992 resultados para Java Advanced Imaging


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Background Malnutrition is common in patients with advanced epithelial ovarian cancer (EOC), and is associated with impaired quality of life (QoL), longer hospital stay and higher risk of treatment-related adverse events. This phase III multi-centre randomised clinical trial tested early enteral feeding versus standard care on postoperative QoL. Methods From 2009 to 2013, 109 patients requiring surgery for suspected advanced EOC, moderately to severely malnourished were enrolled at five sites across Queensland and randomised to intervention (n = 53) or control (n = 56) groups. Intervention involved intraoperative nasojejunal tube placement and enteral feeding until adequate oral intake could be maintained. Despite being randomised to intervention, 20 patients did not receive feeds (13 did not receive the feeding tube; 7 had it removed early). Control involved postoperative diet as tolerated. QoL was measured at baseline, 6 weeks postoperatively and 30 days after the third cycle of chemotherapy. The primary outcome measure was the difference in QoL between the intervention and the control group. Secondary endpoints included treatment-related adverse event occurrence, length of stay, postoperative services use, and nutritional status. Results Baseline characteristics were comparable between treatment groups. No significant difference in QoL was found between the groups at any time point. There was a trend towards better nutritional status in patients who received the intervention but the differences did not reach statistical significance except for the intention-to-treat analysis at 7 days postoperatively (11.8 intervention vs. 13.8 control, p 0.04). Conclusion Early enteral feeding did not significantly improve patients' QoL compared to standard of care but may improve nutritional status.

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There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

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Accepted Article Abstract Background: Liver diseases in Australia are estimated to affect 6 million people with a societal cost of $51 billion annually. Information about utilization of specialist hepatology care is critical in informing policy makers about the requirements for delivery of hepatology-related health care. Aims: This study examined etiology and severity of liver disease seen in a tertiary hospital hepatology clinic, as well as resource utilisation patterns. Methods: A longitudinal cohort study included consecutive patients booked in hepatology outpatient clinics during a 3 month period. Subsequent outpatient appointments for these patients over the following 12 months were then recorded. Results: During the initial 3 month period 1471 appointments were scheduled with a hepatologist, 1136 of which were attended. 21% of patients were “new cases”. Hepatitis B (HBV) was the most common disease etiology for new cases (37%). Advanced disease at presentation varied between etiology, with HBV (5%), Hepatitis C (HCV) (31%), non-alcoholic fatty liver disease (NAFLD) (46%) and alcoholic liver disease (ALD) (72%). Most patients (83%) attended multiple hepatology appointments, and a range of referrals patterns for procedures, investigations and other specialty assessments were observed. Conclusions: There is a high prevalence of HBV in new case referrals. Patients with HCV, NAFLD and ALD have a high prevalence of advanced liver disease at referral, requiring ongoing surveillance for development of decompensated liver disease and liver cancer. These findings that describe patterns of health service utilisation among patients with liver disease provide useful information for planning sustainable health service provision for this clinical population

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Background The size and flexibility of the nursing workforce has positioned nursing as central to the goals of health service improvement. Nursing's response to meeting these goals has resulted in proliferation of advanced practice nursing with a confusing array of practice profiles, titles and roles. Whilst numerous models and definitions of advanced practice nursing have been developed there is scant published research of significant scope that supports these models. Consequently there is an ongoing call in the literature for clarity and stability in nomenclature, and confusion in the health industry on how to optimise the utility of advanced practice nursing. Objectives To identify and delineate advanced practice from other levels of nursing practice through examination of a national nursing workforce. Design A cross-sectional electronic survey of nurses using the validated Advanced Practice Role Delineation tool based on the Strong Model of Advanced Practice. Participants Study participants were registered nurses employed in a clinical service environment across all states and territories of Australia. Methods A sample of 5662 registered nurses participated in the study. Domain means for each participant were calculated then means for nursing position titles were calculated. Position titles were grouped by delineation and were compared with one-way analysis of variance on domain means. The alpha for all tests was set at 0.05. Significant effects were examined with Scheffe post hoc comparisons to control for Type 1 error. Results The survey tool was able to identify position titles where nurses were practicing at an advanced level and to delineate this cohort from other levels of nursing practice, including nurse practitioner. The results show that nurses who practice at an advanced level are characterised by high mean scores across all Domains of the Strong Model of Advanced Practice. The mean scores of advanced practice nurses were significantly different from nurse practitioners in the Direct Care Domain and significantly different from other levels of nurse across all domains. Conclusions The study results show that the nurse practitioner, advanced practice nurse and foundation level registered nurse have different patterns of practice and the Advanced Practice Role Delineation tool has the capacity to clearly delineate and define advanced practice nursing. These findings make a significant contribution to the international debate and show that the profession can now identify what is and what is not advanced practice in nursing.

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Low Level Virtual Machine (LLVM) on moderni koko ohjelman elinkaaren optimointeihin keskittyvä kääntäjäarkkitehtuuri. Java-virtuaalikone on puolestaan suosittu korkean tason virtuaalikone, johon monien ohjelmointikielten toteutus nykyään perustuu. Tutkielmassa esitellään alun perin suorituskykyisen C- ja C++-kääntäjän toteuttamiseksi luotu LLVM-järjestelmä ja arvioidaan, miten hyvin LLVM-infrastruktuuri tukee Java-virtuaalikoneen toteuttamista. Tämän lisäksi tutkielmassa pohditaan, miten dynaamisten kielten usein tarvitsemaa suoritusaikaista ja lähdekieliriippuvaista optimointia voidaan tukea lähdekieliriippumattomassa LLVM-järjestelmässä. Lopuksi tutkielmassa esitellään kehitysehdotelma yleisen roskienkeruuinfrastruktuurin toteuttamiseksi LLVM:ssä, mikä tukisi dynaamista muistia automaattisesti hallitsevien kielten, kuten Javan ja sen virtuaalikoneen toteuttamista.

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Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

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Aim To assess the effectiveness of a decision support intervention using a pragmatic single blind Randomized Controlled Trial. Background Worldwide the proportion of older people (aged 65 years and over) is rising. This population is known to have a higher prevalence of chronic diseases including chronic kidney disease. The resultant effect of the changing health landscape is seen in the increase in older patients (aged ≥65 years) commencing on dialysis. Emerging evidence suggests that for some older patients dialysis may provide minimal benefit. In a majority of renal units non-dialysis management is offered as an alternative to undertaking dialysis. Research regarding decision-making support that is required to assist this population in choosing between dialysis or non-dialysis management is limited. Design. A multisite single blinded pragmatic randomized controlled trial is proposed. Methods Patients will be recruited from four Queensland public hospitals and randomizd into either the control or intervention group. The decision support intervention is multimodal and includes counselling provided by a trained nurse. The comparator is standard decision-making support. The primary outcomes are decisional regret and decisional conflict. Secondary outcomes are improved knowledge and quality of life. Ethics approval obtained November 2014. Conclusion This is one of the first randomized controlled trials assessing a decision support intervention in older people with advance chronic kidney disease. The results may provide guidance for clinicians in future approaches to assist this population in decision-making to ensure reduced decisional regret and decisional conflict.

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Special switching sequences can be employed in space-vector-based generation of pulsewidth-modulated (PWM) waveforms for voltage-source inverters. These sequences involve switching a phase twice, switching the second phase once, and clamping the third phase in a subcycle. Advanced bus-clamping PWM (ABCPWM) techniques have been proposed recently that employ such switching sequences. This letter studies the spectral properties of the waveforms produced by these PWM techniques. Further, analytical closed-form expressions are derived for the total rms harmonic distortion due to these techniques. It is shown that the ABCPWM techniques lead to lower distortion than conventional space vector PWM and discontinuous PWM at higher modulation indexes. The findings are validated on a 2.2-kW constant $V/f$ induction motor drive and also on a 100-kW motor drive.

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Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

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Background Patients with diabetic foot disease require frequent screening to prevent complications and may be helped through telemedical home monitoring. Within this context, the goal was to determine the validity and reliability of assessing diabetic foot infection using photographic foot imaging and infrared thermography. Subjects and Methods For 38 patients with diabetes who presented with a foot infection or were admitted to the hospital with a foot-related complication, photographs of the plantar foot surface using a photographic imaging device and temperature data from six plantar regions using an infrared thermometer were obtained. A temperature difference between feet of > 2.2 °C defined a ''hotspot.'' Two independent observers assessed each foot for presence of foot infection, both live (using the Perfusion-Extent-Depth- Infection-Sensation classification) and from photographs 2 and 4 weeks later (for presence of erythema and ulcers). Agreement in diagnosis between live assessment and (the combination of ) photographic assessment and temperature recordings was calculated. Results Diagnosis of infection from photographs was specific (> 85%) but not very sensitive (< 60%). Diagnosis based on hotspots present was sensitive (> 90%) but not very specific (<25%). Diagnosis based on the combination of photographic and temperature assessments was both sensitive (> 60%) and specific (> 79%). Intra-observer agreement between photographic assessments was good (Cohen's j = 0.77 and 0.52 for both observers). Conclusions Diagnosis of foot infection in patients with diabetes seems valid and reliable using photographic imaging in combination with infrared thermography. This supports the intended use of these modalities for the home monitoring of high-risk patients with diabetes to facilitate early diagnosis of signs of foot infection.

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Purpose: To explore the fatigue self-management behaviors and factors associated with effectiveness of these behaviors in patients with advanced cancer. Design: Prospective longitudinal interviewer-administered survey. Setting: A tertiary cancer center in Queensland Australia. Sample: One hundred fifty two outpatients with metastatic breast, lung, colorectal and prostate cancer experiencing fatigue (>3/10) were recruited. Main Research Variables: Fatigue self-management behaviors outcomes (perceived effectiveness, self-efficacy and frequency), medical/demographic characteristics (including sites of primary cancer and metastasis, comorbidity, performance status), social support, depressive, anxiety, and other symptoms were assessed. Findings: The participants reported moderate levels of fatigue at baseline (M=5.85, SD 1.44), and maintained moderate levels at 4 weeks and 8 weeks. On average, participants consistently used approximately nine behaviors at each time point. Factors significantly associated with higher levels of perceived effectiveness of fatigue self-management behaviors were higher self-efficacy (p<.001), higher education level (p=.02), and lower levels of depressive symptoms (p=.04). Conclusions: The findings of this study demonstrate that patients with cancer, even with advanced disease, still want and are able to use a number of behaviors to control their fatigue. Self-management interventions that aim to enhance self-efficacy and address any concurrent depressive symptoms have the potential to reduce fatigue severity. Implications for Nursing: Nurses are well positioned to play a key role in supporting patients in their fatigue self-management. Knowledge Translation: This study particularly focused on the perspectives of patients about fatigue self-management, highlighting a number of issues requiring further attention in clinical practice and the potential for future research.

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Background Chronic kidney disease (CKD) leads to a range of symptoms, which are often under-recognised and little is known about the multidimensional symptom experience in advanced CKD. Objectives To examine (1) symptom burden at CKD stages 4 and 5, and dialysis modalities, and (2) demographic and renal history correlates of symptom burden. Methods Using a cross-sectional design, a convenience sample of 436 people with CKD was recruited from three hospitals. The CKD Symptom Burden Index (CKD-SBI) was used to measure the prevalence, severity, distress and frequency of 32 symptoms. Demographic and renal history data were also collected. Results Of the sample, 75.5 % were receiving dialysis (haemodialysis, n = 287; peritoneal dialysis, n = 42) and 24.5 % were not undergoing dialysis (stage 4, n = 69; stage 5, n = 38). Participants reported an average of 13.01 ± 7.67 symptoms. Fatigue and pain were common and burdensome across all symptom dimensions. While approximately one-third experienced sexual symptoms, when reported these symptoms were frequent, severe and distressing. Haemodialysis, older age and being female were independently associated with greater symptom burden. Conclusions In CKD, symptom burden is better understood when capturing the multidimensional aspects of a range of physical and psychological symptoms. Fatigue, pain and sexual dysfunction are key contributors to symptom burden, and these symptoms are often under-recognised and warrant routine assessment. The CKD-SBI offers a valuable tool for renal clinicians to assess symptom burden, leading to the commencement of timely and appropriate interventions.