Drug abusers perceptions of their parents.

Many clinicians in the area of drug addiction believe that emotional problems arise from particular styles of parenting. To investigate this link, 63 young male and female addicts who had sought treatment completed the Parental Bonding Instrument which tapped their perceptions of their relationship with each parent. Addicts reported early parental experiences differing from those of a control group. Drug abusers judged their parents as cold, indifferent, controlling and intrusive. In addition, these perceptions were shared by male and female addicts. These results, together with previous research suggest that these perceptions might well point to a general risk factor for the development of a broad range of psychological and psychiatric disorders. In addition, the issue of family factors in the design and implementation of drug treatment programs needs to be addressed.

An analytical method for assessing stage-specific drug activity in Plasmodium vivax malaria : implications for ex vivo drug susceptibility testing

The emergence of highly chloroquine (CQ) resistant P. vivax in Southeast Asia has created an urgent need for an improved understanding of the mechanisms of drug resistance in these parasites, the development of robust tools for defining the spread of resistance, and the discovery of new antimalarial agents. The ex vivo Schizont Maturation Test (SMT), originally developed for the study of P. falciparum, has been modified for P. vivax. We retrospectively analysed the results from 760 parasite isolates assessed by the modified SMT to investigate the relationship between parasite growth dynamics and parasite susceptibility to antimalarial drugs. Previous observations of the stage-specific activity of CQ against P. vivax were confirmed, and shown to have profound consequences for interpretation of the assay. Using a nonlinear model we show increased duration of the assay and a higher proportion of ring stages in the initial blood sample were associated with decreased effective concentration (EC50) values of CQ, and identify a threshold where these associations no longer hold. Thus, starting composition of parasites in the SMT and duration of the assay can have a profound effect on the calculated EC50 for CQ. Our findings indicate that EC50 values from assays with a duration less than 34 hours do not truly reflect the sensitivity of the parasite to CQ, nor an assay where the proportion of ring stage parasites at the start of the assay does not exceed 66%. Application of this threshold modelling approach suggests that similar issues may occur for susceptibility testing of amodiaquine and mefloquine. The statistical methodology which has been developed also provides a novel means of detecting stage-specific drug activity for new antimalarials.

Utilising Reliability and Condition Monitoring Data for Asset Health Prognosis

The ability to forecast machinery health is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models which attempt to forecast machinery health based on condition data such as vibration measurements. This paper demonstrates how the population characteristics and condition monitoring data (both complete and suspended) of historical items can be integrated for training an intelligent agent to predict asset health multiple steps ahead. The model consists of a feed-forward neural network whose training targets are asset survival probabilities estimated using a variation of the Kaplan–Meier estimator and a degradation-based failure probability density function estimator. The trained network is capable of estimating the future survival probabilities when a series of asset condition readings are inputted. The output survival probabilities collectively form an estimated survival curve. Pump data from a pulp and paper mill were used for model validation and comparison. The results indicate that the proposed model can predict more accurately as well as further ahead than similar models which neglect population characteristics and suspended data. This work presents a compelling concept for longer-range fault prognosis utilising available information more fully and accurately.

FOXC2 expression links epithelial-mesenchymal transition and stem cell properties in breast cancer

Resistance to chemotherapy and metastases are the major causes of breast cancer-related mortality. Moreover, cancer stem cells (CSC) play critical roles in cancer progression and treatment resistance. Previously, it was found that CSC-like cells can be generated by aberrant activation of epithelial–mesenchymal transition (EMT), thereby making anti-EMT strategies a novel therapeutic option for treatment of aggressive breast cancers. Here, we report that the transcription factor FOXC2 induced in response to multiple EMT signaling pathways as well as elevated in stem cell-enriched factions is a critical determinant of mesenchymal and stem cell properties, in cells induced to undergo EMT- and CSC-enriched breast cancer cell lines. More specifically, attenuation of FOXC2 expression using lentiviral short hairpin RNA led to inhibition of the mesenchymal phenotype and associated invasive and stem cell properties, which included reduced mammosphere-forming ability and tumor initiation. Whereas, overexpression of FOXC2 was sufficient to induce CSC properties and spontaneous metastasis in transformed human mammary epithelial cells. Furthermore, a FOXC2-induced gene expression signature was enriched in the claudin-low/basal B breast tumor subtype that contains EMT and CSC features. Having identified PDGFR-β to be regulated by FOXC2, we show that the U.S. Food and Drug Administration-approved PDGFR inhibitor, sunitinib, targets FOXC2-expressing tumor cells leading to reduced CSC and metastatic properties. Thus, FOXC2 or its associated gene expression program may provide an effective target for anti-EMT-based therapies for the treatment of claudin-low/basal B breast tumors or other EMT-/CSC-enriched tumors.

Underground power cable environment on-line monitoring and analysis

Knowledge of cable parameters has been well established but a better knowledge of the environment in which the cables are buried lags behind. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Results based on long term continuous field data are given. A probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. This data from field studies can reduce the risk in cable rating decisions and provide a basis for reliable prediction of “hot spot” of an existing cable circuit

Dry powder inhaler formulations : effect of carrier size on the drug dispersion

Background: The size of the carrier influences drug aerosolization from a dry powder inhaler (DPI) formulation. Lactose particles with irregular shape and rough surface in a variety of sizes are additionally used as carriers; however, contradictory reports exist regarding the effect of carrier size on the dispersion of drug. We examined the influence of the spherical particle size of the biodegradable polylactide-co-glycolide (PLGA) carrier on the aerosolization of a model drug, salbutamol sulphate (SS). Methods: Four different sizes (20-150 µm) of polymer carriers were fabricated using solvent evaporation technique and the dispersion of SS from these carriers was measured by a Twin Stage Impinger (TSI). The size and morphological properties of polymer carriers were determined by laser diffraction and SEM, respectively. Results: The FPF was found to increase from 5.6% to 21.3% with increasing carrier sizeup to150 µm. Conclusions: The aerosolization of drug increased linearly with the size of polymer carriers. For a fixed mass of drug particles in a formulation, the mass of drug particles per unit area of carriers is higher in formulations containing the larger carriers, which leads to an increase in the dispersion of drug due to the increased mechanical forces occurred between the carriers and the device walls.

Monitoring smartphones for anomaly detection

In this paper we demonstrate how to monitor a smartphone running Symbian operating system and Windows Mobile in order to extract features for anomaly detection. These features are sent to a remote server because running a complex intrusion detection system on this kind of mobile device still is not feasible due to capability and hardware limitations. We give examples on how to compute relevant features and introduce the top ten applications used by mobile phone users based on a study in 2005. The usage of these applications is recorded by a monitoring client and visualized. Additionally, monitoring results of public and self-written malwares are shown. For improving monitoring client performance, Principal Component Analysis was applied which lead to a decrease of about 80 of the amount of monitored features.

Symposium - How effective are brief motivational interviewing interventions : Are they necessary? Do they require enhancement? Can they be translated into routine clinical practice?

Brief interventions are effective for problem drinking and reductions are known to occur in association with screening and assessment. Design and methods: This study aimed to determine how much change occurred between baseline assessment and a one-session brief intervention (S1), and the predictors of early change among adults with comorbid depression and alcohol misuse (n=202) participating in a clinical trial. The primary focus was on changes in Beck Depression Inventory fastscreen scores and alcohol consumption (standard drinks per week) prior to random allocation to nine further sessions addressing either depression, alcohol, or both problems. Results: There were large and clinically significant reductions between baseline and S1, with the strongest predictors being baseline scores in the relevant domain and change in the other domain. Client engagement was also predictive of early depression changes. Discussion and Conclusion: Monitoring progress in both domains from first contact, and provision of empathic care, followed by brief intervention appear to be useful for this high prevalence comorbidity...

Goodbye TAIS and thanks for all the information

The Therapeutic Advice and Information Service was funded by the National Prescribing Service to provide a national drug information service for health professionals working in the community. For ten years the service achieved high levels of client satisfaction, and reached its contracted target of 6000 enquiries about medicines per year, however the service ceased on 30 June 2010.

Real-time risk monitoring in business processes : a sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

Performance characterization of VGCF/epoxy nanocomposite sensors under static load cycles and in static structural health monitoring

Compared to conventional metal-foil strain gauges, nanocomposite piezoresistive strain sensors have demonstrated high strain sensitivity and have been attracting increasing attention in recent years. To fulfil their ultimate success, the performance of vapor growth carbon fiber (VGCF)/epoxy nanocomposite strain sensors subjected to static cyclic loads was evaluated in this work. A strain-equivalent quantity (resistance change ratio) in cantilever beams with intentionally induced notches in bending was evaluated using the conventional metal-foil strain gauges and the VGCF/epoxy nanocomposite sensors. Compared to the metal-foil strain gauges, the nanocomposite sensors are much more sensitive to even slight structural damage. Therefore, it was confirmed that the signal stability, reproducibility, and durability of these nanocomposite sensors are very promising, leading to the present endeavor to apply them for static structural health monitoring.

Monitoring android for collaborative anomaly detection : a first architectural draft

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways, e.g. for payment systems or assisting the lives of elderly or disabled people. Security threats for these devices become more and more dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level and where third-party developers first time have the opportunity to develop kernel-based low-level security tools. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS, holding the greatest market share among all smartphone OSs, was even closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners privacy. Since signature-based approaches mainly detect known malwares, anomaly-based approaches can be a valuable addition to these systems. They base on mathematical algorithms processing data that describe the state of a certain device. For gaining this data, a monitoring client is needed that has to extract usable information (features) from the monitored system. Our approach follows a dual system for analyzing these features. On the one hand, functionality for on-device light-weight detection is provided. But since most algorithms are resource exhaustive, remote feature analysis is provided on the other hand. Having this dual system enables event-based detection that can react to the current detection need. In our ongoing research we aim to investigates the feasibility of light-weight on-device detection for certain occasions. On other occasions, whenever significant changes are detected on the device, the system can trigger remote detection with heavy-weight algorithms for better detection results. In the absence of the server respectively as a supplementary approach, we also consider a collaborative scenario. Here, mobile devices sharing a common objective are enabled by a collaboration module to share information, such as intrusion detection data and results. This is based on an ad-hoc network mode that can be provided by a WiFi or Bluetooth adapter nearly every smartphone possesses.

Social signal processing for pain monitoring using a hidden conditional random field

utomatic pain monitoring has the potential to greatly improve patient diagnosis and outcomes by providing a continuous objective measure. One of the most promising methods is to do this via automatically detecting facial expressions. However, current approaches have failed due to their inability to: 1) integrate the rigid and non-rigid head motion into a single feature representation, and 2) incorporate the salient temporal patterns into the classification stage. In this paper, we tackle the first problem by developing a “histogram of facial action units” representation using Active Appearance Model (AAM) face features, and then utilize a Hidden Conditional Random Field (HCRF) to overcome the second issue. We show that both of these methods improve the performance on the task of pain detection in sequence level compared to current state-of-the-art-methods on the UNBC-McMaster Shoulder Pain Archive.

Nanotechnology in the targeted drug delivery for bone diseases and bone regeneration

Nanotechnology is a vigorous research area and one of its important applications is in biomedical sciences. Among biomedical applications, targeted drug delivery is one of the most extensively studied subjects. Nanostructured particles and scaffolds have been widely studied for increasing treatment efficacy and specificity of present treatment approaches. Similarly, this technique has been used for treating bone diseases including bone regeneration. In this review, we have summarized and highlighted the recent advancement of nanostructured particles and scaffolds for the treatment of cancer bone metastasis, osteosarcoma, bone infections and inflammatory diseases, osteoarthritis, as well as for bone regeneration. Nanoparticles used to deliver deoxyribonucleic acid and ribonucleic acid molecules to specific bone sites for gene therapies are also included. The investigation of the implications of nanoparticles in bone diseases have just begun, and has already shown some promising potential. Further studies have to be conducted, aimed specifically at assessing targeted delivery and bioactive scaffolds to further improve their efficacy before they can be used clinically