The link between belongingness and depressive symptoms: An exploration in the workplace interpersonal context

Interpersonal factors are crucial to a deepened understanding of depression. Belongingness, also referred to as connectedness, has been established as a strong risk/protective factor for depressive symptoms. To elucidate this link it may be beneficial to investigate the relative importance of specific psychosocial contexts as belongingness foci. Here we investigate the construct of workplace belongingness. Employees at a disability services organisation (N = 125) completed measures of depressive symptoms, anxiety symptoms, workplace belongingness and organisational commitment. Psychometric analyses, including Horn's parallel analyses, indicate that workplace belongingness is a unitary, robust and measurable construct. Correlational data indicate a substantial relationship with depressive symptoms (r = −.54) and anxiety symptoms (r = −.39). The difference between these correlations was statistically significant, supporting the particular importance of belongingness cognitions to the etiology of depression. Multiple regression analyses support the hypothesis that workplace belongingness mediates the relationship between affective organisational commitment and depressive symptoms. It is likely that workplaces have the potential to foster environments that are intrinsically less depressogenic by facilitating workplace belongingness. From a clinical perspective, cognitions regarding the workplace psychosocial context appear to be highly salient to individual psychological health, and hence warrant substantial attention.

Reduction rules for reset/inhibitor nets

Reset/inhibitor nets are Petri nets extended with reset arcs and inhibitor arcs. These extensions can be used to model cancellation and blocking. A reset arc allows a transition to remove all tokens from a certain place when the transition fires. An inhibitor arc can stop a transition from being enabled if the place contains one or more tokens. While reset/inhibitor nets increase the expressive power of Petri nets, they also result in increased complexity of analysis techniques. One way of speeding up Petri net analysis is to apply reduction rules. Unfortunately, many of the rules defined for classical Petri nets do not hold in the presence of reset and/or inhibitor arcs. Moreover, new rules can be added. This is the first paper systematically presenting a comprehensive set of reduction rules for reset/inhibitor nets. These rules are liveness and boundedness preserving and are able to dramatically reduce models and their state spaces. It can be observed that most of the modeling languages used in practice have features related to cancellation and blocking. Therefore, this work is highly relevant for all kinds of application areas where analysis is currently intractable.

Economic development, enlightenment and creative transformation : creative industries in the New China

This paper examines some of the implications for China of the creative industries agenda as drawn by some recent commentators. The creative industries have been seen by many commentators as essential if China is to move from an imitative low-value economy to an innovative high value one. Some suggest that this trajectory is impossible without a full transition to liberal capitalism and democracy - not just removing censorship but instituting 'enlightenment values'. Others suggest that the development of the creative industries themselves will promote social and political change. The paper suggests that the creative industries takes certain elements of a prior cultural industries concept and links it to a new kind of economic development agenda. Though this agenda presents problems for the Chinese government it does not in itself imply the kind of radical democratic political change with which these commentators associate it. In the form in which the creative industries are presented – as part of an informational economy rather than as a cultural politics – it can be accommodated by a Chinese regime doing ‘business as usual’.

FGFR2 mutations are rare across histologic subtypes of ovarian cancer

OBJECTIVE: Ovarian cancer is the leading cause of death from gynecologic malignancies in the Western world. Fibroblast growth factor receptor (FGFR) signaling has been implicated to play a role in ovarian tumorigenesis. Mutational activation of one member of this receptor family, FGFR2, is a frequent event in endometrioid endometrial cancer. Given the similarities in the histologic and molecular genetics of ovarian and endometrial cancers, we hypothesized that activating FGFR2 mutations may occur in a subset of endometrioid ovarian tumors, and possibly other histotypes. METHODS: Six FGFR2 exons were sequenced in 120 primary ovarian tumors representing the major histologic subtypes. RESULTS: FGFR2 mutation was detected at low frequency in endometrioid (1/46, 2.2%) and serous (1/41, 2.4%) ovarian cancer. No mutations were detected in clear cell, mucinous, or mixed histology tumors or in the ovarian cancer cell lines tested. Functional characterization of the FGFR2 mutations confirmed that the mutations detected in ovarian cancer result in receptor activation. CONCLUSIONS: Despite the low incidence of FGFR2 mutations in ovarian cancer, the two FGFR2 mutations identified in ovarian tumors (S252W, Y376C) overlap with the oncogenic mutations previously identified in endometrial tumors, suggesting activated FGFR2 may contribute to ovarian cancer pathogenesis in a small subset of ovarian tumors.

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

Relationship to the bereaved and perceptions of severity of trauma differentiate elements of posttraumatic growth

The field of bereavement and grief has been expanding to recognise the potential for growth following the loss of a loved one. This study sought to examine the effect of the relationship to the deceased and perceptions of the severity of the trauma on dimensions of posttraumatic growth. Participants were 146 people who had lost either: a) a first degree relative, b) a second degree relative, or c) a non-related friend. Results demonstrated that both severity and the relationship to the bereaved differentiate posttraumatic growth outcomes. For example, participants who had lost a first degree relative reported higher levels of growth than those who had lost a second degree relative. Consistent with previous research in general trauma populations, the more severe the loss was rated, the higher the levels of growth. Implications for practice are discussed.

Younger and older women's concerns about menopause after breast cancer

A number of treatments for breast cancer induce menopause. This study's aim was to explore women's perceptions and beliefs about menopausal symptoms and their management following breast cancer, and to compare younger and older women's experiences. Data were collected via semi-structured focus groups from women who had undergone treatment for breast cancer, and who were currently experiencing menopausal symptoms. Data were interpreted by way of simple inductive thematic analysis. The women experienced a range of menopausal symptoms that they were not prepared for and found difficult to manage. The central themes related to their lack of knowledge of how to manage menopausal symptoms, and the distress and helplessness that arose from this. Women who were diagnosed prior to 40 years of age reported additional menopausal issues than women who were older at diagnosis. The women in this study expressed a thirst for information related to menopause after breast cancer. The women identified that their needs with regard to menopause after breast cancer were not being met, either through their own lack of knowledge or via conflicting or absent support and management. The importance of enabling women to deal with menopausal symptoms was a central theme to emerge from the data.

Tool-supported dataflow analysis of a security-critical embedded device

Defence organisations perform information security evaluations to confirm that electronic communications devices are safe to use in security-critical situations. Such evaluations include tracing all possible dataflow paths through the device, but this process is tedious and error-prone, so automated reachability analysis tools are needed to make security evaluations faster and more accurate. Previous research has produced a tool, SIFA, for dataflow analysis of basic digital circuitry, but it cannot analyse dataflow through microprocessors embedded within the circuit since this depends on the software they run. We have developed a static analysis tool that produces SIFA compatible dataflow graphs from embedded microcontroller programs written in C. In this paper we present a case study which shows how this new capability supports combined hardware and software dataflow analyses of a security critical communications device.