Social innovation and social enterprise : evidence from Australia

‘Social innovation’ is a construct increasingly used to explain the practices, processes and actors through which sustained positive transformation occurs in the network society (Mulgan, G., Tucker, S., Ali, R., Sander, B. (2007). Social innovation: What it is, why it matters and how can it be accelerated. Oxford:Skoll Centre for Social Entrepreneurship; Phills, J. A., Deiglmeier, K., & Miller, D. T. Stanford Social Innovation Review, 6(4):34–43, 2008.). Social innovation has been defined as a “novel solution to a social problem that is more effective, efficient, sustainable, or just than existing solutions, and for which the value created accrues primarily to society as a whole rather than private individuals.” (Phills,J. A., Deiglmeier, K., & Miller, D. T. Stanford Social Innovation Review, 6 (4):34–43, 2008: 34.) Emergent ideas of social innovation challenge some traditional understandings of the nature and role of the Third Sector, as well as shining a light on those enterprises within the social economy that configure resources in novel ways. In this context, social enterprises – which provide a social or community benefit and trade to fulfil their mission – have attracted considerable policy attention as one source of social innovation within a wider field of action (see Leadbeater, C. (2007). ‘Social enterprise and social innovation: Strategies for the next 10 years’, Cabinet office,Office of the third sector http://www.charlesleadbeater.net/cms xstandard/social_enterprise_innovation.pdf. Last accessed 19/5/2011.). And yet, while social enterprise seems to have gained some symbolic traction in society, there is to date relatively limited evidence of its real world impacts.(Dart, R. Not for Profit Management and Leadership, 14(4):411–424, 2004.) In other words, we do not know much about the social innovation capabilities and effects of social enterprise. In this chapter, we consider the social innovation practices of social enterprise, drawing on Mulgan, G., Tucker, S., Ali, R., Sander, B. (2007). Social innovation: What it is, why it matters and how can it be accelerated. Oxford: Skoll Centre for Social Entrepreneurship: 5) three dimensions of social innovation: new combinations or hybrids of existing elements; cutting across organisational, sectoral and disciplinary boundaries; and leaving behind compelling new relationships. Based on a detailed survey of 365 Australian social enterprises, we examine their self-reported business and mission-related innovations, the ways in which they configure and access resources and the practices through which they diffuse innovation in support of their mission. We then consider how these findings inform our understanding of the social innovation capabilities and effects of social enterprise,and their implications for public policy development.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Study protocol : Screening and treatment of alcohol-related trauma (START): a randomised controlled trial

Background: The incidence of mandibular fractures in the Northern Territory of Australia is very high, especially among Indigenous people. Alcohol intoxication is implicated in the majority of facial injuries, and substance use is therefore an important target for secondary prevention. The current study tests the efficacy of a brief therapy, Motivational Care Planning, in improving wellbeing and substance misuse in youth and adults hospitalised with alcohol-related facial trauma. Methods and design: The study is a randomised controlled trial with 6 months of follow-up, to examine the effectiveness of a brief and culturally adapted intervention in improving outcomes for trauma patients with at-risk drinking admitted to the Royal Darwin Hospital maxillofacial surgery unit. Potential participants are identified using AUDIT-C questionnaire. Eligible participants are randomised to either Motivational Care Planning (MCP) or Treatment as Usual (TAU). The outcome measures will include quantity and frequency of alcohol and other substance use by Timeline Followback. The recruitment target is 154 participants, which with 20% dropout, is hoped to provide 124 people receiving treatment and follow-up. Discussion: This project introduces screening and brief interventions for high-risk drinkers admitted to the hospital with facial trauma. It introduces a practical approach to integrating brief interventions in the hospital setting, and has potential to demonstrate significant benefits for at-risk drinkers with facial trauma.

Internet interventions for treatment of alcohol related problems

This is the protocol for a review and there is no abstract. The objectives are as follows: The primary objective of this review will be to assess the effect of internet and mobile phone alcohol-related interventions on reducing participants' alcohol consumption. Secondary objectives will include assessing the impact of the interventions on symptoms of alcohol-related disorders and degree of alcohol dependence, the effects on functioning, and patient acceptability. The review will also assess whether there are different outcomes for different diagnostic groups, and which intervention approaches or components (including therapeutic support) may be contributing to any positive effects.

Lifting the joint venture veil : liability of related entities for misleading conduct of agents engaged by joint venture partners

At common law, a corporation may be liable vicariously for the conduct of its appointed agents, employees or directors. This generally requires the agent or employee to be acting in the course of his or her agency or employment and, in the case of representations, to have actual or implied authority to make the representations. The circumstances in which a corporation may be liable for the conduct of its agents, employees or directors is broadened under the Australian Consumer Law (ACL) to where one of these parties engages in conduct “on behalf of” the corporation. As the decision in Bennett v Elysium Noosa Pty Ltd (in liq) demonstrates, this may extend to liability for the misleading conduct of a salesperson for the joint venture to parties who are not formal members of the joint venture, but where the joint venture activities are within the course of the entity’s “business, affairs or activities”.

Selective cleavage of human sex hormone-binding globulin by kallikrein-related peptidases and effects on androgen action in LNCaP prostate cancer cells

Stimulation of the androgen receptor via bioavailable androgens, including testosterone and testosterone metabolites, is a key driver of prostate development and the early stages of prostate cancer. Androgens are hydrophobic and as such require carrier proteins, including sex hormone-binding globulin (SHBG), to enable efficient distribution from sites of biosynthesis to target tissues. The similarly hydrophobic corticosteroids also require a carrier protein whose affinity for steroid is modulated by proteolysis. However, proteolytic mechanisms regulating the SHBG/androgen complex have not been reported. Here, we show that the cancer-associated serine proteases, kallikrein-related peptidase (KLK)4 and KLK14, bind strongly to SHBG in glutathione S-transferase interaction analyses. Further, we demonstrate that active KLK4 and KLK14 cleave human SHBG at unique sites and in an androgen-dependent manner. KLK4 separated androgen-free SHBG into its two laminin G-like (LG) domains that were subsequently proteolytically stable even after prolonged digestion, whereas a catalytically equivalent amount of KLK14 reduced SHBG to small peptide fragments over the same period. Conversely, proteolysis of 5α-dihydrotestosterone (DHT)-bound SHBG was similar for both KLKs and left the steroid binding LG4 domain intact. Characterization of this proteolysis fragment by [(3)H]-labeled DHT binding assays revealed that it retained identical affinity for androgen compared with full-length SHBG (dissociation constant = 1.92 nM). Consistent with this, both full-length SHBG and SHBG-LG4 significantly increased DHT-mediated transcriptional activity of the androgen receptor compared with DHT delivered without carrier protein. Collectively, these data provide the first evidence that SHBG is a target for proteolysis and demonstrate that a stable fragment derived from proteolysis of steroid-bound SHBG retains binding function in vitro.

The effect of injury diagnosis on expected Postconcussion Syndrome (PCS) symptom reporting and illness perception

Objective: To determine if systematic variation of diagnostic terminology (i.e. concussion, minor head injury [MHI], mild traumatic brain injury [mTBI]) following a standardized injury description produced different expected symptoms and illness perceptions. We hypothesized that worse outcomes would be expected of mTBI, compared to other diagnoses, and that MHI would be perceived as worse than concussion. Method:108 volunteers were randomly allocated to conditions in which they read a vignette describing a motor vehicle accident-related mTBI followed by: a diagnosis of mTBI (n=27), MHI (n=24), concussion (n=31); or, no diagnosis (n=26). All groups rated: a) event ‘undesirability’; b) illness perception, and; c) expected Postconcussion Syndrome (PCS) and Posttraumatic Stress Disorder (PTSD) symptoms six months post injury. Results: On average, more PCS symptomatology was expected following mTBI compared to other diagnoses, but this difference was not statistically significant. There was a statistically significant group effect on undesirability (mTBI>concussion & MHI), PTSD symptomatology (mTBI & no diagnosis>concussion), and negative illness perception (mTBI & no diagnosis>concussion). Conclusion: In general, diagnostic terminology did not affect anticipated PCS symptoms six months post injury, but other outcomes were affected. Given that these diagnostic terms are used interchangeably, this study suggests that changing terminology can influence known contributors to poor mTBI outcome.

Cellular model systems to study the tumor biological role of kallikrein-related peptidases in ovarian and prostate cancer

Since the identification of the gene family of kallikrein related peptidases (KLKs), their function has been robustly studied at the biochemical level. In vitro biochemical studies have shown that KLK proteases are involved in a number of extracellular processes that initiate intracellular signaling pathways by hydrolysis, as reviewed in Chapters 8, 9, and 15, Volume 1. These events have been associated with more invasive phenotypes of ovarian, prostate, and other cancers. Concomitantly, aberrant expression of KLKs has been associated with poor prognosis of patients with ovarian and prostate cancer (Borgoño and Diamandis, 2004; Clements et al., 2004; Yousef and Diamandis, 2009), with prostate-specific antigen (PSA, KLK3) being a long standing, clinically employed biomarker for prostate cancer (Lilja et al., 2008). Data generated from patient samples in clinical studies, alongwith biochemical activity, suggests that KLKs function in the development and progression of these diseases. To bridge the gap between their function at the molecular level and the clinical need for efficacious treatment and prognostic biomarkers, functional assessment at the in vitro cellular level, using various culture models, is increasing, particularly in a three-dimensional (3D) context (Abbott, 2003; Bissell and Radisky, 2001; Pampaloni et al., 2007; Yamada and Cukierman, 2007).

Systematic variation of the severity of motor vehicle accident-related traumatic brain injury vignettes produces different post-concussion symptom reports

This study investigated the specificity of the post-concussion syndrome (PCS) expectation-as-etiology hypothesis. Undergraduate students (n = 551) were randomly allocated to one of three vignette conditions. Vignettes depicted either a very mild (VMI), mild (MI), or moderate-to-severe (MSI) motor vehicle-related traumatic brain injury (TBI). Participants reported the PCS and PTSD symptoms that they imagined the depicted injury would produce. Secondary outcomes (knowledge of mild TBI, and the perceived undesirability of TBI) were also assessed. After data screening, the distribution of participants by condition was: VMI (n = 100), MI (n = 96), and MSI (n = 71). There was a significant effect of condition on PCS symptomatology, F(2, 264) = 16.55, p < .001. Significantly greater PCS symptomatology was expected in the MSI condition compared to the other conditions (MSI > VMI; medium effect, r = .33; MSI > MI; small-to-medium effect, r = .22). The same pattern of group differences was found for PTSD symptoms, F(2, 264) = 17.12, p < .001. Knowledge of mild TBI was not related to differences in expected PCS symptoms by condition; and the perceived undesirability of TBI was only associated with reported PCS symptomatology in the MSI condition. Systematic variation in the severity of a depicted TBI produces different PCS and PTSD symptom expectations. Even a very mild TBI vignette can elicit expectations of PCS symptoms.

The effect of Tai Chi on health related quality of life in people with elevated blood glucose or diabetes : a randomized controlled trial

Purpose The aim was to assess the effects of a Tai Chi based program on health related quality of life (HR-QOL) in people with elevated blood glucose or diabetes who were not on medication for glucose control. Method 41 participants were randomly allocated to either a Tai Chi intervention group (N = 20) or a usual medical care control group (N = 21). The Tai Chi group involved 3 x 1.5 hour supervised and group-based training sessions per week for 12 weeks. Indicators of HR-QOL were assessed by self-report survey immediately prior to and after the intervention. Results There were significant improvements in favour of the Tai Chi group for the SF36 subscales of physical functioning (mean difference = 5.46, 95% CI = 1.35-9.57, P < 0.05), role physical (mean difference = 18.60, 95% CI = 2.16-35.05, P < 0.05), bodily pain (mean difference = 9.88, 95%CI = 2.06-17.69, P < 0.05) and vitality (mean difference = 9.96, 95% CI = 0.77-19.15, P < 0.05). Conclusions The findings show that this Tai Chi program improved indicators of HR-QOL including physical functioning, role physical, bodily pain and vitality in people with elevated blood glucose or diabetes who were not on diabetes medication.

Impact of a novel nurse-led prechemotherapy education intervention (ChemoEd) on patient distress, symptom burden, and treatment-related information and support needs : results from a randomised, controlled trial

Background: High levels of distress and need for self-care information by patients commencing chemotherapy suggest that current prechemotherapy education is suboptimal. We conducted a randomised, controlled trial of a prechemotherapy education intervention (ChemoEd) to assess impact on patient distress, treatment-related concerns, and the prevalence and severity of and bother caused by six chemotherapy side-effects. Patients and methods: One hundred and ninety-two breast, gastrointestinal, and haematologic cancer patients were recruited before the trial closing prematurely (original target 352). ChemoEd patients received a DVD, question-prompt list, self-care information, an education consultation ≥24 h before first treatment (intervention 1), telephone follow-up 48 h after first treatment (intervention 2), and a face-to-face review immediately before second treatment (intervention 3). Patient outcomes were measured at baseline (T1: pre-education) and immediately preceding treatment cycles 1 (T2) and 3 (T3). Results: ChemoEd did not significantly reduce patient distress. However, a significant decrease in sensory/psychological (P = 0.027) and procedural (P = 0.03) concerns, as well as prevalence and severity of and bother due to vomiting (all P = 0.001), were observed at T3. In addition, subgroup analysis of patients with elevated distress at T1 indicated a significant decrease (P = 0.035) at T2 but not at T3 (P = 0.055) in ChemoEd patients. Conclusions: ChemoEd holds promise to improve patient treatment-related concerns and some physical/psychological outcomes; however, further research is required on more diverse patient populations to ensure generalisability.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

The human tissue kallikrein and kallikrein-related peptidase family

The human kallikrein-related peptidases are a subgroup of trypsin and chymotrypsin-like serine peptidases that are characterized by their homology to tissue kallikrein or kallikrein 1 (KLK1) encoded by the KLK1 gene (reviewed in[1-4]). The human KLK locus spans an approximately 320 kb region on chromosome 19q13.3-13.4 and contains fifteen genes encoding KLK1 and fourteen other kallikrein-related peptidases, KLK2-KLK15, which have been named contiguously in the locus in the order of their discovery [5-8] (Figure 606.1). It is the largest contiguous cluster of serine protease encoding genes in the human genome which has evolved from gene duplication of KLK1 and then subsequent reduplication of the newly evolved KLK genes [2]. The high conservation noted for KLK1-KLK3 (62-77%) reflects the proposed duplication of the KLK1 gene that produced the KLK2 gene which further generated the KLK3 gene. In contrast, the newer KLK4-KLK15 proteases share much less similarity, from 24-66%, although strong homology between KLK4 and KLK5, KLK9 and KLK11, and KLK10 and KLK12 suggests these genes are duplications of each other [2]...

Paclitaxel resistance and multicellular spheroid formation are induced by kallikrein-related peptidase 4 in serous ovarian cancer cells in an ascites mimicking microenvironment

High tumor kallikrein-related-peptidase 4 (KLK4) levels are associated with a poor outcome for women with serous epithelial ovarian cancer (EOC), for which peritoneal dissemination and chemoresistance are key events. To determine the role of KLK4 in these events, we examined KLK4-transfected SKOV-3 and endogenous KLK4 expressing OVCA432 cells in 3-dimensional (3D) suspension culture to mimic the ascites microenvironment. KLK4-SKOV-3 cells formed multicellular aggregates (MCAs) as seen in ascites, as did SKOV-3 cells treated with active KLK4. MCA formation was reduced by treatment with a KLK4 blocking antibody or the selective active site KLK4 sunflower trypsin inhibitor (SFTI-FCQR). KLK4-MCAs formed larger cancer cell foci in mesothelial cell monolayers than those formed by vector and native SKOV-3 cells, suggesting KLK4-MCAs are highly invasive in the peritoneal microenvironment. A high level of KLK4 is expressed by ascitic EOC cells compared to matched primary tumor cells, further supporting its role in the ascitic microenvironment. Interestingly, KLK4 transfected SKOV-3 cells expressed high levels of the KLK4 substrate, urokinase plasminogen activator (uPA), particularly in 3D-suspension, and high levels of both KLK4 and uPA were observed in patient cells taken from ascites. Importantly, the KLK4-MCAs were paclitaxel resistant which was reversed by SFTI-FCQR and to a lesser degree by the general serine protease inhibitor, Aprotinin, suggesting that in addition to uPA, other as yet unidentified substrates of KLK4 must be involved. Nonetheless, these data suggest that KLK4 inhibition, in conjunction with paclitaxel, may improve the outcome for women with serous epithelial ovarian cancer and high KLK4 levels in their tumors.