Effects of intrinsic and extrinsic motivation on user-generated content

User-generated content where content is created and shared among consumers is of key importance to marketers. This study investigates consumer intrinsic and extrinsic motivation to understand why people create user-generated branded video content. Specifically, we examine the role of altruism (individual difference – intrinsic motivation), social benefits (extrinsic reward), and economic incentives (extrinsic reward) on intentions to create user-generated content. Results show that extrinsic rewards (economic incentives) result in more positive intentions to create user-generated content than intrinsic motivations. However, an effect for altruism is also evident revealing that high altruism consumers are more likely to create positive user-generated content. The implication of these findings is that marketers wanting to encourage user-generated content about their brands should target high altruism consumers and offer economic incentives for content creation.

Modeling conditional correlations of asset returns : a smooth transition approach

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

Self-reflection as an intervention to influence achievement goal orientations and intrinsic motivation

In the context of physical activity, intrinsic motivation refers to the inherent satisfaction associated with participation in the activity. Interest-enjoyment, perceived competence, and effort have been identified as three underlying components of intrinsic motivation. Achievement goal theory stipulates that achievement goals guide our beliefs and behavior. The two main achievement goal orientations identified in the sport and physical activity literature are task and ego orientations. A person with a strong task orientation defines success in self-referenced terms, as improving one’s own performance or mastering new skills. Someone with a strong ego orientation defines success normatively, as being better than others. The majority of research suggests that having a strong task orientation is a good thing, whether with regard to motivationally adaptive responses, sources of sport confidence, students’ satisfaction with learning, or the use of cognitive and self-regulatory strategies. Although the literature supporting the potential benefits of having a strong task orientation is vast, considerably less research has tested interventions designed to strengthen task orientations and intrinsic motivation. A climate that emphasises individual mastery has resulted in increased interest-enjoyment and perceived competence, whereas an emphasis on competition and comparison with others has resulted in a decrease in interest-enjoyment and an increase in tension-pressure. One possible intervention is the use of structured self-reflection. Using self-reflection sheets that cause respondents to focus on specific elements of technique or skills, and rate one’s own performance, should theoretically promote a task focus. Hanrahan suggested that engaging in self-reflection may enhance intrinsic motivation. Perceived competence could be positively affected, as self-analysis and self-monitoring have been found to positively influence the acquisition of physical skills. The purpose of this study was to determine if the use of structured self-reflection in community dance classes would influence achievement goal orientations or levels of intrinsic motivation.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

Biophysical correlates of intrinsic and stress-induced morphological variability in lateral amygdaloid neurons: A computational study

Morphological and physiological characteristics of neurons located in the dorsolateral and two ventral subdivisions of the lateral amygdala (LA) have been compared in order to differentiate their roles in the formation and storage of fear memories (Alphs et al, SfN abs 623.1, 2003). Briefly, in these populations, significant differences are observed in input resistance, membrane time constant, firing frequency, dendritic tortuosity, numbers of primary dendrites, dendritic segments and dendritic nodes...

Differences in intrinsic properties of dorsally and ventrally located lateral amygdala neurons of the rat

During Pavlovian auditory fear conditioning a previously neutral auditory stimulus (CS) gains emotional significance through pairing with a noxious unconditioned stimulus (US). These associations are believed to be formed by way of plasticity at auditory input synapses on principal neurons of the lateral nucleus of the amygdala (LA). While the LA has been implicated as a key brain structure for fear learning, how its network of cellular components performs these operations is not yet known...

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

Direct mapping of hippocampal surfaces with intrinsic shape context

We propose in this paper a new method for the mapping of hippocampal (HC) surfaces to establish correspondences between points on HC surfaces and enable localized HC shape analysis. A novel geometric feature, the intrinsic shape context, is defined to capture the global characteristics of the HC shapes. Based on this intrinsic feature, an automatic algorithm is developed to detect a set of landmark curves that are stable across population. The direct map between a source and target HC surface is then solved as the minimizer of a harmonic energy function defined on the source surface with landmark constraints. For numerical solutions, we compute the map with the approach of solving partial differential equations on implicit surfaces. The direct mapping method has the following properties: (1) it has the advantage of being automatic; (2) it is invariant to the pose of HC shapes. In our experiments, we apply the direct mapping method to study temporal changes of HC asymmetry in Alzheimer's disease (AD) using HC surfaces from 12 AD patients and 14 normal controls. Our results show that the AD group has a different trend in temporal changes of HC asymmetry than the group of normal controls. We also demonstrate the flexibility of the direct mapping method by applying it to construct spherical maps of HC surfaces. Spherical harmonics (SPHARM) analysis is then applied and it confirms our results on temporal changes of HC asymmetry in AD.

Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

The impact of nonlinear pedagogy on physical education teacher education students’ intrinsic motivation

Background: Providing motivationally supportive physical education experiences for learners is crucial since empirical evidence in sport and physical education research has associated intrinsic motivation with positive educational outcomes. Self-determination theory (SDT) provides a valuable framework for examining motivationally supportive physical education experiences through satisfaction of three basic psychological needs: autonomy, competence and relatedness. However, the capacity of the prescriptive teaching philosophy of the dominant traditional physical education teaching approach to effectively satisfy the psychological needs of students to engage in physical education has been questioned. The constraints-led approach (CLA) has been proposed as a viable alternative teaching approach that can effectively support students’ self-motivated engagement in physical education. Purpose: We sought to investigate whether adopting the learning design and delivery of the CLA, guided by key pedagogical principles of nonlinear pedagogy (NLP), would address basic psychological needs of learners, resulting in higher self-reported levels of intrinsic motivation. The claim was investigated using action research. The teacher/researcher delivered two lessons aimed at developing hurdling skills: one taught using the CLA and the other using the traditional approach. Participants and Setting: The main participant for this study was the primary researcher and lead author who is a PETE educator, with extensive physical education teaching experience. A sample of 54 pre-service PETE students undertaking a compulsory second year practical unit at an Australian university was recruited for the study, consisting of an equal number of volunteers from each of two practical classes. A repeated measures experimental design was adopted, with both practical class groups experiencing both teaching approaches in a counterbalanced order. Data collection and analysis: Immediately after participation in each lesson, participants completed a questionnaire consisting of 22 items chosen from validated motivation measures of basic psychological needs and indices of intrinsic motivation, enjoyment and effort. All questionnaire responses were indicated on a 7-point Likert scale. A two-tailed, paired-samples t-test was used to compare the groups’ motivation subscale mean scores for each teaching approach. The size of the effect for each group was calculated using Cohen’s d. To determine whether any significant differences between the subscale mean scores of the two groups was due to an order effect, a two-tailed, independent samples t test was used. Findings: Participants’ reported substantially higher levels of self-determination and intrinsic motivation during the CLA hurdles lesson compared to during the traditional hurdles lesson. Both groups reported significantly higher motivation subscale mean scores for competence, relatedness, autonomy, enjoyment and effort after experiencing the CLA than mean scores reported after experiencing the traditional approach. This significant difference was evident regardless of the order that each teaching approach was experienced. Conclusion: The theoretically based pedagogical principles of NLP that inform learning design and delivery of the CLA may provide teachers and coaches with tools to develop more functional pedagogical climates, which result in students exhibiting more intrinsically motivated behaviours during learning.

A method for estimating intrinsic noise in electroretinographic (ERG) signals

Purpose To develop a signal processing paradigm for extracting ERG responses to temporal sinusoidal modulation with contrasts ranging from below perceptual threshold to suprathreshold contrasts. To estimate the magnitude of intrinsic noise in ERG signals at different stimulus contrasts. Methods Photopic test stimuli were generated using a 4-primary Maxwellian view optical system. The 4-primary lights were sinusoidally temporally modulated in-phase (36 Hz; 2.5 - 50% Michelson). The stimuli were presented in 1 s epochs separated by a 1 ms blank interval and repeated 160 times (160.16 s duration) during the recording of the continuous flicker ERG from the right eye using DTL fiber electrodes. After artefact rejection, the ERG signal was extracted using Fourier methods in each of the 1 s epochs where a stimulus was presented. The signal processing allows for computation of the intrinsic noise distribution in addition to the signal to noise (SNR) ratio. Results We provide the initial report that the ERG intrinsic noise distribution is independent of stimulus contrast whereas SNR decreases linearly with decreasing contrast until the noise limit at ~2.5%. The 1ms blank intervals between epochs de-correlated the ERG signal at the line frequency (50 Hz) and thus increased the SNR of the averaged response. We confirm that response amplitude increases linearly with stimulus contrast. The phase response shows a shallow positive relationship with stimulus contrast. Conclusions This new technique will enable recording of intrinsic noise in ERG signals above and below perceptual visual threshold and is suitable for measurement of continuous rod and cone ERGs across a range of temporal frequencies, and post-receptoral processing in the primary retinogeniculate pathways at low stimulus contrasts. The intrinsic noise distribution may have application as a biomarker for detecting changes in disease progression or treatment efficacy.

Molecular Origin of the Intrinsic Bending Force for Helical Morphology Observed in Chiral Amphiphilic Assemblies: Concentration and Size Dependence

The formation of the helical morphology in monolayers and bilayers of chiral amphiphilic assemblies is believed to be driven at least partly by the interactions at the chiral centers of the amphiphiles. However, a detailed microscopic understanding of these interactions and their relation with the helix formation is still not clear. In this article a study of the molecular origin of the chirality-driven helix formation is presented by calculating, for the first time, the effective pair potential between a pair of chiral molecules. This effective potential depends on the relative sizes of the groups attached to the two chiral centers, on the orientation of the amphiphile molecules, and also on the distance between them. We find that for the mirror-image isomers (in the racemic modification) the minimum energy conformation is a nearly parallel alignment of the molecules. On the other hand, the same for a pair of molecules of one kind of enantiomer favors a tilt angle between them, thus leading to the formation of a helical morphology of the aggregate. The tilt angle is determined by the size of the groups attached to the chiral centers of the pair of molecules considered and in many cases predicted it to be close to 45 degrees. The present study, therefore, provides a molecular origin of the intrinsic bending force, suggested by Helfrich (J. Chem. Phys. 1986, 85, 1085-1087), to be responsible for the formation of helical structure. This effective potential may explain many of the existing experimental results, such as the size and the concentration dependence of the formation of helical morphology. It is further found that the elastic forces can significantly modify the pitch predicted by the chiral interactions alone and that the modified real pitch is close to the experimentally observed value. The present study is expected to provide a starting point for future microscopic studies.

Rattling modes and the intrinsic vibrational spectrum of beetle-type scanning tunneling microscopes

It is known that the vibrational spectra of beetle-type scanning tunneling microscopes with a total mass of ≈3–4 g contain extrinsic ‘rattling’ modes in the frequency range extending from 500 to 1700 Hz that interfere with image acquisition. These modes lie below the lowest calculated eigenfrequency of the beetle and it has been suggested that they arise from the inertial sliding of the beetle between surface asperities on the raceway. In this paper we describe some cross-coupling measurements that were performed on three home-built beetle-type STMs of two different designs. We provide evidence that suggests that for beetles with total masses of 12–15 g all the modes in the rattling range are intrinsic. This provides additional support for the notion that the vibrational properties of beetle-type scanning tunneling microscopes can be improved by increasing the contact pressure between the feet of the beetle and the raceway.

Level of contribution of intrinsic risk factors to the management of patients with plantar heel pain

Introduction: Injuries in the lower extremity are considered to have multifactorial causes, whilst people with heel pain represent the most frequent cause of visits to health professionals. Managing these patients can be very difficult. The purpose of this research is to identify key variables which can influence foot health in patients with heel pain. Materials and method: A cross-sectional observational study was carried out with a sample of sixty-two participants recruited from the Educational Welfare Unit of the University of Malaga. The therapists, blinded for the study, fill in the data with anthropometric information and the FPI, while participants fill in the foot health status questionnaire, FHSQ. The most significant results reveal that there is a moderate relation between the clinical variables and the FHSQ commands. The most significant contribution is the BMI in the foot health status questionnaire. Conclusion: The variables which can help manage clinical subjects with heel pain are age, BMI, footwear and FPI (left foot).