An Autonomic Cross-Platform Operating Environment for On-Demand Internet Computing

The Internet has evolved into a global and ubiquitous communication medium interconnecting powerful application servers, diverse desktop computers and mobile notebooks. Along with recent developments in computer technology, such as the convergence of computing and communication devices, the way how people use computers and the Internet has changed people´s working habits and has led to new application scenarios. On the one hand, pervasive computing, ubiquitous computing and nomadic computing become more and more important since different computing devices like PDAs and notebooks may be used concurrently and alternately, e.g. while the user is on the move. On the other hand, the ubiquitous availability and pervasive interconnection of computing systems have fostered various trends towards the dynamic utilization and spontaneous collaboration of available remote computing resources, which are addressed by approaches like utility computing, grid computing, cloud computing and public computing. From a general point of view, the common objective of this development is the use of Internet applications on demand, i.e. applications that are not installed in advance by a platform administrator but are dynamically deployed and run as they are requested by the application user. The heterogeneous and unmanaged nature of the Internet represents a major challenge for the on demand use of custom Internet applications across heterogeneous hardware platforms, operating systems and network environments. Promising remedies are autonomic computing systems that are supposed to maintain themselves without particular user or application intervention. In this thesis, an Autonomic Cross-Platform Operating Environment (ACOE) is presented that supports On Demand Internet Computing (ODIC), such as dynamic application composition and ad hoc execution migration. The approach is based on an integration middleware called crossware that does not replace existing middleware but operates as a self-managing mediator between diverse application requirements and heterogeneous platform configurations. A Java implementation of the Crossware Development Kit (XDK) is presented, followed by the description of the On Demand Internet Computing System (ODIX). The feasibility of the approach is shown by the implementation of an Internet Application Workbench, an Internet Application Factory and an Internet Peer Federation. They illustrate the use of ODIX to support local, remote and distributed ODIC, respectively. Finally, the suitability of the approach is discussed with respect to the support of ODIC

PRN Medicines Management for Older People with Long-Term Mental Health Disorders in Home Care

publishedVersio

Postgraduate palliative care education and curricular issues in Central Asia, Eastern and South-Eastern Europe: Results from a quantitative study

Introduction. The WHO Europe Office, together with the European Association for Palliative Care, issupporting the development of an interdisciplinary core curriculum for health care professionals in theEuropean Region, which is to be given to the countries as a recommendation.Material and methods. Between April and September 2018, a research journey to Central Asia, Easternand South-Eastern Europe took place. It covered two main tasks: collecting quantitative data using a surveyand collecting qualitative data by conducting on-site interviews. This article contains the quantitativepart. Experts in palliative care education in 23 countries were invited to fill out a questionnaire. The datareceived from 23 questions were statistically evaluated by IBM SPSS Statistics 25.Results. 27 surveys received from 21 countries were evaluated. In one-third of the surveyed countries, thereis still no postgraduate training in palliative care. The main barriers to the development of educational workare limited political interest, followed by limited educational structures, missing curricula, lack of trainersand the limited healthcare system. For 92.6% of all respondents, a WHO-recommended interdisciplinarypostgraduate core curriculum would help promote palliative care in their country.Conclusion. There is a high need for postgraduate education in general and the intended core curriculumin particular. The results of the survey, along with those from the interviews in a later second part of thepublication, are essential for the development of a core curriculum

Needs Assessment of Safe Medicines Management for Older People With Cognitive Disorders in Home Care: An Integrative Systematic Review

Background and Objectives: The global trend of healthcare is to improve the quality and safety of care for older people with cognitive disorders in their own home. There is a need to identify how medicines management for these older people who are cared by their family caregivers can be safeguarded. This integrative systematic review aimed to perform the needs assessment of medicines management for older people with cognitive disorders who receive care from their family caregivers in their own home.Methods: An integrative systematic review of the international literature was conducted to retrieve all original qualitative and quantitative studies that involved the family caregivers of older people with cognitive disorders in medicines management in their own home. MeSH terms and relevant keywords were used to search four online databases of PubMed (including Medline), Scopus, CINAHL, and Web of Science and to retrieve studies published up to March 2021. Data were extracted by two independent researchers, and the review process was informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Given that selected studies were heterogeneous in terms of the methodological structure and research outcomes, a meta-analysis could not be performed. Therefore, narrative data analysis and knowledge synthesis were performed to report the review results.Results: The search process led to retrieving 1,241 studies, of which 12 studies were selected for data analysis and knowledge synthesis. They involved 3,890 older people with cognitive disorders and 3,465 family caregivers. Their methodologies varied and included cohort, randomised controlled trial, cross-sectional studies, grounded theory, qualitative framework analysis, and thematic analysis. The pillars that supported safe medicines management with the participation of family caregivers in home care consisted of the interconnection between older people's needs, family caregivers' role, and collaboration of multidisciplinary healthcare professionals.Conclusion: Medicines management for older people with cognitive disorders is complex and multidimensional. This systematic review provides a comprehensive image of the interconnection between factors influencing the safety of medicines management in home care. Considering that home-based medicines management is accompanied with stress and burden in family caregivers, multidisciplinary collaboration between healthcare professionals is essential along with the empowerment of family caregivers through education and support

Adrenal Hormone Interactions and Metabolism: A Single Sample Multi-Omics Approach

The adrenal gland is important for many physiological and pathophysiological processes, but studies are often restricted by limited availability of sample material. Improved methods for sample preparation are needed to facilitate analyses of multiple classes of adrenal metabolites and macromolecules in a single sample. A procedure was developed for preparation of chromaffin cells, mouse adrenals, and human chromaffin tumors that allows for multi-omics analyses of different metabolites and preservation of native proteins. To evaluate the new procedure, aliquots of samples were also prepared using conventional procedures. Metabolites were analyzed by liquid-chromatography with mass spectrometry or electrochemical detection. Metabolite contents of chromaffin cells and tissues analyzed with the new procedure were similar or even higher than with conventional methods. Catecholamine contents were comparable between both procedures. The TCA cycle metabolites, cis-aconitate, isocitate, and α-ketoglutarate were detected at higher concentrations in cells, while in tumor tissue only isocitrate and potentially fumarate were measured at higher contents. In contrast, in a broad untargeted metabolomics approach, a methanol-based preparation procedure of adrenals led to a 1.3-fold higher number of detected metabolites. The established procedure also allows for simultaneous investigation of adrenal hormones and related enzyme activities as well as proteins within a single sample. This novel multi-omics approach not only minimizes the amount of sample required and overcomes problems associated with tissue heterogeneity, but also provides a more complete picture of adrenal function and intra-adrenal interactions than previously possible

In-Situ Solar Tower Power Plant Optimization by Differentiable Raytracing

Solar tower power plants deliver climate-neutral electricity and process heat and can play a key role to facilitate the ongoing energy transition. These plants reflect sunlight with thousands of mirrors (heliostats) to a receiver and can generate temperatures over 1000°C. In practice, a plant must be operated with safety margins as even small surface deformations and heliostat misalignments can locally lead to dangerous temperature peaks. These imperfections are difficult to assess and limit the plant's efficiency, which hinders commercial success in a competitive market. We present a computational technique that predicts the incident power distribution of each heliostat including the inaccuracies based solely on focal spot images that are already acquired in most solar power plants. The method combines differentiable ray tracing with a smooth parametric description of the heliostat and reconstructs flawed mirror surfaces with sub-millimeter precision. Applied at the solar tower plant in Jülich, our approach outperforms all alternatives in accuracy and reliability. The approach can be integrated into the existing infrastructure and plant control at low cost, leading to increased efficiency of existing and decreased expenses for future power plants and supports establishing a new, green energy technology. For other fields, our approach can be a blueprint. We implement a common simulation technique in the Machine Learning framework PyTorch, leveraging automatic differentiation and GPU computation. By combining gradient-based optimization methods and a tunable parametric heliostat model, we overcome the high data requirements of data-centric methods while at the same time maintaining the flexibility required for modeling a complex real-world system

In-Situ Solar Tower Power Plant Optimization by Differentiable Raytracing

Solar tower power plants deliver climate-neutral electricity and process heat and can play a key role to facilitate the ongoing energy transition. These plants reflect sunlight with thousands of mirrors (heliostats) to a receiver and can generate temperatures over 1000°C. In practice, a plant must be operated with safety margins as even small surface deformations and heliostat misalignments can locally lead to dangerous temperature peaks. These imperfections are difficult to assess and limit the plant's efficiency, which hinders commercial success in a competitive market. We present a computational technique that predicts the incident power distribution of each heliostat including the inaccuracies based solely on focal spot images that are already acquired in most solar power plants. The method combines differentiable ray tracing with a smooth parametric description of the heliostat and reconstructs flawed mirror surfaces with sub-millimeter precision. Applied at the solar tower plant in Jülich, our approach outperforms all alternatives in accuracy and reliability. The approach can be integrated into the existing infrastructure and plant control at low cost, leading to increased efficiency of existing and decreased expenses for future power plants and supports establishing a new, green energy technology. For other fields, our approach can be a blueprint. We implement a common simulation technique in the Machine Learning framework PyTorch, leveraging automatic differentiation and GPU computation. By combining gradient-based optimization methods and a tunable parametric heliostat model, we overcome the high data requirements of data-centric methods while at the same time maintaining the flexibility required for modeling a complex real-world system

A systematic practice review: providing palliative care for people with Parkinson's disease and their caregivers

Background: People with Parkinson’s disease has significant and increasing physical, psychosocial and spiritual needs, as well as problems with coordination and continuity of care. Despite the benefits that palliative care could offer, there is no consensus on how it should be delivered. Aim: The aim of this study is to provide a pragmatic overview of the evidence to make clinical recommendations to improve palliative care for people with Parkinson’s disease and their caregivers. Design:A systematic review method was adopted to determine the strength of evidence, supported by feedback from an expert panel, to generate the ‘do’, ‘do not do’ and ‘do not know’ recommendations for palliative care. Data sources: Searches were conducted via OVID to access CINAHL, MEDLINE, EMBASE and the Cochrane Library from 01/01/2006 to 31/05/2021. An additional search was conducted in December 2022. The search was limited to articles that included empirical studies of approaches to enabling palliative care. Results: A total of 62 studies met inclusion criteria. There is evidence that education about palliative care and movement disorders is essential. palliative care should be multi-disciplinary, individualised and coordinated. Proactive involvement and support of caregivers throughout the illness is recommended. Limited data provide referral indicators for palliative care integration. Discussions about advance care planning should be held early.Conclusions: Consideration of palliative care integration based on symptom burden and personal preferences, coordination and continuity of care are needed to maintain the quality of life of people with Parkinson’s disease and their caregivers.info:eu-repo/semantics/publishedVersio

All-sky imager based irradiance nowcasts: combining a physical and a deep learning mdoel

Improved solar irradiance nowcasts based on all-sky imagers. Hybrid physical and end-to-end machine learning (ML) model. The ML model is based on an multi-modal deep learning model combining an vision transformer (for images) with an time series transformer (for time series data). Skill score improvements >12% points are achieved. Correct detection of cloud ramp rates improved by >8% points

High Interlaboratory Reproducibility and Accuracy of Next-Generation-Sequencing- Based Bacterial Genotyping in a Ring Trial

Today, next-generation whole-genome sequencing (WGS) is increasingly used to determine the genetic relationships of bacteria on a nearly whole-genome level for infection control purposes and molecular surveillance. Here, we conducted a multicenter ring trial comprising five laboratories to determine the reproducibility and accuracy of WGS-based typing. The participating laboratories sequenced 20 blind-coded Staphylococcus aureus DNA samples using 250-bp paired-end chemistry for library preparation in a single sequencing run on an Illumina MiSeq sequencer. The run acceptance criteria were sequencing outputs >5.6 Gb and Q30 read quality scores of > 75%. Subsequently, spa typing, multilocus sequence typing (MLST), ribosomal MLST, and core genome MLST (cgMLST) were performed by the participants. Moreover, discrepancies in cgMLST target sequences in comparisons with the included and also published sequence of the quality control strain ATCC 25923 were resolved using Sanger sequencing. All five laboratories fulfilled the run acceptance criteria in a single sequencing run without any repetition. Of the 400 total possible typing results, 394 of the reported spa types, sequence types (STs), ribosomal STs (rSTs), and cgMLST cluster types were correct and identical among all laboratories; only six typing results were missing. An analysis of cgMLST allelic profiles corroborated this high reproducibility; only 3 of 183,927 (0.0016%) cgMLST allele calls were wrong. Sanger sequencing confirmed all 12 discrepancies of the ring trial results in comparison with the published sequence of ATCC 25923. In summary, this ring trial demonstrated the high reproducibility and accuracy of current next-generation sequencing-based bacterial typing for molecular surveillance when done with nearly completely locked-down methods