as those of geometric parameters. No correlation between variation of geometric parameters and variation of calculated hemodynamic parameters was found. Errors introduced due to the user-dependency were of the same size as the variations of calculated hemodynamics. The variation was thereby of the same scale as deviations in clinical measurements of blood flow velocity using Doppler echocardiography. Since no correlation between geometric and hemodynamic uncertainty was found, further investigation of the complex relationship between anatomy, leaflet shape and flow is necessary.

Segmentation of gliomas in 18F-Fluorocholine PET/CT. A multiapproach study

AimOur aim was two-fold, to study the interobserver agreement in tumour segmentation and to search for a reliable methodology to segment gliomas using 18F-Fluorocholine PET/CT. Methods25 patients with glioma, from a prospective and non-randomized study [FuMeGA (Functional and Metabolic Glioma Analysis)], were included.Interobserver variability in tumour segmentation was assessed using fixed thresholds. Different strategies were used to segment the tumours. First, a semi-automatic tumour segmentation was performed, selecting the best SUVmax-% threshold for each lesion. Next we determined a variable SUVmax-% depending on the SUVmax. Finally a segmentation using a fixed SUVmax threshold was performed. To do so, a sampling of 10 regions of interest (ROIs of 2.8cm2) located in the normal brain was performed. The upper value of the sample mean SUVmax±3 SD was used as cut-off. All procedures were tested and classified as effective or not for tumour segmentation by two observer's consensus. ResultsIn the pilot segmentation, the mean±SD of SUVmax, SUVmean and optimal SUVmax-% threshold were: 3.64±1.77, 1.32±0.57 and 21.32±8.39, respectively. Optimal SUVmax-% threshold showed a significant association with the SUVmax (Pearson=−0.653, p=0.002). However, the linear regression model for the total sample was not good, that supported the division in two homogeneous groups, defining two formulas for predicting the optimal SUVmax-% threshold. As to the third procedure, the obtained value for the mean SUVmax background+3 SD was 0.33. This value allowed segmenting correctly a significant fraction of tumours, although not all. ConclusionA great interobserver variability in the tumour segmentation was found. None of the methods was able to segment correctly all the gliomas, probably explained by the wide tumour heterogeneity on 18F-Fluorocholine PET/CT.

Reliability of Single-Slice-Based 2D CT Texture Analysis of Renal Masses: Influence of Intra- and Interobserver Manual Segmentation Variability on Radiomic Feature Reproducibility.

OBJECTIVE. The objective of our study was to investigate the potential influence of intra- and interobserver manual segmentation variability on the reliability of single-slice-based 2D CT texture analysis of renal masses. MATERIALS AND METHODS. For this retrospective study, 30 patients with clear cell renal cell carcinoma were included from a public database. For intra- and interobserver analyses, three radiologists with varying degrees of experience segmented the tumors from unenhanced CT and corticomedullary phase contrast-enhanced CT (CECT) in different sessions. Each radiologist was blind to the image slices selected by other radiologists and him- or herself in the previous session. A total of 744 texture features were extracted from original, filtered, and transformed images. The intraclass correlation coefficient was used for reliability analysis. RESULTS. In the intraobserver analysis, the rates of features with good to excellent reliability were 84.4-92.2% for unenhanced CT and 85.5-93.1% for CECT. Considering the mean rates of unenhanced CT and CECT, having high experience resulted in better reliability rates in terms of the intraobserver analysis. In the interobserver analysis, the rates were 76.7% for unenhanced CT and 84.9% for CECT. The gray-level cooccurrence matrix and first-order feature groups yielded higher good to excellent reliability rates on both unenhanced CT and CECT. Filtered and transformed images resulted in more features with good to excellent reliability than the original images did on both unenhanced CT and CECT. CONCLUSION. Single-slice-based 2D CT texture analysis of renal masses is sensitive to intra- and interobserver manual segmentation variability. Therefore, it may lead to nonreproducible results in radiomic analysis unless a reliability analysis is considered in the workflow.

Is religiosity an important consideration in Muslim consumer behavior

PurposeThis study aims to explore whether religiosity influences consumer purchase behavior among Muslim consumers in Pakistan.Design/methodology/approachAn in-depth, semi-structured interview protocol was developed and administered to a sample of 90 participants, both male and female, across eight metropolitan cities of Pakistan. Professionals, university students and housewives were part of the sample. NVivo Version 11 was used for data analysis to answer the research questions raised in this study. Moreover, the purposive sampling method has been used in this research.FindingsThe behavior of consumers was found to vary with the degree of involvement and the degree of religiosity. Study findings are divided into three themes. Firstly, a high level of religiosity makes Muslim consumers follow the Islamic principles of food consumption, by evaluating the product ingredients, spending moderately and verifying a halal logo at the time of purchase. Secondly, a major theme is the view that religiosity has no influence on food consumption; it is more about individuals’ needs and priorities. Finally, the consumers’ overall perception of quality, product value, purity and health consciousness over-powers the concept of religiosity.Research limitations/implicationsBecause of its qualitative and exploratory nature, the generalizability of this paper is limited. In addition to that, this research is just focused on one Muslim country.Practical implicationsThis study suggests that western food exporters may use religiosity and other factors as probable segmentation variables to effectively position their brands. Religious images and other factors may be highlighted in product packaging and communication campaigns by marketers to gain recognition and usage of western food and consumption among religious, Pakistani Muslim consumers. The output of this research may support prospective entrants into the food business; those interested in exploring the Asian consumer market. Findings from this study may also be helpful for those in the west interested in exploring Pakistan as an emerging consumer market.Social implicationsThe presence of western imported food may improve the quality of life by having more opportunities and healthier options for the nation. Western food products can also bring cultural convergence whereby the underdeveloped nation feels upgraded and modern. Moreover, if the western food products are certified halal, the product has a fair chance of adoption and penetration in the society. Also, the food products coming from the western world induces mindfulness, people are more aware about innovative and useful ingredients that can satisfy their taste buds, improve their health, increase their life expectancy and contented approach toward life.Originality/valueThus far, limited research has analyzed religiosity of an overwhelmingly Muslim population and its impact on consumer behavior. This study is a preliminary effort to provide a basic understanding of the behavior of Pakistani Muslims, who have been insufficiently investigated by marketing and consumer researchers. The intriguing results are to remind marketers that there are several factors that govern religiosity and lead to a purchase decision.

Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability.

The reproducibility and non-redundancy of radiomic features are challenges in accelerating the clinical translation of radiomics. In this study, we focused on the robustness and non-redundancy of radiomic features extracted from computed tomography (CT) scans in hepatocellular carcinoma (HCC) patients with respect to different tumor segmentation methods. Arterial enhanced CT images were retrospectively randomly obtained from 106 patients. As a training data set, 26 HCC patients were used to calculate the features' reproducibility and redundancy. Another data set (55 HCC patients and 25 healthy volunteers) was used for classification. The GrowCut and GraphCut semiautomatic segmentation methods were implemented in 3D Slicer software by two independent observers, and manual delineation was performed by five abdominal radiation oncologists to acquire the gross tumor volume (GTV). Seventy-one radiomic features were extracted from GTVs using Imaging Biomarker Explorer (IBEX) software, including 17 tumor intensity statistical features, 16 shape features and 38 textural features. For each radiomic feature, intraclass correlation coefficient (ICC) and hierarchical clustering were used to quantify its reproducibility and redundancy. Features with ICC values greater than 0.75 were considered reproducible. To generate the number of non-redundancy feature subgroups, the R2 statistic method was used. Then, a classification model was built using a support vector machine (SVM) algorithm with 10-fold cross validation, and area under ROC curve (AUC) was used to evaluate the utility of non-redundant feature extraction by hierarchical clustering. The percentages of excellent reproducible features in the manual delineation group, GraphCut and GrowCut segmentation group were 69% [49], 73% [52] and 79% [56], respectively. Sixty-five percent [46] of the features showed strong robustness for all segmentation methods. The optimal number of cluster subgroup were 9, 13 and 11 for manual delineation, GraphCut and GrowCut segmentation, respectively. The optimal cluster subgroup number was 6 for all groups when the collectively high reproducibility features were selected for clustering. The receiver operating characteristic (ROC) analysis of radiomics classification model with and without feature reduction for healthy liver and HCC had an AUC value of 0.857 and 0.721 respectively. Our study demonstrates that variations exist in the reproducibility of quantitative imaging features extracted from tumor regions segmented using different methods. The reproducibility and non-redundancy of the radiomic features rely greatly on the tumor segmentation in HCC CT images. We recommend that the most reliable and uniform radiomic features should be selected in the clinical use of radiomics. Classification experiments with feature reduction showed that radiomic features were effective in identifying healthy liver and HCC.

Assessment of the transit ridership prediction errors using AVL/APC data

The disparity between actual and forecasted transit ridership has been an important area of study and a concern for researchers for several decades. In order to decrease the discrepancy caused by model property errors, a number of studies focus on better representation of difficult-to-measure cost functions and incorporation of behavioral variables in mode choice models. In spite of the improvement, some gaps still remain in practical applications, particularly for large-scale regional travel forecasting models which are zone-based and aggregated. With automated data collection systems including Automatic Vehicle Location/Automatic Passenger Count (AVL/APC), modellers have great potential to use these technologies as new or complementary data sources to reliably estimate system performances and observed transit ridership. In particular, an opportunity exists to explore model prediction errors at a more disaggregate spatial scale. In this paper, using AVL/APC data, a method to effectively identify and evaluate the source of transit ridership prediction errors is proposed. Multinomial regression models developed in this research produce equations for mode choice prediction errors as a function of: measurable but omitted market segmentation variables in current mode choice utility functions; and newly quantifiable attributes with new data sources or techniques including quality of service variables. Further, the proposed composite index can systematically evaluate and prioritize the major source of prediction errors by quantifying total magnitudes of prediction error and a possible error component. The outcomes of the research can serve as foundation towards more reliable and accurate mode choice models and ultimately enhanced transit travel forecasting.

Segmentation of Coffee Consumers Using Sustainable Values: Cluster Analysis on the Polish Coffee Market

Producers and retailers are the driving force behind the adoption of the idea of sustainability. It has been found that while preparing their product range offer, many still pay attention to the same set of criteria: size of the customers’ earnings, how often they shop, and how much they buy when shopping. In general, sustainable values applied by consumers in their purchasing decisions are rarely taken into account in consumer segmentation. The aim of this study is to recognize if values such as environmental protection, producers’ ethical behavior, fair trade or maximizing the utility function of consumption are important factors in the purchasing process of coffee and if they can be used as segmentation variables. The discussed findings come from a standardized online survey conducted on a sample of 800 Polish coffee consumers in July 2018. The obtained results are discussed by employing multi-dimensional analyses, such as exploratory factor analysis (EFA) and cluster analysis (CA). In consequence, six segments of coffee consumers are identified and described: “responsible, aspiring to be connoisseurs”, “loyal coffee enthusiasts”, “pragmatic users”, “coffee laypersons”, “sophisticated connoisseurs”, and “consumerists, connoisseurs, but not at any price”. Among the identified segments, the most often indicated sustainable consumption values refer to “responsible, aspiring to be connoisseurs”, and the least often to “consumerists, connoisseurs, but not at any price”. The conclusions may be used by manufacturing and trade enterprises operating in the coffee market to respond to the identified needs and expectations of consumers.

Selecting geomorphic variables for automatic river segmentation: Trade-offs between information gained and effort required

Identifying river segments with apparently distinct geomorphic characteristics but relatively homogeneous internal features may be critically helpful in designing network analysis for characterization, environmental assessment and river management. Automatic segmentation procedures using geographic tools and statistical methods provide objective and replicable results. In particular, multivariate procedures may be appropriated for different purposes such as coping with the multiple dimensionality of river systems. Although there is an increasing number of studies dealing with segmentation using different sets of morphological variables, the influence that the selected variables have on segmentation results is rarely assessed. In this context, we defined five combinations of frequently used geomorphic variables (i.e., channel slope, active channel width, valley bottom width, channel confinement and specific stream power), and compared the obtained segmentation results. We study the upper Esla River network, covering a total length of 294 km, with the largest two rivers regulated by large dams. Variables were measured at successive river sections 200 m apart. Five segmentation results were obtained in which we compared the number and characteristics of the segments, and the internal variability and the suitability of predicting river dynamics (i.e., occurrence of bare and vegetated gravel bars). The number of segments per kilometer of river and their average length were different among segmentations but varied much more across rivers than across segmentations. In general, segmentations including channel slope and active channel width performed better in predicting the occurrence of bare gravel bars than segmentations based on stream power or valley confinement. When splitting the initial data set into regulated and non-regulated segments, differences in predicting the occurrence of gravel bars were found, with better results in the case of non-regulated rivers. Channel slope and active channel width showed a reduced explanatory power for the regulated reaches. Finally, we conclude that primary geomorphic variables such as channel slope and active channel width were more efficient than secondary variables such as stream power, which may encompass more information but needed additional data and the use of empirical models, with greater effort and much uncertainty. In the case of regulated rivers, automatic segmentation including the affected variables (e.g., active channel width) may help in detecting differences in geomorphic sensitivity to river adjustments across the resulting segments downstream from the dams. Our results offer valuable insights into the selection of geomorphic variables for river segmentation analysis, in which trade-offs between the information gained and the effort required must be considered according to the respective research targets.

Native speech plasticity in the German-English late bilingual Stefanie Graf: A longitudinal study over four decades

The purpose of this study was to expose the trajectory of native speech plasticity in the context of late bilingualism through analysis of spontaneous speech of Stefanie Graf (SG) over four decades.With regard to segmental variables, results showed a significant lowering of F2 in /l/, suggesting darkening of the German lateral under the influence of English as a second language (L2). F2 significantly increased in /i/, indicating a more front pronunciation, as predicted due to English L2 acquisition. There was also a significant decrease in F1 of /l/, as well as of /i/, but a significant increase in the F1 frequency of /a/, suggesting widening of the vertical vowel space, potentially due to increasing age. Regarding prosody, there was a significant decrease in pitch level and narrowing of pitch span over time, as expected with increasing age, and surprisingly an increase in average maximum f0 over time, possibly as a result of English L2 acquisition of prosody.These findings suggest that native speech remains plastic post adolescence throughout adulthood, here proposed to be evidenced through a result of acquisition of L2 counterparts in late bilingualism, and that such changes are intertwined with natural biological speech developments over the lifespan.

On the relationship between passion, word-of-mouth behaviour and eudaimonic wellbeing

This study proposes a dualistic model of passion, with impacts on positive word-of-mouth (WOM) behaviour and eudaimonic wellbeing. Neither passion nor eudaimonic wellbeing attracts sufficient attention in sport consumer literature, despite their promise in related fields. The parsimonious model, with its strong theoretical justification, reveals that harmonious passion (HP) and obsessive passion (OP) explain substantial variance in both outcome variables. Specifically, higher levels of OP are associated with lower levels of positive WOM, and consumers exhibiting HP tend to be strong, positive WOM ambassadors. In addition, higher levels of eudaimonic wellbeing mitigate adverse effects of OP. Considering the prominent role of passion for people's identity, it offers an attractive segmentation variable.

ST/HR variables in firefighter exercise ECG - relation to ischemic heart disease.

Exercise electrocardiography (ExECG) is regularly performed by Swedish firefighters by law. Heart rate‐corrected analysis of ST segment variables (ST/HR) has shown improved prediction of ischemic heart disease (IHD) compared to ST depression alone. This has not previously been extensively studied in asymptomatic persons with a low probability of IHD. We therefore evaluated the predictive performance of ST/HR analysis in firefighter ExECG. ExECG was studied in 521 male firefighters. During 8.4 ± 2.1 years, 2.3% (n = 12) were verified with IHD by catheterization or myocardial scintigraphy (age 51.5 ± 5.5 years) and were compared with firefighters without imaging proof of IHD (44.2 ± 10.1 years). The predictive value of ST depression, ST/HR index, ST/HR slope, and area and rotation of the ST/HR loop was calculated as age‐adjusted odds ratios (OR), in 10 ECG leads. Predictive accuracy was analyzed with receiver operating characteristics (ROC) analysis. ST/HR index ≤−1.6 μV/bpm and ST/HR slope ≤−2.4 μV/bpm were associated with increased IHD risk in three individual leads (all OR > 1.0, P < 0.05). ST/HR loop area lower than the fifth percentile of non‐IHD subjects indicated IHD risk in V4, V5, aVF, II, and –aVR (P < 0.05). ST depression ≤−0.1 mV was associated with IHD only in V4 (OR, 9.6, CI, 2.3‐40.0). ROC analysis of each of these variables yielded areas under the curve of 0.72 or lower for all variables and leads. Clockwise‐rotated ST/HR loops was associated with increased risk in most leads compared to counterclockwise rotation. The limited clinical value of ExECG in low‐risk populations was emphasized, but if performed, ST/HR analysis should probably be given more importance.

On the relationship between passion, word-of-mouth behaviour and eudaimonic wellbeing

This study proposes a dualistic model of passion, with impacts on positive word-of-mouth (WOM) behaviour and eudaimonic wellbeing. Neither passion nor eudaimonic wellbeing attracts sufficient attention in sport consumer literature, despite their promise in related fields. The parsimonious model, with its strong theoretical justification, reveals that harmonious passion (HP) and obsessive passion (OP) explain substantial variance in both outcome variables. Specifically, higher levels of OP are associated with lower levels of positive WOM, and consumers exhibiting HP tend to be strong, positive WOM ambassadors. In addition, higher levels of eudaimonic wellbeing mitigate adverse effects of OP. Considering the prominent role of passion for people's identity, it offers an attractive segmentation variable.

Myocardial segmental thickness variability on echocardiography is a highly sensitive and specific marker to distinguish ischemic and non-ischemic dilated cardiomyopathy in new onset heart failure

The aim of this study was to determine non-invasive diagnostic markers by echocardiography that differentiate ischemic dilated (ICM) from non-ischemic dilated cardiomyopathy (NICM) in patients with new onset heart failure. We identified 100 consecutive new heart failure patients with dilated cardiomyopathy (valvular etiology excluded). Clinical risk factors, medication history, serum biomarkers, ECG and echocardiographic variables were compared between the ICM and NICM groups (as confirmed by coronary angiography). Mean age, left ventricular size and ejection fraction were 56 years, 6.1 cm and 26% respectively. A total of 24% had ICM. Patients with ICM were older (65 vs. 53 years; P < 0.001). No significant difference was observed between ICM and NICM among 18 clinical variables, 7 laboratory tests, 6 EKG parameters and 10 of the 13 echocardiographic markers evaluated. Segmental wall thickness variability, regional wall motion abnormality and RV enlargement on echocardiogram (echo) differentiated ICM from NICM. Segmental thickness variability outperformed wall motion abnormality in diagnosing ICM with a sensitivity and specificity of 79.2 and 98.7% versus 62.5 and 84.2% respectively. RV enlargement was not sensitive but 90.6% specific for predicting NICM. Myocardial segmental thickness variability on echo, resulting from thinned infarcted or hibernating myocardium, is a highly sensitive and specific marker to differentiate ICM from NICM in new onset heart failure.

Evaluation of tumor coverage after MR-guided prostate focal laser ablation therapy.

Prostate cancer is the most common noncutaneous cancer among men in the USA. Focal laser thermal ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. In this study, we evaluated the location of ablation zones relative to targeted lesions in 23 patients who underwent FLA therapy in a phase II trial. The ablation zone margins and unablated tumor volume were measured to determine whether complete coverage of each tumor was achieved, which would be considered a clinically successful ablation. Preoperative mpMRI was acquired for each patient 2-3 months preceding the procedure and the prostate and lesion(s) were manually contoured on 3T T2-weighted axial images. The prostate and ablation zone(s) were also manually contoured on postablation 1.5T T1-weighted contrast-enhanced axial images acquired immediately after the procedure intraoperatively. The lesion surface was nonrigidly registered to the postablation image using an initial affine registration followed by nonrigid thin-plate spline registration of the prostate surfaces. The margins between the registered lesion and ablation zone were calculated using a uniform spherical distribution of rays, and the volume of intersection was also calculated. Each prostate was contoured five times to determine the segmentation variability and its effect on intersection of the lesion and ablation zone. Our study showed that the boundaries of the segmented tumor and ablation zone were close. Of the 23 lesions that were analyzed, 11 were completely covered by the ablation zone and 12 were partially covered. A shift of 1.0, 2.0, and 2.6mm would result in 19, 21, and all tumors completely covered by the ablation zone, respectively. The median unablated tumor volume across all tumors was 0.1 with an IQR of 3.7 , which was 0.2% of the median tumor volume (46.5 with an IQR of 46.3 ). The median extension of the tumors beyond the ablation zone, in cases which were partially ablated, was 0.9mm (IQR of 1.3mm), with the furthest tumor extending 2.6mm. In all cases, the boundary of the tumor was close to the boundary of the ablation zone, and in some cases, the boundary of the ablation zone did not completely enclose the tumor. Our results suggest that some of the ablations were not clinically successful and that there is a need for more accurate needle tracking and guidance methods. Limitations of the study include errors in the registration and segmentation methods used as well as different voxel sizes and contrast between theregistered T2 and T1 MRI sequences and asymmetric swelling of the prostate postprocedurally.

Feeling emotions in the public performing arts sector: does gender affect?

A distinct new development presented by this paper is the analysis of attendees’ heterogeneity considering gender and its influence on consumer post-use behavior. The study analyses whether gender moderates the relationship between emotions and post-use behavior in terms of satisfaction and loyalty in public services. A quantitative study was conducted to gather data from 867 Spanish opera-goers of a public opera house through e-mail with a link to a questionnaire. Hypotheses were tested using a multigroup analysis by parametric approach in a structural equation modelling. Gender was found to moderate the relationships presented in the model. Empirical results show that gender provides differences in the effect of emotions in the post-use behavior. Particularly, the effect of the negative emotions in loyalty only exists for female attendees. Moreover, it can be concluded that the positive impact of satisfaction on loyalty is stronger for men than women. Results reveal the importance of managing emotions as well as considering gender differences as segmentation variables. Examining the phenomenon of emotions in context of performing arts, while considering gender as moderator, highlights the originality and contribution of the present study to the public hedonic services.

Differences in lower-limb coordination and coordination variability between novice and experienced runners during a prolonged treadmill run at anaerobic threshold speed

ABSTRACTThis study investigated differences in lower-limb coordination and coordination variability between experienced and novice runners during a prolonged run. Thirty-four participants were categorised as either experienced (n = 17) or novice runners (n = 17). All participants performed a 31-min treadmill run at their individual anaerobic threshold speed, and lower-limb kinematic data were acquired in the sagittal plane at the beginning, middle, and end of the run. Lower-limb coordination and variability during the stance phase were quantified using a vector coding technique for hip-knee, knee-ankle, pelvis-thigh, thigh-shank, and shank-foot couplings. Repeated-measure analysis of covariance revealed that running experience and time had significant interactions on the coordination patterns for hip-knee and pelvis-thigh couplings. During the midstance, experienced runners exhibited a higher percentage of in-phase motion for pelvis-thigh and knee-ankle couplings while novice runners displayed a higher percentage of distal motion for pelvis-thigh coupling and anti-phase motion for hip-knee coupling. Experienced runners displayed more variability in hip-knee and shank-foot couplings, and novice runners had more variability in hip, knee, and thigh motion. Experienced and novice runners adapted to progressive fatigue through different lower-limb coordination patterns. Throughout the prolonged run, experienced runners demonstrated greater coordination variability and novice runners displayed greater joint and segment variability.

Segmentation of financial clients by attitudes and behavior

PurposeThe purpose of this paper is to investigate segmentations by finance-related attitudes and behavior of financial consumers in Switzerland and Vietnam.Design/methodology/approachThe authors replicated the questionnaire measuring attitudes toward financial affairs as used in the study of Fünfgeld and Wang (2009). In order to extract factors and identify profiles of financial customers, the authors applied the same techniques including factor analysis and a two-step cluster analysis (Ward and K-means) to both samples. Linear regressions were used to examine the impact of socio-demographic variables.FindingsFactor analysis reveals surprisingly similar underlying dimensions of financial attitudes and behavior for participants in both countries. The five clusters based on these dimensions exhibit strikingly similar characteristics. The authors also find that socio-demographic variables such as gender, age and education significantly vary across groups.Research limitations/implicationsThere are small differences in the composition of the revealed dimensions between the two countries, mainly a mixture of intuitive decisions and free-spending aspects. Future research may investigate more countries with comparable samples to further test the reliabilities and validities of the scales.Practical implicationsThe findings suggest that the instruments as developed by Fünfgeld and Wang (2009) can be used not only in highly developed Western markets but also in non-Western and emerging markets. Such instruments can be very useful for offering financial advice based on market segmentation in a global market.Originality/valueThe study provides empirical evidence on universal segmentation variables that reflect financial consumers’ psychological traits and attitudes toward saving and spending. Furthermore, the study stresses the need for a broad use of those variables when studying consumer decision-making in international financial markets.

Are consumers' minds or hearts guiding country of origin effects? Conditioning roles of need for cognition and need for affect

Contributing to research on consumer segmentation in the context of country-of-origin (COO) effects, the current study focuses on the need for cognition (NFC) and need for affect (NFA) as conditioning variables on the links between country image and attitude towards the country on the one hand and consumers' product-country image (PCI) assessments on the other. We conduct two studies: one in a highly developed, EU-member country (Austria, N = 203) and one in a developing CEE country (Bosnia & Herzegovina, N = 195). Our findings show that NFC and NFA have opposing influences on the aforementioned relationships in Austria. In contrast, in Bosnia & Herzegovina we find no significant interaction effects as well as a non-significant relationship between attitude towards the country and PCI. Overall, our results indicate that the utility of NFC and NFA as segmentation variables is country-specific and reveal cross-country differences in the operation of COO effects.

Segmentation of Peripheral Nerves From Magnetic Resonance Neurography: A Fully-Automatic, Deep Learning-Based Approach.

Diagnosis of peripheral neuropathies relies on neurological examinations, electrodiagnostic studies, and since recently magnetic resonance neurography (MRN). The aim of this study was to develop and evaluate a fully-automatic segmentation method of peripheral nerves of the thigh. T2-weighted sequences without fat suppression acquired on a 3 T MR scanner were retrospectively analyzed in 10 healthy volunteers and 42 patients suffering from clinically and electrophysiologically diagnosed sciatic neuropathy. A fully-convolutional neural network was developed to segment the MRN images into peripheral nerve and background tissues. The performance of the method was compared to manual inter-rater segmentation variability. The proposed method yielded Dice coefficients of 0.859 ± 0.061 and 0.719 ± 0.128, Hausdorff distances of 13.9 ± 26.6 and 12.4 ± 12.1 mm, and volumetric similarities of 0.930 ± 0.054 and 0.897 ± 0.109, for the healthy volunteer and patient cohorts, respectively. The complete segmentation process requires less than one second, which is a significant decrease to manual segmentation with an average duration of 19 ± 8 min. Considering cross-sectional area or signal intensity of the segmented nerves, focal and extended lesions might be detected. Such analyses could be used as biomarker for lesion burden, or serve as volume of interest for further quantitative MRN techniques. We demonstrated that fully-automatic segmentation of healthy and neuropathic sciatic nerves can be performed from standard MRN images with good accuracy and in a clinically feasible time.