Reflections on assessing academic quality in marketing, and the UK REF

Purpose – The purpose of this editorial is to comment on the paper by Saunders and Wong in this issue. In doing so, the paper reflects on the notion of academic quality within marketing research, along with the systems in place to evaluate and reward it. Design/methodology/approach – The paper takes a reflective, discursive approach. Findings – The author finds that, while Saunders and Wong make a number of pertinent observations, and come up with interesting solutions, the notion of academic quality espoused in their paper is based on a logically flawed set of arguments. Research limitations/implications – The paper is primarily a personal view, and thus does not rely on any empirical research. Practical implications – There are key implications for many parties involved in the creation and assessment of marketing knowledge. In particular, scholars would be well advised to consider notions of quality in relation to their own work, rather than rely unquestioningly on existing definitions. Policy makers and research managers (e.g. business school deans) also need to consider what quality in academic research really is, and how to appropriately direct and reward it. Originality/value – The paper provides another perspective on the well-established debate regarding quality, and thus it is hoped will stimulate further thinking.

Psychosoziale Merkmale der Arbeit, Überforderungserleben und Depressivität

Die vorliegende Studie untersuchte die im Job-Demand-Control-Support-Modell und Effort-Reward-Imbalance-Modell beschriebenen Tätigkeitsmerkmale in Bezug auf Depressivität in einer Stichprobe von 265 Erwerbstätigen. Anhand konfirmatorischer Faktorenanalysen wurden Gemeinsamkeiten und Unterschiede beider Modelle geprüft. Anschließend wurde die Bedeutung der nachweisbaren Tätigkeitsmerkmale für die Vorhersage von Depressivität getestet und untersucht, inwieweit die Effekte durch Überforderungserleben mediiert werden. Die Analysen zeigten, dass die Modelle sowohl gemeinsame (Arbeitsintensität bzw. berufliche Anforderungen) als auch distinkte Arbeitsmerkmale (Tätigkeitsspielraum, Arbeitsplatzsicherheit, beruflicher Status, soziale Anerkennung) erfassen. Hohe Arbeitsintensität, geringe Arbeitsplatzsicherheit und fehlende soziale Anerkennung standen in signifikantem Zusammenhang mit Depressivität. Anders als erwartet war der berufliche Status positiv mit Depressivität assoziiert, während für den Tätigkeitsspielraum keine signifikanten Effekte nachweisbar waren. Das Pfadmodell bestätigte sowohl direkte als auch durch Überforderungserleben vermittelte Zusammenhänge zwischen den Tätigkeitsmerkmalen und Depressivität (39 % Varianzaufklärung). Die Ergebnisse bieten eine Grundlage für die Identifizierung potenzieller Risikofaktoren für das Auftreten depressiver Symptome am Arbeitsplatz. This study examined the job characteristics in the Job-Demand-Control-Support Model and in the Effort-Reward Imbalance Model with regard to depression in a sample of 265 employees. First, we tested by means of confirmatory factor analysis similarities and differences of the two models. Secondly, job characteristics were introduced as predictors in a path model to test their relation with depression. Furthermore, we examined whether the associations were mediated by the experience of excessive demands. Our analyses showed the demand/effort component to be one common factor, while decision latitude and reward (subdivided into the three facets of job security, social recognition, and status-related reward) remained distinctive components. Employees with high job demands/effort, low job security, low social recognition, but high status-related rewards reported higher depression scores. Unexpectedly, status-related rewards were positively associated with depression, while we found no significant effects for decision latitude. The path models confirmed direct as well as mediation effects (through experienced excessive demands) between job characteristics and depression (39 % explained variance in depression). Our results could be useful to identify possible job-related risk factors for depression.

Gene delivery of the elastase inhibitor elafin protects macrophages from neutrophil elastase-mediated impairment of apoptotic cell recognition

The resolution of inflammation is dependent on recognition and phagocytic removal of apoptotic cells by macrophages. Receptors for apoptotic cells are sensitive to degradation by human neutrophil elastase (HNE). We show in the present study that HNE cleaves macrophage cell surface CD14 and in so doing, reduces phagocytic recognition of apoptotic lymphocytic cells (Mutu 1). Using an improved method of adenovirus-mediated transfection of macrophages with the HNE inbibitor elafin, we demonstrate that elafin overexpression prevents CD14 cleavage and restores apoptotic cell recognition by macrophages. This approach of genetic modification of macrophages could be used to restore apoptotic cell recognition in inflammatory conditions. (C) 2004 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Late development of metric part-relational processing in object recognition

Four experiments with unfamiliar objects examined the remarkably late consolidation of part-relational relative to part-based object recognition (Jüttner, Wakui, Petters, Kaur, & Davidoff, 2013). Our results indicate a particularly protracted developmental trajectory for the processing of metric part relations. Schoolchildren aged 7 to 14 years and adults were tested in 3-Alternative-Forced-Choice tasks to judge the correct appearance of upright and inverted newly learned multipart objects that had been manipulated in terms of individual parts or part relations. Experiment 1 showed that even the youngest tested children were close to adult levels of performance for recognizing categorical changes of individual parts and relative part position. By contrast, Experiment 2 demonstrated that performance for detecting metric changes of relative part position was distinctly reduced in young children compared with recognizing metric changes of individual parts, and did not approach the latter until 11 to 12 years. A similar developmental dissociation was observed in Experiment 3, which contrasted the detection of metric relative-size changes and metric part changes. Experiment 4 showed that manipulations of metric size that were perceived as part (rather than part-relational) changes eliminated this dissociation. Implications for theories of object recognition and similarities to the development of face perception are discussed. © 2014 American Psychological Association.

Latin Americans in London:language, integration and ethnic identity

This thesis studies the links between language, migration and integration in the context of the 'new migrant' group of Latin Americans in London. It reviews the many ways in which language impacts the integration processes of migrants by influencing people's access to jobs, services, social contacts and information. By focusing on migrants' experiences this research also investigates the ways in which language and identity articulate, as well as the affective variables that are at play in the acquisition of the local language. With a large sector trapped in a cycle of poor command of English and labour market disadvantage, many Latin Americans experience exclusion and poverty. In reaction to this, a sector of the community is campaigning for ethnic minority recognition. This work reviews the debates for recognition and the strategy of organising around ethnicity, paying special attention to the role language plays in the process. The study is based on over two and half years of qualitative research, which included interviews, surveys, and long-term participant observation within a community organisation and a recognition campaign. Its interdisciplinary perspective allows the recognition of both the intimate links between language and identity, as well as the social and structural forces that influence migrants' linguistic integration. It unveils the practical and symbolic value that the mother tongue has for Latin American migrants and provides a broader account of their experiences. This research calls attention to the need for a more comprehensive approach to the study of language and migration in order to acknowledge the affective and social factors involved in the linguistic practices of migrants. By studying the community's struggles for recognition, this work evidences both the importance of visibility for minority groups in London and the intrinsic methodological limitations of monitoring through ethnic categorisation.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.

The unhappy marriage of religion and politics:problems and pitfalls for gender equality

This article explores how religion as a political force shapes and deflects the struggle for gender equality in contexts marked by different histories of nation building and challenges of ethnic diversity, different state–society relations (from the more authoritarian to the more democratic), and different relations between state power and religion (especially in the domain of marriage, family and personal laws). It shows how ‘private’ issues, related to the family, sexuality and reproduction, have become sites of intense public contestation between conservative religious actors wishing to regulate them based on some transcendent moral principle, and feminist and other human rights advocates basing their claims on pluralist and time- and context-specific solutions. Not only are claims of ‘divine truth’ justifying discriminatory practices against women hard to challenge, but the struggle for gender equality is further complicated by the manner in which it is closely tied up with, and inseparable from, struggles for social and economic justice, ethnic/racial recognition, and national self-determination vis-à-vis imperial/global domination.

Differences between younger and older adults in the structure of suicidal intent and its correlates

OBJECTIVE: To analyze differences in the variables associated with severity of suicidal intent and in the main factors associated with intent when comparing younger and older adults. DESIGN: Observational, descriptive cross-sectional study. SETTING: Four general hospitals in Madrid, Spain. PARTICIPANTS: Eight hundred seventy suicide attempts by 793 subjects split into two groups: 18-54 year olds and subjects older than 55 years. MEASUREMENTS: The authors tested the factorial latent structure of suicidal intent through multigroup confirmatory factor analysis for categorical outcomes and performed statistical tests of invariance across age groups using the DIFFTEST procedure. Then, they tested a multiple indicators-multiple causes (MIMIC) model including different covariates regressed on the latent factor "intent" and performed two separate MIMIC models for younger and older adults to test for differential patterns. RESULTS: Older adults had higher suicidal intent than younger adults (z = 2.63, p = 0.009). The final model for the whole sample showed a relationship of intent with previous attempts, support, mood disorder, personality disorder, substance-related disorder, and schizophrenia and other psychotic disorders. The model showed an adequate fit (chi²[12] = 22.23, p = 0.035; comparative fit index = 0.986; Tucker-Lewis index = 0.980; root mean square error of approximation = 0.031; weighted root mean square residual = 0.727). All covariates had significant weights in the younger group, but in the older group, only previous attempts and mood disorders were significantly related to intent severity. CONCLUSIONS: The pattern of variables associated with suicidal intent varies with age. Recognition, and treatment of geriatric depression may be the most effective measure to prevent suicidal behavior in older adults.

Consistency and accuracy in memory: Effects of schema-typicality, retention interval and question-format

This study examined the effect of schemas on consistency and accuracy of memory across interviews, providing theoretical hypotheses explaining why inconsistencies may occur. The design manipulated schema-typicality of items (schema-typical and atypical), question format (free-recall, cued-recall and recognition) and retention interval (immediate/2 week and 2 week/4 week). Consistency, accuracy and experiential quality of memory were measured. ^ All independent variables affected accuracy and experiential quality of memory while question format was the only variable affecting consistency. These results challenge the commonly held notion in the legal arena that consistency is a proxy for accuracy. The study also demonstrates that other variables, such as item-typicality and retention interval have different effects on consistency and accuracy in memory. ^

Multidimensional classification and diagnosis of leukemia in flow cytometry

This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

Estrogen and lithium: Facilitating factors involved in brain cell signaling pathways

Learning and memory in adult females decline during menopause and estrogen replacement therapy is commonly prescribed during menopause. Post-menopausal women tend to suffer from depression and are prescribed antidepressants – in addition to hormone therapy. Estrogen replacement therapy is a topic that engenders debate since several studies contradict its efficacy as a palliative therapy for cognitive decline and neurodegenerative diseases. Signaling transduction pathways can alter brain cell activity, survival, and morphology by facilitating transcription factor DNA binding and protein production. The steroidal hormone estrogen and the anti-depressant drug lithium interact through these signaling transduction pathways facilitating transcription factor activation. The paucity of data on how combined hormones and antidepressants interact in regulating gene expression led me to hypothesize that in primary mixed brain cell cultures, combined 17β-estradiol (E2) and lithium chloride (LiCl) (E2/LiCl) will alter genetic expression of markers involved in synaptic plasticity and neuroprotection. Results from these studies indicated that a 48 h treatment of E2/LiCl reduced glutamate receptor subunit genetic expression, but increased neurotrophic factor and estrogen receptor genetic expression. Combined treatment also failed to protect brain cell cultures from glutamate excitotoxicity. If lithium facilitates protein signaling pathways mediated by estrogen, can lithium alone serve as a palliative treatment for post-menopause? This question led me to hypothesize that in estrogen-deficient mice, lithium alone will increase episodic memory (tested via object recognition), and enhance expression in the brain of factors involved in anti-apoptosis, learning and memory. I used bilaterally ovariectomized (bOVX) C57BL/6J mice treated with LiCl for one month. Results indicated that LiCl-treated bOVX mice increased performance in object recognition compared with non-treated bOVX. Increased performance in LiCl-treated bOVX mice coincided with augmented genetic and protein expression in the brain. Understanding the molecular pathways of estrogen will assist in identifying a palliative therapy for menopause-related dementia, and lithium may serve this purpose by acting as a selective estrogen-mediated signaling modulator.

Neural network based off-line handwritten text recognition system

This dissertation introduces a new system for handwritten text recognition based on an improved neural network design. Most of the existing neural networks treat mean square error function as the standard error function. The system as proposed in this dissertation utilizes the mean quartic error function, where the third and fourth derivatives are non-zero. Consequently, many improvements on the training methods were achieved. The training results are carefully assessed before and after the update. To evaluate the performance of a training system, there are three essential factors to be considered, and they are from high to low importance priority: (1) error rate on testing set, (2) processing time needed to recognize a segmented character and (3) the total training time and subsequently the total testing time. It is observed that bounded training methods accelerate the training process, while semi-third order training methods, next-minimal training methods, and preprocessing operations reduce the error rate on the testing set. Empirical observations suggest that two combinations of training methods are needed for different case character recognition. Since character segmentation is required for word and sentence recognition, this dissertation provides also an effective rule-based segmentation method, which is different from the conventional adaptive segmentation methods. Dictionary-based correction is utilized to correct mistakes resulting from the recognition and segmentation phases. The integration of the segmentation methods with the handwritten character recognition algorithm yielded an accuracy of 92% for lower case characters and 97% for upper case characters. In the testing phase, the database consists of 20,000 handwritten characters, with 10,000 for each case. The testing phase on the recognition 10,000 handwritten characters required 8.5 seconds in processing time.

Color-based surface reflectance separation for scene illumination estimation and rendering

Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. ^ Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. ^ As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. ^ In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects. ^

Estrogen and Lithium: Facilitating Factors Involved in Brain Cell Signaling Pathways

Learning and memory in adult females decline during menopause and estrogen replacement therapy is commonly prescribed during menopause. Post-menopausal women tend to suffer from depression and are prescribed antidepressants – in addition to hormone therapy. Estrogen replacement therapy is a topic that engenders debate since several studies contradict its efficacy as a palliative therapy for cognitive decline and neurodegenerative diseases. Signaling transduction pathways can alter brain cell activity, survival, and morphology by facilitating transcription factor DNA binding and protein production. The steroidal hormone estrogen and the anti-depressant drug lithium interact through these signaling transduction pathways facilitating transcription factor activation. The paucity of data on how combined hormones and antidepressants interact in regulating gene expression led me to hypothesize that in primary mixed brain cell cultures, combined 17beta-estradiol (E2) and lithium chloride (LiCl) (E2/LiCl) will alter genetic expression of markers involved in synaptic plasticity and neuroprotection. Results from these studies indicated that a 48 h treatment of E2/LiCl reduced glutamate receptor subunit genetic expression, but increased neurotrophic factor and estrogen receptor genetic expression. Combined treatment also failed to protect brain cell cultures from glutamate excitotoxicity. If lithium facilitates protein signaling pathways mediated by estrogen, can lithium alone serve as a palliative treatment for post-menopause? This question led me to hypothesize that in estrogen-deficient mice, lithium alone will increase episodic memory (tested via object recognition), and enhance expression in the brain of factors involved in anti-apoptosis, learning and memory. I used bilaterally ovariectomized (bOVX) C57BL/6J mice treated with LiCl for one month. Results indicated that LiCl-treated bOVX mice increased performance in object recognition compared with non-treated bOVX. Increased performance in LiCl-treated bOVX mice coincided with augmented genetic and protein expression in the brain. Understanding the molecular pathways of estrogen will assist in identifying a palliative therapy for menopause-related dementia, and lithium may serve this purpose by acting as a selective estrogen-mediated signaling modulator.