Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

Background. Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. © 2008 Scotch et al; licensee BioMed Central Ltd

Statistical evaluation of a new resistance model for cold-formed stainless steel cross-sections subjected to web crippling

This paper presents a statistical evaluation according to Annex D of EN 1990 (2002) of a new resistance function for web crippling design of cold-formed stainless steel cross-sections. This resistance function was derived by Bock et al. (2013) through the use of carefully validated numerical models with the aim to propose a design expression for stainless steel sections, which are currently designed following the provisions for cold-formed carbon steel sections given in EN 1993-1-3 (2006). Although it was shown that the proposed design equation is appropriate for application to various stainless steels, the statistical uncertainties in material properties that the different types of stainless steels exhibit require an assessment of various partial safety factors. The statistical assessment showed that the proposed resistance function by Bock et al. (2013) requires adjustment to satisfy the safety level set out in EN 1993-1-4 (2006); A recalibration is performed herein. The web crippling design provisions given in EN 1993-1-3 (2006) and SEI/ASCE 8-02 (2002) American standard for application to stainless steel are also statistically evaluated herein. Comparison with test and numerical data showed that the predictions of the recalibrated resistance function are better suited and consistent than existing design provisionsResearch Fund for Coal and Stee

Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators

Models of the hexagonally arrayed spatial activity pattern of grid cell firing in the literature generally fall into two main categories: continuous attractor models or oscillatory interference models. Burak and Fiete (2009, PLoS Comput Biol) recently examined noise in two continuous attractor models, but did not consider oscillatory interference models in detail. Here we analyze an oscillatory interference model to examine the effects of noise on its stability and spatial firing properties. We show analytically that the square of the drift in encoded position due to noise is proportional to time and inversely proportional to the number of oscillators. We also show there is a relatively fixed breakdown point, independent of many parameters of the model, past which noise overwhelms the spatial signal. Based on this result, we show that a pair of oscillators are expected to maintain a stable grid for approximately t = 5µ3/(4πσ)2 seconds where µ is the mean period of an oscillator in seconds and σ2 its variance in seconds2. We apply this criterion to recordings of individual persistent spiking neurons in postsubiculum (dorsal presubiculum) and layers III and V of entorhinal cortex, to subthreshold membrane potential oscillation recordings in layer II stellate cells of medial entorhinal cortex and to values from the literature regarding medial septum theta bursting cells. All oscillators examined have expected stability times far below those seen in experimental recordings of grid cells, suggesting the examined biological oscillators are unfit as a substrate for current implementations of oscillatory interference models. However, oscillatory interference models can tolerate small amounts of noise, suggesting the utility of circuit level effects which might reduce oscillator variability. Further implications for grid cell models are discussed

A perspective for advancing climate prediction services in Brazil

The Climate Science for Service Partnership Brazil (CSSP-Brazil) project provides Brazil and UK partners the opportunity to address important challenges faced by the climate modeling community, including the need to develop subseasonal and seasonal prediction and climate projection services. This paper provides an overview of the climate modeling and prediction research conducted through CSSP-Brazil within the context of a framework to advance climate prediction services in Brazil that includes a research-to-services (R2S) and a services-to-research (S2R) feedback pathway. The paper also highlights plans to advance scientific understanding and capability to produce beneficial climate knowledge and new products to improve climate prediction services to support decisions in various industries in Brazil. Policy-relevant outcomes from climate modeling and prediction exercises illustrated in this paper include supporting stakeholders with climate information provided from weeks to months ahead for (a) improving water management strategies for human consumption, navigation, and agricultural and electricity production; (b) defining crop variety and calendars for food production; and (c) diversifying energy production with alternatives to hydropower

Management of patients with advanced prostate cancer—metastatic and/or castration-resistant prostate cancer: report of the Advanced Prostate Cancer Consensus Conference (APCCC) 2022

Background: Innovations in imaging and molecular characterisation together with novel treatment options have improved outcomes in advanced prostate cancer. However, we still lack high-level evidence in many areas relevant to making management decisions in daily clinical practise. The 2022 Advanced Prostate Cancer Consensus Conference (APCCC 2022) addressed some questions in these areas to supplement guidelines that mostly are based on level 1 evidence. Objective: To present the voting results of the APCCC 2022. Design, setting, and participants: The experts voted on controversial questions where high- level evidence is mostly lacking: locally advanced prostate cancer; biochemical recurrence after local treatment; metastatic hormone-sensitive, non-metastatic, and metastatic castration- resistant prostate cancer; oligometastatic prostate cancer; and managing side effects of hormonal therapy. A panel of 105 international prostate cancer experts voted on the consensus questions. Outcome measurements and statistical analysis: The panel voted on 198 pre-defined questions, which were developed by 117 voting and non-voting panel members prior to the conference following a modified Delphi process. A total of 116 questions on metastatic and/or castration- resistant prostate cancer are discussed in this manuscript. In 2022, the voting was done by a web-based survey because of COVID-19 restrictions. Results and limitations: The voting reflects the expert opinion of these panellists and did not incorporate a standard literature review or formal meta-analysis. The answer options for the consensus questions received varying degrees of support from panellists, as reflected in this article and the detailed voting results are reported in the supplementary material. We report here on topics in metastatic, hormone-sensitive prostate cancer (mHSPC), non-metastatic, castration-resistant prostate cancer (nmCRPC), metastatic castration-resistant prostate cancer (mCRPC), and oligometastatic and oligoprogressive prostate cancer. Conclusions: These voting results in four specific areas from a panel of experts in advanced prostate cancer can help clinicians and patients navigate controversial areas of management for which high-level evidence is scant or conflicting and can help research funders and policy makers identify information gaps and consider what areas to explore further. However, diagnostic and treatment decisions always have to be individualised based on patient characteristics, including the extent and location of disease, prior treatment(s), co-morbidities, patient preferences, and treatment recommendations and should also incorporate current and emerging clinical evidence and logistic and economic factors. Enrolment in clinical trials is strongly encouraged. Importantly, APCCC 2022 once again identified important gaps where there is non-consensus and that merit evaluation in specifically designed trials. Patient summary: The Advanced Prostate Cancer Consensus Conference (APCCC) provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference aims to share the knowledge of international experts in prostate cancer with healthcare providers worldwide. At each APCCC, an expert panel votes on pre-defined questions that target the most clinically relevant areas of advanced prostate cancer treatment for which there are gaps in knowledge. The results of the voting provide a practical guide to help clinicians discuss therapeutic options with patients and their relatives as part of shared and multidisciplinary decision-making. This report focuses on the advanced setting, covering metastatic hormone-sensitive prostate cancer and both non-metastatic and metastatic castration-resistant prostate cancer. Twitter summary: Report of the results of APCCC 2022 for the following topics: mHSPC, nmCRPC, mCRPC, and oligometastatic prostate cancer. Take-home message: At APCCC 2022, clinically important questions in the management of advanced prostate cancer management were identified and discussed, and experts voted on pre-defined consensus questions. The report of the results for metastatic and/or castration- resistant prostate cancer is summarised here

Management of Patients with Advanced Prostate Cancer. Part I: Intermediate-/High-risk and Locally Advanced Disease, Biochemical Relapse, and Side Effects of Hormonal Treatment: Report of the Advanced Prostate Cancer Consensus Conference 2022.

BACKGROUND: Innovations in imaging and molecular characterisation and the evolution of new therapies have improved outcomes in advanced prostate cancer. Nonetheless, we continue to lack high-level evidence on a variety of clinical topics that greatly impact daily practice. To supplement evidence-based guidelines, the 2022 Advanced Prostate Cancer Consensus Conference (APCCC 2022) surveyed experts about key dilemmas in clinical management. OBJECTIVE: To present consensus voting results for select questions from APCCC 2022. DESIGN, SETTING, AND PARTICIPANTS: Before the conference, a panel of 117 international prostate cancer experts used a modified Delphi process to develop 198 multiple-choice consensus questions on (1) intermediate- and high-risk and locally advanced prostate cancer, (2) biochemical recurrence after local treatment, (3) side effects from hormonal therapies, (4) metastatic hormone-sensitive prostate cancer, (5) nonmetastatic castration-resistant prostate cancer, (6) metastatic castration-resistant prostate cancer, and (7) oligometastatic and oligoprogressive prostate cancer. Before the conference, these questions were administered via a web-based survey to the 105 physician panel members ("panellists") who directly engage in prostate cancer treatment decision-making. Herein, we present results for the 82 questions on topics 1-3. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Consensus was defined as ≥75% agreement, with strong consensus defined as ≥90% agreement. RESULTS AND LIMITATIONS: The voting results reveal varying degrees of consensus, as is discussed in this article and shown in the detailed results in the Supplementary material. The findings reflect the opinions of an international panel of experts and did not incorporate a formal literature review and meta-analysis. CONCLUSIONS: These voting results by a panel of international experts in advanced prostate cancer can help physicians and patients navigate controversial areas of clinical management for which high-level evidence is scant or conflicting. The findings can also help funders and policymakers prioritise areas for future research. Diagnostic and treatment decisions should always be individualised based on patient and cancer characteristics (disease extent and location, treatment history, comorbidities, and patient preferences) and should incorporate current and emerging clinical evidence, therapeutic guidelines, and logistic and economic factors. Enrolment in clinical trials is always strongly encouraged. Importantly, APCCC 2022 once again identified important gaps (areas of nonconsensus) that merit evaluation in specifically designed trials. PATIENT SUMMARY: The Advanced Prostate Cancer Consensus Conference (APCCC) provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference aims to share the knowledge of international experts in prostate cancer with health care providers and patients worldwide. At each APCCC, a panel of physician experts vote in response to multiple-choice questions about their clinical opinions and approaches to managing advanced prostate cancer. This report presents voting results for the subset of questions pertaining to intermediate- and high-risk and locally advanced prostate cancer, biochemical relapse after definitive treatment, advanced (next-generation) imaging, and management of side effects caused by hormonal therapies. The results provide a practical guide to help clinicians and patients discuss treatment options as part of shared multidisciplinary decision-making. The findings may be especially useful when there is little or no high-level evidence to guide treatment decisions

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate