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Agent Based & Hybrid Modeling for Health Researchers
By Nathaniel Osgood 510 days ago
The Agent-Based and Hybrid Modeling Bootcamp for Health Researchers is an intensive, hands-on tutorial that seeks to provide health science researchers with a systematic, practical and accessible introduction to agent-based and hybrid system science modeling for health and health care, using familiar language and concepts. This year's bootcamp will focus on agent-based modeling, but with a particular emphasis on insightful, practical and performant hybrids with System Dynamics modeling and discrete event modeling.
Using lectures and guided exercises, the tutorial will introduce a broad set of topics in agent-based and especially hybrid modeling, offer optional material for those seeking additional depth of coverage, and emphasize the complementary insights when agent-based and hybrid modeling is combined with traditional health sciences approaches. Course material is drawn from the instructor's semester-long interdisciplinary courses at MIT and the University of Saskatchewan, as well as previous bootcamps, including those hosted at UCLA, University of New South Wales, NCSU/UNC, Flinders University, Deakin University, and the Sax Institute. The optional final day of the bootcamp will give participants the opportunity to brainstorm with the instructor and teaching assistants concerning ideas for modeling projects, and to discuss concrete design and implementation strategies for those projects.
Session screencasts, diverse example models and case studies, interactive exercises, and custom-built tools to ease model insight and debugging will be made available for post-tutorial review. Optional tutorials will additionally be provided on programming concepts and skills required for intermediate and advanced agent-based and hybrid modeling for health insight.
NB: To help cover additional material, a separate "incubator" is being held so as to further leverage the extensive experience of the instructor and teaching assistants to provide ongoing advice, guidance, tips and direct assistance as participants build, explore and debug their own models addressing their research interests. Please write to the organizers to learn about the timing of that incubator.
Objectives and Audience
The bootcamp is designed to give a detailed, hands-on introduction to the application of agent-based and hybrid modeling to health decision making. The bootcamp is specifically designed for health researchers who have no background in modeling, but who are interested in applications of modeling in the health area. While the bootcamp will assume some familiarity with general terms from the health sciences, no background in computer programming or mathematics is required. The tutorial is also suitable for those researchers previously familiar with some form of modeling but who are seeking to develop skill in agent-based modeling conducted with the AnyLogic software package. Course material presented here has been refined from presentations over the past four years to students with a variety of health science and veterinary science backgrounds. The large majority of the tutorial will be focused on Agent-Based and Hybrid Modeling in AnyLogic, with a particular emphasis on practical, performant and insightful hybrid modeling. The bootcamp will especially ways in which such methods can be synergistically combined to yield greater insight, but will draw on the instructors decades-long experience in applying multiple systems science approaches to characterize the tradeoffs between multiple systems science approaches so the participants have the best sense as to their natural regions of application. The tutorial will emphasize the practical benefits extending from the use of system science methods, and how such methods can be used in conjunction with traditional techniques.
The primary objectives of the bootcamp are the following:
To provide hands-on expertise in building agent-based and hybrid-models in AnyLogic;
To provide participants a chance to plan implement their own articulated models with help by experienced modelers;
To convey an understanding of how agent-based and hybrid systems science models can be used together with traditional tools of the health sciences, including epidemiological and biostatistical methods, administrative data, systematic reviews and meta-analyses;
To provide participants access to sophisticated tools to assist with model analysis, understanding, debugging and management of the modeling process;
To link participants in with a modeling support network of practitioners at all stages of expertise;
To provide participants with a broad and evolving set of existing health and health care models and resources where they can secure further information.
Dr. Nathaniel D. Osgood
Dr. Nathaniel D. Osgood is a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan. His research is focused on providing cross-linked simulation, ubiquitous sensing, and machine learning tools to inform understanding of population health trends and health policy tradeoffs. His applications work has addressed challenges in the communicable, zoonotic, environmental, and chronic disease areas. Dr. Osgood is further the co-creator of two novel mobile sensor-based epidemiological monitoring systems, most recently the Google Android- and iPhone-based iEpi (now Ethica Health) mobile epidemiological monitoring systems. He has additionally contributed innovations to improve dynamic modeling quality and efficiency, introduced novel techniques hybridizing multiple simulation approaches and simulation models with decision analysis tools, and which leverage such models using data gathered from wireless epidemiological monitoring systems. Dr. Osgood has led many international courses in simulation modeling and health around the world, and his online videos on the subject attract thousands of views per month. Prior to joining the U of S faculty, he graduated from MIT with a PhD in Computer Science in 1999, served as a Senior Lecturer at MIT and worked for a number of years in a variety of academic, consulting and industry positions.
The course will be staffed with a broad set of graduate-level teaching assistants, who will provide assistance both during the tutorial sessions and during the open times and post-tutorial brainstorming sessions. To better address the questions of participants from a wide variety of backgrounds, the teaching assistants will be drawn from both health science and technical backgrounds.
The tutorial will employ a hands-on teaching style where participants will learn concepts while interactively exploring existing modeling software, model structure and model results. The instructor will use examples to highlight unique features of agentbased models, and the types of questions on which they offer particular advantage, and limitations of such models. Registered participants will be given access to examples prior to the tutorial, and will be provided usable working copies of AnyLogic for the duration of the tutorial.
Additional times will be set aside for experimenting with the modeling package, pursuing exercises, raising points for clarification, and brainstorming with modelers and TAs concerning possible modeling projects.
Tutorial Contents
The tutorial will consist of a set of plenary sessions covering in which the participants will build example models as guided by the instructor (and with a pool of teaching assistants circulating to assist). Such exercises aid the participant in exploring ways of applying the tool to investigate particular types of health issues, and building strengths in use of the platform. A large fraction of the event will be spent in sessions where participants will have opportunity to pursue their own modeling projects in teams or alone, or may opt to participate in parallel sessions covering more detailed or more technically demanding material.
Optional Additional Sessions
Additional background sections will be offered for practitioners interested in seeking broader background or deeper understanding of some modeling practices and supporting technologies. The particular set of sessions to be offered will depend on the balance student interest expressed in the candidate sessions. While we cannot guarantee that all topics listed below will be covered during the bootcamp, dedicated sessions will cover material of interest to participants in a prioritized fashion, and videos will be made available for those topics which could not be included within the bootcamp.
Motivation for systems science methods in general, and agent-based modeling in particular
Best practices for model building
Model performance
Common performance vulnerabilities
Measuring performance using profilers
Effective strategy for improving model performance
Helpful bits of Java for AnyLogic users who lack programming exposure but are interested in securing added flexibility when creating models, and deeper understanding of model plumbing.
Basic introduction to Java
Methods & functions
Classes & objects
Using code in external Java libraries
Capturing hierarchies of related agents or resources: Subtyping and subclassing
Simulating the flow and interaction of agents and resources in facilities: Discrete event modeling and visualization in AnyLogic
Discussion on use of agent-based models for study planning, including evaluation of robustness of study design or statistical measures.
Optional post-tutorial modelling brainstorm session
The instructor and teaching assistants will be available to participants for a day of modeling brainstorming. This session will provide participants a chance to integrate and assimilate teachings from the tutorial session, and discuss application to their area of interest.
By the conclusion of the tutorial, each participant will be provided with the following:
Models built by the participant during inclass exercises
Example models provided to participants
Models built by the participant with TA & instructor guidance
References to more extensive learning opportunities (full courses, articles, books and model libraries)
Guidance on accessing videos of course contents and related online material
Custombuilt tools to ease model insight and debugging
Why Systems Science?
Despite widespread progress in prolonging life over the past century, many illnesses continue to impose troublingly high health burdens. Recent decades have witnessed the emergence of dramatic new health challenges, including the rise of complex, multifactorial risk factors such as obesity, antibiotic and drug resistant pathogens, newly emerging infectious diseases that cross the animalhuman interface, gaping and rising health disparities, and the emergence of syndemics of interacting illnesses. Although there is widespread recognition of the urgency of identifying and promoting policies that address such health challenges, formulating effective policies is dauntingly complex. While traditional analytical tools can offer much insight into public health gaps, there are significant methodological challenges in using such tools alone to understand the etiology of such disparities, and their implication for policy. These challenges reflect, among other things, the wide variety of interacting factors playing out over the life of an individual (often in feedbacks reflecting reciprocal causality), the broad ranges of timescales involved, the multiple levels of causation and effect (e.g., physiological and psychological mechanisms within individuals, surrounding layers of social and institutional context), widespread heterogeneities, the presence of bidirectional, delayed, geneenvironment interactions, and discontinuous and timevarying causal interactions between factors within and between scales. Because of the interaction of diverse factors in shaping outcomes, there are also methodological challenges in using traditional approaches unassisted to identify effective, robust and cost effective ways to decrease the burden of illness. These interactions operate through many pathways, including immunologic, psychosocial, mental health, nutrition, and through the health care system. Studying such complex linkages purely using one methodology or tool is challenging and, all too often, ineffective. In recent years, a growing number of researchers in public health have addressed similar challenges by complementing traditional techniques with dynamic modeling approaches, such as AgentBased Modeling, microsimulation, System Dynamics, and dynamic social network analysis. Such studies have shed much light on the interconnections between diverse causal factors, helped inform policy tradeoffs, interpret epidemiological trends, and prioritize data collection. Such models also serve as potent "learning prostheses" to enable us to learn more quickly, deeply, and robustly from the evidence available.
Why Agent-Based Modelling?
AgentBased Modeling approaches serve as a particularly popular Systems Science technique due to a number of characteristics. Their capacity to capture heterogeneity  both continuous and discrete  at an individual and higher level; such heterogeneity often disproportionately shapes dynamics, and plays a central role in formulating targeted interventions, and is of central importance in understanding health equity concerns, and in formulating interventions that reduce health disparities. Secondly, by characterizing individual trajectories, agentbased models support a life course perspective (permitting, for example, capturing the effects of early life exposures on later life outcomes), as well as interventions depending on such history. Both of these previous considerations further allow for grounding the model using longitudinal data in a way that is not possible using the aggregate perspective of crosssectional models. Thirdly, such models confer great value for their ability to capture aspects of context. This includes spatial/geographic location of agents  key for understanding, among other considerations, accessibility to resources such as grocery stores offering healthy foods, health care and allied health professional services facilities, walkable built environment, recreational resources, and for investigation of the impact of detailed interventions, such as those involving placement of resources. For many models, capturing context with respect to one or more networks (social networks, sexual networks, familial networks, needle-sharing networks, service networks) is further of great interest, given the role that these networks play in shaping, for example, spread of knowledge, attitudes, beliefs, norms, and innovations.
Reflecting the impacts of such context on choice sets and preferences, AgentBased models further offer a strong support for capturing aspects of situated individual decision making. Fourthly, the capacity of such models to represent factors at multiple scales  not just at an individual level, but also, for example, family, neighbourhood and region  confers strong support for multilevel health analysis, and understanding the effects of portfolios of interventions that operate at or employ information at such different levels. Finally, the individualbased characterization supported by AgentBased models often provides key support for securing buyin from stakeholders who can contribute expertise and evidence speaking to that level of representation, and for whom an individuallevel representation will secure additional degrees of buyin and credibility.
Why Hybrid Modelling?
While each Systems Science technique approach can confer great value when applied in isolation, there are significant, textured and varied tradeoffs that obtain between the methods when applying dynamic modeling approaches to particular problems. Associated considerations – which run the gamut from the capacity to capture longitudinal data, represent situated and localized decisionmaking, representing aspects network, spatial or multilevel context to communication barriers with stakeholders to performance challenges to human resource and skill sets – mean that the modeling approach best suited to characterizing one component of a system is sometimes poorly suited to others. Attempting to forcefit a single modeling approach onto the modeling effort can lead to diverse adverse outcomes, including – but not limited to – inability to investigate important issues of interest, difficulty in adequately characterizing intervention strategies, and models that are inflexible, or opaque and alienating to stakeholders. Within recent years, advances in modeling technology have opened the door to far more ready creation of hybrid and multiscale models. In successive problems in diverse domains, such models offer greater capacity to respond to modeler intention, and capable of more precisely addressing research questions involved, as well as more adaptive to changes in modeling priorities and scope in light of modelrelated learning, easier to understand and communicate, and more flexible and versatile. In many models, the hybrid approach supports understanding in excess of what would be gained with independent and parallel pursuit of modeling in each distinct modeling approach, and sometimes likely greater than the sum of the insights that could be secured collectively from several singleapproach investigations.
Supported by a series of handson case studies of hybrid and multiscale modeling in health and healthspecific training examples, this event focuses on practical application of hybrid and multiscale modeling and the criteria used to select among modeling types. Case studies will support participants in exploring and interacting with diverse health models that combine AgentBased, System Dynamics and Discrete Event modeling, including  but not limited to  use of agents some of whose states are driven by System Dynamics stocks & flows, System Dynamics models that from which agents are individuated at a certain point in risk progression or where interacting agents drive flow rates, agentbased epidemiological models linked to discrete event models capturing patient care pathways and patient flow, multiscale models, and case studies combining all three types of modeling. Emphasis will be placed on ensuring that participants can understand adapt the mechanisms in such models to their own circumstances. In addition to hybrid and multiscale models, we will further examine how multiple modeling methods can be fruitfully combined in the same modeling project to yield ongoing insight.
Prospective students seeking to better understand bootcamp coverage or registered students seeking to gain early exposure to material are recommended to view materials from the instructor's recent courses (http://www.tinyurl.com/ConsensusABM).
Introductory Course for Systems Science in Health
Agent-based models
Hybrid Models
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19/08/2019 18:00:00 24/08/2019 19:00:00 Agent Based & Hybrid Modeling for Health Researchers The Agent-Based and Hybrid Modeling Bootcamp for Health Researchers is an intensive, hands-on tutorial that seeks to provide health science researchers with a systematic, practical and accessible introduction to agent-based and hybrid system science modeling for health and health care, using familiar language and concepts. This year's bootcamp will focus on agent-based modeling, but with a particular emphasis on insightful, practical and performant hybrids with System Dynamics modeling and discrete event modeling. Using lectures and guided exercises, the tutorial will introduce a broad set of topics in agent-based and especially hybrid modeling, offer optional material for those seeking additional depth of coverage, and emphasize the complementary insights when agent-based and hybrid modeling is combined with traditional health sciences approaches. Course material is drawn from the instructor's semester-long interdisciplinary courses at MIT and the University of Saskatchewan, as well as previous bootcamps, including those hosted at UCLA, University of New South Wales, NCSU/UNC, Flinders University, Deakin University, and the Sax Institute. The optional final day of the bootcamp will give participants the opportunity to brainstorm with the instructor and teaching assistants concerning ideas for modeling projects, and to discuss concrete design and implementation strategies for those projects. Session screencasts, diverse example models and case studies, interactive exercises, and custom-built tools to ease model insight and debugging will be made available for post-tutorial review. Optional tutorials will additionally be provided on programming concepts and skills required for intermediate and advanced agent-based and hybrid modeling for health insight. NB: To help cover additional material, a separate "incubator" is being held so as to further leverage the extensive experience of the instructor and teaching assistants to provide ongoing advice, guidance, tips and direct assistance as participants build, explore and debug their own models addressing their research interests. Please write to the organizers to learn about the timing of that incubator. Objectives and Audience The bootcamp is designed to give a detailed, hands-on introduction to the application of agent-based and hybrid modeling to health decision making. The bootcamp is specifically designed for health researchers who have no background in modeling, but who are interested in applications of modeling in the health area. While the bootcamp will assume some familiarity with general terms from the health sciences, no background in computer programming or mathematics is required. The tutorial is also suitable for those researchers previously familiar with some form of modeling but who are seeking to develop skill in agent-based modeling conducted with the AnyLogic software package. Course material presented here has been refined from presentations over the past four years to students with a variety of health science and veterinary science backgrounds. The large majority of the tutorial will be focused on Agent-Based and Hybrid Modeling in AnyLogic, with a particular emphasis on practical, performant and insightful hybrid modeling. The bootcamp will especially ways in which such methods can be synergistically combined to yield greater insight, but will draw on the instructors decades-long experience in applying multiple systems science approaches to characterize the tradeoffs between multiple systems science approaches so the participants have the best sense as to their natural regions of application. The tutorial will emphasize the practical benefits extending from the use of system science methods, and how such methods can be used in conjunction with traditional techniques. The primary objectives of the bootcamp are the following: To provide hands-on expertise in building agent-based and hybrid-models in AnyLogic; To provide participants a chance to plan implement their own articulated models with help by experienced modelers; To convey an understanding of how agent-based and hybrid systems science models can be used together with traditional tools of the health sciences, including epidemiological and biostatistical methods, administrative data, systematic reviews and meta-analyses; To provide participants access to sophisticated tools to assist with model analysis, understanding, debugging and management of the modeling process; To link participants in with a modeling support network of practitioners at all stages of expertise; To provide participants with a broad and evolving set of existing health and health care models and resources where they can secure further information. Instructor Dr. Nathaniel D. Osgood Dr. Nathaniel D. Osgood is a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan. His research is focused on providing cross-linked simulation, ubiquitous sensing, and machine learning tools to inform understanding of population health trends and health policy tradeoffs. His applications work has addressed challenges in the communicable, zoonotic, environmental, and chronic disease areas. Dr. Osgood is further the co-creator of two novel mobile sensor-based epidemiological monitoring systems, most recently the Google Android- and iPhone-based iEpi (now Ethica Health) mobile epidemiological monitoring systems. He has additionally contributed innovations to improve dynamic modeling quality and efficiency, introduced novel techniques hybridizing multiple simulation approaches and simulation models with decision analysis tools, and which leverage such models using data gathered from wireless epidemiological monitoring systems. Dr. Osgood has led many international courses in simulation modeling and health around the world, and his online videos on the subject attract thousands of views per month. Prior to joining the U of S faculty, he graduated from MIT with a PhD in Computer Science in 1999, served as a Senior Lecturer at MIT and worked for a number of years in a variety of academic, consulting and industry positions. Teaching Assistants The course will be staffed with a broad set of graduate-level teaching assistants, who will provide assistance both during the tutorial sessions and during the open times and post-tutorial brainstorming sessions. To better address the questions of participants from a wide variety of backgrounds, the teaching assistants will be drawn from both health science and technical backgrounds. Teaching Style The tutorial will employ a hands-on teaching style where participants will learn concepts while interactively exploring existing modeling software, model structure and model results. The instructor will use examples to highlight unique features of agentbased models, and the types of questions on which they offer particular advantage, and limitations of such models. Registered participants will be given access to examples prior to the tutorial, and will be provided usable working copies of AnyLogic for the duration of the tutorial. Additional times will be set aside for experimenting with the modeling package, pursuing exercises, raising points for clarification, and brainstorming with modelers and TAs concerning possible modeling projects. Tutorial Contents The tutorial will consist of a set of plenary sessions covering in which the participants will build example models as guided by the instructor (and with a pool of teaching assistants circulating to assist). Such exercises aid the participant in exploring ways of applying the tool to investigate particular types of health issues, and building strengths in use of the platform. A large fraction of the event will be spent in sessions where participants will have opportunity to pursue their own modeling projects in teams or alone, or may opt to participate in parallel sessions covering more detailed or more technically demanding material. Optional Additional Sessions Additional background sections will be offered for practitioners interested in seeking broader background or deeper understanding of some modeling practices and supporting technologies. The particular set of sessions to be offered will depend on the balance student interest expressed in the candidate sessions. While we cannot guarantee that all topics listed below will be covered during the bootcamp, dedicated sessions will cover material of interest to participants in a prioritized fashion, and videos will be made available for those topics which could not be included within the bootcamp. Motivation for systems science methods in general, and agent-based modeling in particular Best practices for model building Model performance Common performance vulnerabilities Measuring performance using profilers Effective strategy for improving model performance Helpful bits of Java for AnyLogic users who lack programming exposure but are interested in securing added flexibility when creating models, and deeper understanding of model plumbing. Basic introduction to Java Methods & functions Classes & objects Events Types Expressions Statements Using code in external Java libraries Capturing hierarchies of related agents or resources: Subtyping and subclassing Simulating the flow and interaction of agents and resources in facilities: Discrete event modeling and visualization in AnyLogic Discussion on use of agent-based models for study planning, including evaluation of robustness of study design or statistical measures. Optional post-tutorial modelling brainstorm session The instructor and teaching assistants will be available to participants for a day of modeling brainstorming. This session will provide participants a chance to integrate and assimilate teachings from the tutorial session, and discuss application to their area of interest. Deliverables By the conclusion of the tutorial, each participant will be provided with the following: Slides Exercises Models built by the participant during inclass exercises Example models provided to participants Models built by the participant with TA & instructor guidance References to more extensive learning opportunities (full courses, articles, books and model libraries) Guidance on accessing videos of course contents and related online material Custombuilt tools to ease model insight and debugging Motivations Why Systems Science? Despite widespread progress in prolonging life over the past century, many illnesses continue to impose troublingly high health burdens. Recent decades have witnessed the emergence of dramatic new health challenges, including the rise of complex, multifactorial risk factors such as obesity, antibiotic and drug resistant pathogens, newly emerging infectious diseases that cross the animalhuman interface, gaping and rising health disparities, and the emergence of syndemics of interacting illnesses. Although there is widespread recognition of the urgency of identifying and promoting policies that address such health challenges, formulating effective policies is dauntingly complex. While traditional analytical tools can offer much insight into public health gaps, there are significant methodological challenges in using such tools alone to understand the etiology of such disparities, and their implication for policy. These challenges reflect, among other things, the wide variety of interacting factors playing out over the life of an individual (often in feedbacks reflecting reciprocal causality), the broad ranges of timescales involved, the multiple levels of causation and effect (e.g., physiological and psychological mechanisms within individuals, surrounding layers of social and institutional context), widespread heterogeneities, the presence of bidirectional, delayed, geneenvironment interactions, and discontinuous and timevarying causal interactions between factors within and between scales. Because of the interaction of diverse factors in shaping outcomes, there are also methodological challenges in using traditional approaches unassisted to identify effective, robust and cost effective ways to decrease the burden of illness. These interactions operate through many pathways, including immunologic, psychosocial, mental health, nutrition, and through the health care system. Studying such complex linkages purely using one methodology or tool is challenging and, all too often, ineffective. In recent years, a growing number of researchers in public health have addressed similar challenges by complementing traditional techniques with dynamic modeling approaches, such as AgentBased Modeling, microsimulation, System Dynamics, and dynamic social network analysis. Such studies have shed much light on the interconnections between diverse causal factors, helped inform policy tradeoffs, interpret epidemiological trends, and prioritize data collection. Such models also serve as potent "learning prostheses" to enable us to learn more quickly, deeply, and robustly from the evidence available. Why Agent-Based Modelling? AgentBased Modeling approaches serve as a particularly popular Systems Science technique due to a number of characteristics. Their capacity to capture heterogeneity  both continuous and discrete  at an individual and higher level; such heterogeneity often disproportionately shapes dynamics, and plays a central role in formulating targeted interventions, and is of central importance in understanding health equity concerns, and in formulating interventions that reduce health disparities. Secondly, by characterizing individual trajectories, agentbased models support a life course perspective (permitting, for example, capturing the effects of early life exposures on later life outcomes), as well as interventions depending on such history. Both of these previous considerations further allow for grounding the model using longitudinal data in a way that is not possible using the aggregate perspective of crosssectional models. Thirdly, such models confer great value for their ability to capture aspects of context. This includes spatial/geographic location of agents  key for understanding, among other considerations, accessibility to resources such as grocery stores offering healthy foods, health care and allied health professional services facilities, walkable built environment, recreational resources, and for investigation of the impact of detailed interventions, such as those involving placement of resources. For many models, capturing context with respect to one or more networks (social networks, sexual networks, familial networks, needle-sharing networks, service networks) is further of great interest, given the role that these networks play in shaping, for example, spread of knowledge, attitudes, beliefs, norms, and innovations. Reflecting the impacts of such context on choice sets and preferences, AgentBased models further offer a strong support for capturing aspects of situated individual decision making. Fourthly, the capacity of such models to represent factors at multiple scales  not just at an individual level, but also, for example, family, neighbourhood and region  confers strong support for multilevel health analysis, and understanding the effects of portfolios of interventions that operate at or employ information at such different levels. Finally, the individualbased characterization supported by AgentBased models often provides key support for securing buyin from stakeholders who can contribute expertise and evidence speaking to that level of representation, and for whom an individuallevel representation will secure additional degrees of buyin and credibility. Why Hybrid Modelling? While each Systems Science technique approach can confer great value when applied in isolation, there are significant, textured and varied tradeoffs that obtain between the methods when applying dynamic modeling approaches to particular problems. Associated considerations – which run the gamut from the capacity to capture longitudinal data, represent situated and localized decisionmaking, representing aspects network, spatial or multilevel context to communication barriers with stakeholders to performance challenges to human resource and skill sets – mean that the modeling approach best suited to characterizing one component of a system is sometimes poorly suited to others. Attempting to forcefit a single modeling approach onto the modeling effort can lead to diverse adverse outcomes, including – but not limited to – inability to investigate important issues of interest, difficulty in adequately characterizing intervention strategies, and models that are inflexible, or opaque and alienating to stakeholders. Within recent years, advances in modeling technology have opened the door to far more ready creation of hybrid and multiscale models. In successive problems in diverse domains, such models offer greater capacity to respond to modeler intention, and capable of more precisely addressing research questions involved, as well as more adaptive to changes in modeling priorities and scope in light of modelrelated learning, easier to understand and communicate, and more flexible and versatile. In many models, the hybrid approach supports understanding in excess of what would be gained with independent and parallel pursuit of modeling in each distinct modeling approach, and sometimes likely greater than the sum of the insights that could be secured collectively from several singleapproach investigations. Supported by a series of handson case studies of hybrid and multiscale modeling in health and healthspecific training examples, this event focuses on practical application of hybrid and multiscale modeling and the criteria used to select among modeling types. Case studies will support participants in exploring and interacting with diverse health models that combine AgentBased, System Dynamics and Discrete Event modeling, including  but not limited to  use of agents some of whose states are driven by System Dynamics stocks & flows, System Dynamics models that from which agents are individuated at a certain point in risk progression or where interacting agents drive flow rates, agentbased epidemiological models linked to discrete event models capturing patient care pathways and patient flow, multiscale models, and case studies combining all three types of modeling. Emphasis will be placed on ensuring that participants can understand adapt the mechanisms in such models to their own circumstances. In addition to hybrid and multiscale models, we will further examine how multiple modeling methods can be fruitfully combined in the same modeling project to yield ongoing insight. Additional Resources Prospective students seeking to better understand bootcamp coverage or registered students seeking to gain early exposure to material are recommended to view materials from the instructor's recent courses (http://www.tinyurl.com/ConsensusABM). DD/MM/YYYY
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http://tinyurl.com/ABMBootcamp2019Materials


As a Stampin' Up! demonstrator, I receive a monthly magazine that's full of creative ideas. In this month's issue, I saw the typewriter from the "You're My Type" stamp set available in the Occasions Mini Catalog. The more I see this set, the more I fall in love with it. It's just so dang clever.
"You're My Type" stamp set offers a bold typewriter stamp that can "roll" vintage or modern. The sentiments are both charming and versatile for many occasions. This is my spin on a card I CASED (copied or inspiration) from another demonstrator named Mary.
Coverage can be tricky with a large solid stamp like the typewriter. Use a Blender Pen and ink to touch up any areas where ink doesn't transfer perfectly. Layer a bit at a time as you fill in.
Each strip of Sweet Shop Specialty Designer Series Paper was cut to 1 1/4″ x 5 1/4″.
I used a Circle Scissor Plus and Glass Mat to create the large circles. Whisper White diameter 3 1/4″. Riding Hood Red diameter 3 1/2″.
Tie things up with Island Indigo Baker's Twine (CONFESSION – I love baker's twine).
NEED FREE COPIES OF THE OCCASIONS MINI AND SALE-A-BRATION CATALOGS and don't have a relationship with another Stampin' Up! Demonstrator? Please email me your name and U.S. address. I'll send them to you as soon as they are available for distribution.


text:
Difference between revisions of "Portland Afoot"
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(→Description: tagify Oregon and bicycle. - category:Boilerplates)
Latest revision as of 02:13, 7 March 2014 (edit) (undo)
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(→Description: tag Portland)
Portland Afoot is two things:
* A four-page monthly newsmagazine about low-car life in Portland, {{tag|Oregon}}.
* A four-page monthly newsmagazine about low-car life in {{tag|Portland}}, {{tag|Oregon}}.
* An editable online guide to low-car life in Portland
Portland Afoot
OpenEdit
Wiki license:
"Creative Commons" is not in the list of possible values (NoLicense, MultiLicense, Custom license, Attribution to contributing authors, Copyright to contributing authors, Site retains copyright, Public Domain (generic), WTFPL, Licence Art Libre, Open Content License, Apache License, BSD Documentation License, FreeBSD Documentation License, GNU Free Documentation License, GNU General Public License, GNU Lesser General Public License, Creative Commons Public Domain, Creative Commons Public Domain Dedication (CC0), Creative Commons Attribution, Creative Commons Attribution-No Derivative Works, Creative Commons Attribution-Share Alike, Creative Commons Attribution Non-Commercial Share Alike, Proprietary license, Creative Commons Attribution-NonCommercial, Creative Commons ShareAlike, Creative Commons Attribution-NonCommercial-NoDerivatives) for this property.
A four-page monthly newsmagazine about low-car life in Portland, Oregon.
An editable online guide to low-car life in Portland
We cover TriMet, the city, and the culture of the low-car lifestyle from the perspective of the people who live it.
We tell you about the best local car-free camping trips. We tell you when bus fare is going up, why, and what you can do about it. We tell you which seats on the MAX are best for talking on a cell phone, stowing a suitcase or firing up a laptop.
The website itself is totally different but equally awesome: It's a constantly updated guide to low-car life that anyone can improve. That's where you'll find pages on every bus line and its on-time records, plans for new rail lines through your neighborhood and the hours of every bicycle shop in town. It's for the information you need in a pinch but can't find anywhere else.
Our print edition sells for $14 a year; it's also available by email, if you prefer. And the website, of course, is free.
Retrieved from "https://wikiindex.org/index.php?title=Portland_Afoot&oldid=175807"
Wiki Creative Commons
LowCarLifeInPortlandOregon

redpajama_set_name: RedPajamaCommonCrawl


Lakbay Aral Espesyal!: Khana, Chalo! Let's Eat!
As a continuation to my India travel posts, I'd like to share to you some of the local cuisine that I tried when I was in Pune. Though I wasn't that adventurous, I was able to have a taste of some local delicacies thanks to my trainees' persistence. LOL!
Biryani is one of my most favorite (and frequently eaten!) food in Pune. Made up of basmati rice, chicken or mutton (lamb), and a lot of spices. Yes, A LOT. I don't know what spices do they put in it, but it was damn delicious! Interesting to know that the meat and the rice are cooked at the same time in the same container. Neat!
It is often served with a sauce, chili, slices of red onion, and a quarter of lemon. I was surprised the first time I bought one, because they won't give you any utensils; you need to eat it with your bare hands. Kamayan style anyone?
If biryani is my favorite dish, malai pedha is my favorite sweet. I was hesitant to taste it at first, thinking that all foods in India are spiced, even desserts! But once you sink your teeth in this milk-based treat, I bet, one box won't be enough.
This delicacy (also called milk fudge) is made up of milk, sugar, cardamom seeds, saffron, and pistachios or almonds on top. It's very much like our pastillas, but a bit savory and much creamy. The first pedha was actually made 175 years ago!
Chili chicken, fried rice, and Kulfi. Bahut accha!
Thinking of it at first as tokwa, paneer is actually cottage cheese made from curdling milk with vinegar or lemon. Tastes like tofu, but milder. It is sometimes used as meat replacement, and is a staple among non-veg dishes. By the way, meals in India are classified as veg, or non-veg.
I was able to get hold of these weird looking empty shells on my last few days in India. I wasn't interested at first, but my trainees insisted. And it was quite an experience I'll never forget. Much like eating a bomb loaded with a concoction of tamarind juice, peas, potato, and chili, it will literally burst in your mouth! I was given a serving, little did I know that one serving is equal to 8 shells!
It might not be a native dish in India, but it's only found in India. Folks, I had an encounter with Big Mac's brother: the Maharajah Mac.
Crisp veggies, tasty patty. Attack!
Due to India's reverence to cows, burgers are made up of chicken (and paneer, I think). Out of curiosity, I ordered one when we went McDonald's (which they fondly call McD.) I loved the taste, specially with the fresh and crunchy vegetables that goes with it.
Most of my friends ask, "Have you tasted chicken curry in India?"
ewan ko ba malou, naguguluhan ako sa roti, bhatoora, chapati. nga pala di ko naisama dito! tsk! but there's something unique about indian flatbreads. sobrang malasa. and you can eat it with anything!


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text:
"A little bit of wee came out": How to cope with exercise-induced bladder leakage
By Kimberly Gillan| 4 years ago
Ballistic, intense exercises can push harder on your bladder than you think. (Image: iStock)
One in three Australian women experience it, no matter what their age is.
We'd like to think that we could reserve bladder leakage for old age, but research shows one in three Australian women have experienced incontinence – with many suffering it before the age of 30.
For some, that involves "urge incontinence" where you suddenly need to pee but don't make it in time, but for the majority it's "stress incontinence" where you accidentally leak urine when sneezing or coughing.
For women with this issue, certain exercises, such as skipping, jumping or trampolining become no-go activities lest they get a wet patch on their pants.
It's generally a result of a weak pelvic floor, which is the band of muscles that form the base of the pelvis and support the bladder, bowels, vagina and rectum.
"There's an increase in your intra-abdominal pressure and that pushes on your bladder and if your pelvic floor muscles aren't strong enough at the opening of the vagina, then the urine is going to leak out," women's health physiotherapist Holly Brasher told Coach.
"Jumping up and down or running or even lifting weights is going to put pressure on your bladder."
Why some women get it
Brasher says that childbirth is a big risk factor for incontinence problems but some people have a naturally weak pelvic floor and can suffer it without having experienced childbirth, or a caesarean section for that matter.
"Pregnancy, childbirth, having more than one baby, using instruments in childbirth or having a chronic cough can all put you at greater risk," Brasher says.
There are also believed to be hormonal factors at play, and studies suggest that taking the oral contraceptive pill reduces a woman's chance of being incontinent by 50 percent.
"There are a lot of oestrogen receptors in the bladder wall and the bladder neck," Professor Susan Davis from Monash University told ABC.
"One theory is that the high level of oestrogen that comes with taking the pill may be improving bladder function – but quite honestly we don't know."
RELATED: Pelvic floor 101: Why it's the next big thing in fitness
Don't stay in silence
The good news is that in most cases, doing pelvic floor exercises can make a significant difference to the likelihood of bladder leakage.
"Only about 30 percent of women with urinary incontinence seek help, which is sad because in most cases it can be fixed pretty easily – it's nothing to be ashamed of," Brasher explains.
To feel your pelvic floor muscles, sit on a hard stool with your legs spread. Sit straight, relax your lower stomach muscles completely then bring in your lower tummy, urethra and anus so you feel a lift and squeeze but not a pushing down.
Pelvic floor exercises involve repeating this motion for 10 slow squeezes and 10 fast squeezes four to five times each day.
It's always good to see a women's health physio who can make sure you're doing the exercises correctly.
"Doing them wrong can make it worse or not make a difference at all because you're using the wrong muscles," Brasher says
"As with any muscle-strengthening program, it's going to take a minimum or six to 12 weeks [to take effect]."
How to deal in the time being
While you're waiting for your pelvic floor muscles to strengthen, Brasher suggests emptying your bladder before exercising to reduce your risk of bladder leakage.
"Low impact exercise is always going to be better," she says.
"Walking or cycling or low-impact gym classes and avoiding really heavy weights can help."
Wearing a pad when you're exercising is another no-brainer.
"If it's going to keep you exercising and socialising and busy, that's great," Brasher says.
It's also a good idea not to go to the toilet "just in case" because your bladder will adapt to holding less urine. Waiting until you really need to go will help strengthen your bladder muscles.
RELATED: Kayla Itsines' pelvic floor workout for new mums
Auto News: Skoda sales hit 1.24 million in 2019 - caradvice.com.au


text:
Q: Using Math.sqrt() instead of d3.scaleSqrt() for sizing circles on map? I am building a map where circles appended to cities on a US map are sized based upon a value in the CSV (guns column or d.guns in the JavaScript).
I was able to get the circles to resize using Math.sqrt() while appending the circles, but I do not think this is the right way to do it (or is it fine?):
.attr('r', function(d) {
  return Math.sqrt(d.guns * 0.0010);
})

I attempted to use the d3.scaleSqrt() and d3.extent to resize the circles based upon the values, but I was thrown these errors in the console:

Here is the code when I attempted using d3.scaleSqrt:
<head>
  <script>
    function draw(geo_data) {
      'use strict';

      var margin = 75,
        width = 1920 - margin,
        height = 1080 - margin;

      var svg = d3.select('body')
        .append('svg')
        .attr('width', width + margin)
        .attr('height', height + margin)
        .append('g')
        .attr('class', 'map');

      var projection = d3.geoAlbersUsa();

      var path = d3.geoPath().projection(projection);

      var map = svg.selectAll('path')
        .data(geo_data.features)
        .enter()
        .append('path')
        .attr('d', path)
        .style('fill', 'rgba(253, 227, 167, 0.8)')
        .style('stroke', 'black')
        .style('stroke-width', 0.4);

      d3.csv('top100cities.csv', function(error, data) {
    // Converts strings to integers.

    data.forEach(function(d) {
      return d.guns = +d.guns;
    })
        var guns_extent = d3.extent(function(d) {
          return d.guns;
        });

        var radius = d3.scaleSqrt()
          .domain(guns_extent)
          .range([0, 12]);

        svg.append('g')
          .attr('class', 'bubble')
          .selectAll('circle')
          .data(data)
          .enter()
          .append('circle')
          .attr('cx', function(d) {
            return projection([d.lon, d.lat])[0];
          })
          .attr('cy', function(d) {
            return projection([d.lon, d.lat])[1];
          })
          .attr('r', function(d) {
            return radius(d.guns);
          })
          .style('fill', 'rgba(103, 65, 114, 0.5)');

      });

    };
</script>

<body>
<script>
d3.json('us_states.json', draw);
</script>
</body>

A: Although Xavier Guihot's answer is technically correct and proposes a working solution it slightly deviates from the D3 track. The error in your code was caused by not providing all parameters to d3.extent(); you simply forgot to pass in the array, namely data, from which to determine the extent (emphasis mine):

# d3.extent(array[, accessor]) <>
Returns the minimum and maximum value in the given array using natural order. Providing both, the array as well as the accessor, your code would look like this:

var guns_extent = d3.extent(data, function(d) {   // Pass in data as first parameter
  return d.guns;
});

Below is the working demo:

function draw(geo_data) {
  'use strict';

  var margin = 75,
    width = 1920 - margin,
    height = 1080 - margin;

  var svg = d3.select('body')
    .append('svg')
    .attr('width', width + margin)
    .attr('height', height + margin)
    .append('g')
    .attr('class', 'map');

  var projection = d3.geoAlbersUsa();

  var path = d3.geoPath().projection(projection);

  var map = svg.selectAll('path')
    .data(geo_data.features)
    .enter()
    .append('path')
    .attr('d', path)
    .style('fill', 'rgba(253, 227, 167, 0.8)')
    .style('stroke', 'black')
    .style('stroke-width', 0.4);

  d3.csv("https://raw.githubusercontent.com/dieterholger/US-Gun-Manufacturing-Interactive/master/top100cities.csv", function(error, data) {
    // Converts strings to integers.

    data.forEach(function(d) {
      return d.guns = +d.guns;
    })
    var guns_extent = d3.extent(data, function(d) {   // Pass in data
      return d.guns;
    });

    var radius = d3.scaleSqrt()
      .domain(guns_extent)
      .range([0, 12]);

    svg.append('g')
      .attr('class', 'bubble')
      .selectAll('circle')
      .data(data)
      .enter()
      .append('circle')
      .attr('cx', function(d) {
        return projection([d.lon, d.lat])[0];
      })
      .attr('cy', function(d) {
        return projection([d.lon, d.lat])[1];
      })
      .attr('r', function(d) {
        return radius(d.guns);
      })
      .style('fill', 'rgba(103, 65, 114, 0.5)');

  });

};

d3.json('https://raw.githubusercontent.com/dieterholger/US-Gun-Manufacturing-Interactive/master/us_states.json', draw);
<script src="https://d3js.org/d3.v4.js"></script>

A: The error, I think, was in the retrieval of the max number of guns.
Here is the diff:
let guns = data.map( function(d) { return d.guns });
console.log(Math.max(...guns));

var radius = d3.scaleSqrt().domain([0, Math.max(...guns)]).range([0, 25]);

Here is the modified demo:

<head>
  <script>
    function draw(geo_data) {
      'use strict';

      var margin = 75,
        width = 1920 - margin,
        height = 1080 - margin;

      var svg = d3.select('body')
        .append('svg')
        .attr('width', width + margin)
        .attr('height', height + margin)
        .append('g')
        .attr('class', 'map');

      var projection = d3.geoAlbersUsa();

      var path = d3.geoPath().projection(projection);

      var map = svg.selectAll('path')
        .data(geo_data.features)
        .enter()
        .append('path')
        .attr('d', path)
        .style('fill', 'rgba(253, 227, 167, 0.8)')
        .style('stroke', 'black')
        .style('stroke-width', 0.4);

  d3.csv('https://raw.githubusercontent.com/dieterholger/US-Gun-Manufacturing-Interactive/master/top100cities.csv', function(error, data) {

    let guns = data.map( function(d) { return d.guns });
    console.log(Math.max(...guns));

    var radius = d3.scaleSqrt().domain([0, Math.max(...guns)]).range([0, 25]);

    svg.append('g')
      .attr('class', 'bubble')
      .selectAll('circle')
      .data(data)
      .enter()
      .append('circle')
      .attr('cx', function(d) {
        return projection([d.lon, d.lat])[0];
      })
      .attr('cy', function(d) {
        return projection([d.lon, d.lat])[1];
      })
      .attr('r', function(d) {
        return radius(d.guns);
      })
      .style('fill', 'rgba(103, 65, 114, 0.5)');

      });

    };
</script>

<body>
<script src="https://d3js.org/d3.v4.min.js"></script>
<script>
d3.json('https://raw.githubusercontent.com/dieterholger/US-Gun-Manufacturing-Interactive/master/us_states.json', draw);
</script>
</body>

A: Setting up the formula for the area of a circle could work.
The formula is A=πr2, where A equals the area of the circle, r equals the radius.
if A = d.guns
We know Area and π
then:
r = √(d.guns/π)
.attr("r", function (d) {return Math.sqrt(d.guns/3.1416);})
https://www.wikihow.com/Calculate-the-Radius-of-a-Circle#/Image:Calculate-the-Radius-of-a-Circle-Step-10-Version-4.jpg

redpajama_set_name: RedPajamaStackExchange


text:
Multi-agent based middleware for protecting privacy in IPTV content recommender services
Ahmed Elmesiry, Dmitri Botvich
This work presents our efforts to design an agent based middleware that enables the end-users to use IPTV content recommender services without revealing their sensitive preference data to the service provider or any third party involved in this process. The proposed middleware (called AMPR) preserves users' privacy when using the recommender service and permits private sharing of data among different users in the network. The proposed solution relies on a distributed multi-agent architecture involving local agents running on the end-user set up box to implement a two stage concealment process based on user role in order to conceal the local preference data of end-users when they decide to participate in recommendation process. Moreover, AMPR allows the end-users to use P3P policies exchange language (APPEL) for specifying their privacy preferences for the data extracted from their profiles, while the recommender service uses platform for privacy preferences (P3P) policies for specifying their data usage practices. AMPR executes the first stage locally at the end user side but the second stage is done at remote nodes that can be donated by multiple non-colluding end users that we will call super-peers Elmisery and Botvich (2011a, b, c); or third parties mash-up service Elmisery A, Botvich (2011a, b). Participants submit their locally obfuscated profiles anonymously to their local super-peer who collect and mix these preference data from multiple participants. The super-peer invokes AMPR to perform global perturbation process on the aggregated preference data to ensure a complete concealment of user's profiles. Then, it anonymously submits these aggregated profiles to a third party content recommender service to generate referrals without breaching participants' privacy. In this paper, we also provide an IPTV network scenario and experimentation results. Our results and analysis shows that our two-stage concealment process not only protect the users' privacy, but also can maintain the recommendation accuracy
Multimedia Tools and Applications
IPTV networks
Multi-agent
Recommender System
Dive into the research topics of 'Multi-agent based middleware for protecting privacy in IPTV content recommender services'. Together they form a unique fingerprint.
IPTV Engineering & Materials Science 100%
Middleware Engineering & Materials Science 75%
Elmesiry, A., & Botvich, D. (2013). Multi-agent based middleware for protecting privacy in IPTV content recommender services. Multimedia Tools and Applications, 64(2), 249-275. https://doi.org/10.1007/s11042-012-1067-3
Elmesiry, Ahmed ; Botvich, Dmitri. / Multi-agent based middleware for protecting privacy in IPTV content recommender services. In: Multimedia Tools and Applications. 2013 ; Vol. 64, No. 2. pp. 249-275.
@article{c42f9ffa9dbb46219259144c6c6b31fb,
title = "Multi-agent based middleware for protecting privacy in IPTV content recommender services",
abstract = "This work presents our efforts to design an agent based middleware that enables the end-users to use IPTV content recommender services without revealing their sensitive preference data to the service provider or any third party involved in this process. The proposed middleware (called AMPR) preserves users' privacy when using the recommender service and permits private sharing of data among different users in the network. The proposed solution relies on a distributed multi-agent architecture involving local agents running on the end-user set up box to implement a two stage concealment process based on user role in order to conceal the local preference data of end-users when they decide to participate in recommendation process. Moreover, AMPR allows the end-users to use P3P policies exchange language (APPEL) for specifying their privacy preferences for the data extracted from their profiles, while the recommender service uses platform for privacy preferences (P3P) policies for specifying their data usage practices. AMPR executes the first stage locally at the end user side but the second stage is done at remote nodes that can be donated by multiple non-colluding end users that we will call super-peers Elmisery and Botvich (2011a, b, c); or third parties mash-up service Elmisery A, Botvich (2011a, b). Participants submit their locally obfuscated profiles anonymously to their local super-peer who collect and mix these preference data from multiple participants. The super-peer invokes AMPR to perform global perturbation process on the aggregated preference data to ensure a complete concealment of user's profiles. Then, it anonymously submits these aggregated profiles to a third party content recommender service to generate referrals without breaching participants' privacy. In this paper, we also provide an IPTV network scenario and experimentation results. Our results and analysis shows that our two-stage concealment process not only protect the users' privacy, but also can maintain the recommendation accuracy",
keywords = "Clustering, IPTV networks, Multi-agent, Privacy, Recommender System",
author = "Ahmed Elmesiry and Dmitri Botvich",
journal = "Multimedia Tools and Applications",
Elmesiry, A & Botvich, D 2013, 'Multi-agent based middleware for protecting privacy in IPTV content recommender services', Multimedia Tools and Applications, vol. 64, no. 2, pp. 249-275. https://doi.org/10.1007/s11042-012-1067-3
Multi-agent based middleware for protecting privacy in IPTV content recommender services. / Elmesiry, Ahmed; Botvich, Dmitri.
In: Multimedia Tools and Applications, Vol. 64, No. 2, 01.05.2013, p. 249-275.
T1 - Multi-agent based middleware for protecting privacy in IPTV content recommender services
AU - Elmesiry, Ahmed
AU - Botvich, Dmitri
N2 - This work presents our efforts to design an agent based middleware that enables the end-users to use IPTV content recommender services without revealing their sensitive preference data to the service provider or any third party involved in this process. The proposed middleware (called AMPR) preserves users' privacy when using the recommender service and permits private sharing of data among different users in the network. The proposed solution relies on a distributed multi-agent architecture involving local agents running on the end-user set up box to implement a two stage concealment process based on user role in order to conceal the local preference data of end-users when they decide to participate in recommendation process. Moreover, AMPR allows the end-users to use P3P policies exchange language (APPEL) for specifying their privacy preferences for the data extracted from their profiles, while the recommender service uses platform for privacy preferences (P3P) policies for specifying their data usage practices. AMPR executes the first stage locally at the end user side but the second stage is done at remote nodes that can be donated by multiple non-colluding end users that we will call super-peers Elmisery and Botvich (2011a, b, c); or third parties mash-up service Elmisery A, Botvich (2011a, b). Participants submit their locally obfuscated profiles anonymously to their local super-peer who collect and mix these preference data from multiple participants. The super-peer invokes AMPR to perform global perturbation process on the aggregated preference data to ensure a complete concealment of user's profiles. Then, it anonymously submits these aggregated profiles to a third party content recommender service to generate referrals without breaching participants' privacy. In this paper, we also provide an IPTV network scenario and experimentation results. Our results and analysis shows that our two-stage concealment process not only protect the users' privacy, but also can maintain the recommendation accuracy
AB - This work presents our efforts to design an agent based middleware that enables the end-users to use IPTV content recommender services without revealing their sensitive preference data to the service provider or any third party involved in this process. The proposed middleware (called AMPR) preserves users' privacy when using the recommender service and permits private sharing of data among different users in the network. The proposed solution relies on a distributed multi-agent architecture involving local agents running on the end-user set up box to implement a two stage concealment process based on user role in order to conceal the local preference data of end-users when they decide to participate in recommendation process. Moreover, AMPR allows the end-users to use P3P policies exchange language (APPEL) for specifying their privacy preferences for the data extracted from their profiles, while the recommender service uses platform for privacy preferences (P3P) policies for specifying their data usage practices. AMPR executes the first stage locally at the end user side but the second stage is done at remote nodes that can be donated by multiple non-colluding end users that we will call super-peers Elmisery and Botvich (2011a, b, c); or third parties mash-up service Elmisery A, Botvich (2011a, b). Participants submit their locally obfuscated profiles anonymously to their local super-peer who collect and mix these preference data from multiple participants. The super-peer invokes AMPR to perform global perturbation process on the aggregated preference data to ensure a complete concealment of user's profiles. Then, it anonymously submits these aggregated profiles to a third party content recommender service to generate referrals without breaching participants' privacy. In this paper, we also provide an IPTV network scenario and experimentation results. Our results and analysis shows that our two-stage concealment process not only protect the users' privacy, but also can maintain the recommendation accuracy
KW - Clustering
KW - IPTV networks
KW - Multi-agent
KW - Privacy
KW - Recommender System
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
Elmesiry A, Botvich D. Multi-agent based middleware for protecting privacy in IPTV content recommender services. Multimedia Tools and Applications. 2013 May 1;64(2):249-275. https://doi.org/10.1007/s11042-012-1067-3


Hip replacement surgery has been around since the early 1960s. Sir John Charnley experimented in the early 1950s, and he used a small (22 mm) stainless steel ball on a stem in 1962 that he inserted into the femur (hip) bone to replace the femoral head (ball). He then inserted a high-density plastic socket to replace the acetabular (socket) side of the hip joint. Both were secured with a self-curing acrylic polymer known as bone cement.
Jessica Birmingham on The Hipster Club!


You are visiting the placeholder page for Donna Ross. This page is here because someone used our placeholder utility to look for Donna Ross. We created this page automatically in hopes Donna Ross would find it. If you are not Donna Ross, but are an alumni of Irving High School, register on this site for free now.


9aa684ed 55 puts "Export to PS format was done"
58 puts "Error: Export to PS file was done but size of file is incorrect (refsize = $refsize, current = $filesize)."
59 puts "Error: Compare content of resulting PS file with reference."
9aa684ed 63 puts "Faulty : Export to PS format was not done"


I don't want to wake up pregnant.
and I don't want to wake up.
I don't want to wake up the girls, okay? Ah.
but I don't want to wake up my godchild.
I don't want to wake up one morning hating you.
and I don't want to wake up to your dad hating me.
But I don't want to wake up in the morning thinking she's still here.
I don't want him to wake up alone. I should go to the hospital.
She has a shovel here somewhere. Quiet, I don't want to wake her up.
I just don't want him to wake up alone, not knowing what's happening.
I don't want to give that up. I don't want to be an ant, you know?
I don't want to wake.
Don't want to wake up your friends.
I didn't want to wake you up.
I wouldn't want to WAKE anyone up!
I don't want to wake them.


text:
Q: Start Quartz Job dynamically in ASP.NET Core 3.1 WebAPI I have a ASP.NET Core 3.1 Web API and have chosen to use Quartz.net to execute recurring tasks.
I've implemented the QuartzHostedService as recommended and I manage to start job successfully by declaring them in the startup.
But I also need to add and execute some jobs dynamically by getting them in a database, and I don't want to deploy and restart my Web API each time I need to add a new recurring job (because some of my clients could add their own recurring tasks).
I managed to add jobs in the quartzHosted service by implemented a method in it:
public async Task AddJob(JobSchedule job)
{
        Scheduler = await _schedulerFactory.GetScheduler();

        Scheduler.JobFactory = _jobFactory;
        var j = CreateJob(job);
        var trigger = CreateTrigger(job);
        await Scheduler.ScheduleJob(j, trigger);
        job.JobStatus = JobStatus.Scheduling;

        await Scheduler.Start();
        job.JobStatus = JobStatus.Running;
}

I have implemented an InitialJob that have the goal to ask the database for new jobs (this job is declared in the startup).
In this InitialJob, my execute method is like this:
// Create a new scope
using (var scope = _provider.CreateScope())
{
    // Resolve the Scoped service
    var _uow = scope.ServiceProvider.GetService<IUnitOfWork>();
    var stats = await _uow.Stat.GetActive();

    var test = await _quartzHostedService.GetAllJobs();

    foreach (var clientStat in stats.GroupBy(s => s.Clients))
    {
        foreach (var job in clientStat)
        {
            var key = new JobKey($"{job.Constant}.{clientStat.Key.FirstOrDefault().Id}");
            var jobExist = _quartzHostedService.Scheduler.CheckExists(key);

            if (!jobExist.Result)
            {
                var jobSchedule = new JobSchedule(jobType: typeof(GenericSimulationJob), cronExpression: job.Trigger.CronTask, job, clientStat.Key.FirstOrDefault().Id);
                await _quartzHostedService.AddJob(jobSchedule);
            }
        }
    }

    var test2 = await _quartzHostedService.GetAllJobs();
}

When I check the jobs before adding them (variable test) I only have 2 jobs in the quartzHostedService, after adding them in the foreach (variable test2) I have 5. Perfect.
But it seems I'm not able to execute them. I only see 2 jobs in my QuartzHostedService.Schedule.CurrentlyExecutedJob.
I also see only 2 jobs in my jobFactory variable.
I tried to sleep and restart my Schedule but nothing works. Did I missed something? Is it just possible?
Thanks for your help

A: I found my mistake. I forgot to declare my IJob (which contains my scheduleJobs) in the startup, even if there is no job schedule in it at start.
services.AddSingleton<GenericSimulationJob>();

Then my code works (without start scheduler instance again).


Count down to Solar Switch On!
With the handover of the school from the contractors to the Council now imminent, we are hopefully days away from being able to turn the array on. This news comes as we hear that the Leominster Community Solar array on Bridge Street tennis hall has so far saved 100 tonnes of carbon dioxide, over it's (short) lifetime so far. Leominster is blazing a trail for solar co-ops in the UK, setting a number of 'firsts', of which we are very proud. The sooner we can get the share offer complete, the sooner we can set to work on all the other ideas for solar co-ops in the town that are swirling around. Please do pass the word on that we only have £34,500 worth of shares remaining, as word of mouth is always the best way to find new members.


text:
Home Sports Panthers Place QB Cam Newton on Injured Reserve
Panthers Place QB Cam Newton on Injured Reserve
The Carolina Panthers are officially Kyle Allen's team to quarterback, at least for the rest of 2019.
Longtime starting quarterback Cam Newton was placed in injured reserve on Tuesday afternoon, officially ending his ninth NFL season. Newton has not played since sustaining a foot injury in a Week 2.
""We have said all along that it is impossible to put a timetable on this injury. Nobody is more frustrated with that fact than Cam," Panthers general manager Marty Hurney said in a statement on the team website. "He's one of the fiercest competitors I've been around during my 20-plus years in the League. At this time, we have decided that the best decision to reach the goal of bringing the foot back to 100 percent is to place Cam on injured reserve."
Cam Newton placed on injured reservehttps://t.co/H5XQr6A7Av
— Carolina Panthers (@Panthers) November 5, 2019
Since December 2018, the 30-year-old Newton has missed all but two of the Panthers' past ten games with an injury. He underwent offseason shoulder surgery after missing the last two games of the previous year before his latest injury suffered in a Thursday night loss to Tampa Bay in September. Newton had missed just two games due to injury in his first seven NFL season.
Next season, the quarterback will enter the final season of a five-year, $103.8 million contract extension inked in June 2015. Newton was originally drafted first overall by the Panthers in 2011. He has already become the most prolific passer in team history with highs in career yardage (29,041) and touchdown passes (182). Also on Newton's Carolina resume are three Pro Bowl nominations and the 2015 NFL MVP Award en route to an appearance in Super Bowl 50.
Carolina currently sits at 5-3, a half-game behind Minnesota for the final NFC wild card spot. Allen, a second-year undrafted free agent out of Houston, has filled in admirably in Newton's spot, throwing for 1,291 yards and nine touchdowns with a 5-1 record. Will Grier, a third-round pick in the most recent draft, has served as Allen's backup and will continue to do so.
The Panthers continue their playoff chase on Sunday afternoon on the road against the Green Bay Packers.
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text:
Петро Кушка (хресне ім'я Іван;  21 квітня 1953, Вензіна, Польща) — український церковний діяч у Польщі, ієромонах-василіянин, парох греко-католицького храму Успіння Пресвятої Богородиці у Варшаві (вул. Мйодова, 16).

Життєпис
Народився 21 квітня 1953 року у с. Вензіна Вармінсько-Мазурського воєводства в Польщі. Походить із сім'ї українців переселених внаслідок Акції «Вісла» з Любачівського повіту. Середню школу закінчив в Ельблонгу. 29 серпня 1972 року вступив до Василіянського Чину на новіціят у Варшаві. Після новіціяту навчався у римо-католицькій Вищі Митрополичій духовній семінарії у Варшаві. 1 квітня 1979 року склав вічні обіти у Василіянському Чині, а 27 травня цього ж року отримав священничі свячення.

Після висвячення п'ять років душпастирював у Варшаві в храмі при василіянському монастирі і тоді ж упродовж трьох років щонеділі доїздив до греко-католицької парафії в Ольштині, а в 1985—1990 роках працював там постійно, одночасно обслуговуючи другу парафію в Доброму Місті. Окрім праці на цих двох парафіях, доїздив також до кількох осередків, де проводив катехизації. У 1990—1999 роках працював у монастирі у Венґожево: три роки як парох, а потім як магістр новіціяту. У 1999 році повернувся до Варшави, працював спочатку духівником у семінарії, а від 2003 року — парохом.

Виконував різні уряди в управі Провінції Покрови Пресвятої Богородиці отців василіян у Польщі: радника і секретаря провінції, провінційного вікарія (2012—2016) і економа (з 2016 року).

Нагороди
 Орден «За заслуги» III ступеня (23 серпня 2019) — за вагомий особистий внесок у зміцнення міжнародного авторитету України, розвиток міждержавного співробітництва, плідну громадську діяльність.

Примітки

Джерела
 Catalogo dell'Ordine Basiliano di San Giosafat. — Roma 2021. — 193 p.

Василіяни
Священники УГКЦ
Українці Варшави

redpajama_set_name: RedPajamaWikipedia


Our mission is to equip Christian disciples for Christian service. Scroll down to see all our publications on Christian faith and discipleship. Or skip down to items available to download FREE!
Advent is the season of the Christian Year that begins on the fourth Sunday before Christmas. It is a time for celebrating Jesus as the light of the world. Advent the book is a little package of readings, songs, meditations, and prayers for a simple, meaningful way to celebrate Advent with your family and friends. It will give you a way to slow down December to allow you to savor Christmas.
A great gift-giving idea for your family when you gather for Thanksgiving!
Order before November 15 to insure delivery in time for the Advent season.
Prepare for the challenge and thrill of reading the Bible in big bites with interest and insight. Ten lessons with notes for the teacher. Excellent for the classroom, as a small-group study, or for independent study.
A plain-talk translation of the Sermon on the Mount with background notes and an overview of the first thirty years of the Jesus Movement.
The Christian message is the great good news of God's victory over sin and death through Jesus Christ. Heaven Here & Now will help you share that great good news with your family and friends.
Can be printed as a 5½ x 8½ booklet.
The Way of Jesus as a guide to life and love (the part-one companion of To Sit at the Welcome Table). Topics include How to Receive the Holy Spirit and How to Hear a Word from God. Twelve chapters, each with questions for group discussion. Reviewed by Dr. LeRoy Lawson in The Christian Standard.
The Way of Jesus as a guide to life together (the part-two companion of Marching to Zion). Topics include the Politics of Compassion, Prophetic Justice, and How to Recognize the True People of God. Thirteen chapters, each with questions for group discussion.
A prescription for Christian unity written in 1809, more than two hundred years ahead of its time. Presented in the original with its Scot-Irish lilt and in a contemporary English reading. A must for anyone interested in the nature and purpose of the church. A key resource for Christian leadership training.
First John was written to address a crisis. Christians were giving up on authentic Christian community—either to return to an old-time religion or to invent a new one. Today we have a similar crisis. Christians are busy doing religion—and are neglecting authentic Christian community. We need to hear First John!
The items below are available for download, complementary from Holly House.
A ready-reference guide to Bible history.
A strategy for aligning church organization and administration with the Great Commission.
A three-year curriculum in Adult Christian Education. A plan for equipping Christian Disciples for Christian Service.
A worksheet for preachers. Helps you preach so people will know what you're talking about and what you expect them to do about it! Instructions for using The Sermon Worksheet are available below.
How to use The Sermon Worksheet. Includes a sample worksheet and The Congregation's Bill of Rights.
A worksheet that helps you identify your special call to Christian service. For a brief introduction to the biblical idea of spiritual gifts, see Spiritual Gifts below.
A Companion Study to Your Profile for Christian Service.


text:
Health: New Challenges for the LGBTQ Community In Canada
TORONTO – In 2017, it is difficult to find a doctor with a clear understanding of the health problems of the lesbian, gay, bisexual, trans and queer (LGBTQ) community, according to several experts consulted by #ONfr . The challenge is twofold when you want to obtain services in French.
"There is not enough French speaking physicians to meet the needs," says Gilles Marchildon, Executive Director of Reflet Salvéo, a lead agency advising the Local Health Integration Networks (LHINs) Greater Toronto Area.
In 2012, Reflet Salvéo noted the existence of deficiencies in the French-language health system to help victims of the human immunodeficiency virus (HIV). Among other things, there was a lack of case management for Francophones. Five years later, progress has been made on this issue, says Marchildon.
For example, Reflet Salvéo's Executive Director recalls the creation of two case management positions at the Center francophone de Toronto (CFT), which gives a major boost to the community.
"There is still work to be done," he believes all the same.
Mr. Marchildon added that the health problems of the LGBTQ community are becoming more and more known, helping to advance the cause.
Incomprehension of health professionals
Arnaud Baudry, president of FrancoQueer, shares in part the report of Reflet Salvéo. However, it demonstrates that there are many challenges in the LGBTQ environment.
"There is a lack of understanding and lack of knowledge within the medical community regarding transgender people" – Arnaud Baudry.
The president of the francophone association of the LGBTQ community in Ontario says he heard several stories of transgender people about the difficulty of communicating these issues openly with physicians. The issue is even more important when it comes to obtaining health care in French.
"There are services in French but the problems are the same and the patients are faced with caregivers who do not fully understand their reality," says FrancoQueer's president.
"It is unbelievable that health services are one of the places where LGBTQ people are most uncomfortable when they are most in need of services to care for themselves, " – Arnaud Baudry.
Mr. Baudry also regrets that the changes expected by the LGBTQ community within the Ontario health system are not occurring quickly enough.
A gray area around the PrEP
Pre-exposure prophylaxis (PrEP), used to fight HIV, is becoming more and more popular in Canada.
However, Baudry and Marchildon note that there is still a gray area in Ontario with health professionals.
The cure can have two uses: either HIV prevention or the treatment of the virus. Its cost reaches $ 1,000 a month, says the president of FrancoQueer, which is a serious brake on its use.
In addition, Mr. Baudry regretted that doctors were not aware of the preventive use of the drug and that it was often the patient's responsibility to inform the healthcare professionals.
For the president of FrancoQueer, it is clear that better education could make a big difference in the use of this drug.
CategoriesCanada TagsLGBTQ
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"Katrina's Son" "Ticked-off Trannies with Knives"
Official Selection, Cannes Film Festival, 2011. Official Selection, Tribeca Film Festival, 2010.
Winner, 2010 Student Academy Award, Gold Medal, Doc. Official Selection, Sundance Film Festival, 2013.
Finalist, Student Academy Award, 2007.
"I'll Come Running" "Ticked-off Trannies with Knives"
TV Premiere: IFC, Nov, 2009. TV Premiere: SHOWTIME, July, 2011.
"The Cassidy Kids" "Bitter Memories"
TV Premiere: IFC, April, 2008. TV Premiere: SHOWTIME, Feb, 2010.
"A Man Made Early" TV Premiere: SHOWTIME, 2011.
"The Second Coming" "The Second Coming"
HBO Premiere: February, 2008. Cinemax Premiere: April, 2008.
Official Selection, SXSW Film Festival, 2013. TV Premiere: Independent Lens (PBS), June, 2008.
Official Selection, SXSW Film Festival, 2012.
Official Selection, SXSW Film Festival, 2010.
Official Selection, SXSW Film Festival, 2009.
Official Selection, SXSW Film Festival, 2008.
Official Selection, SXSW Film Festival, 2006.


§ 215-1 Hydraulic fracturing prohibited.
§ 215-3 Treatment, discharge, disposal or storage of waste and other byproducts prohibited.
§ 215-4 Violations and penalties; enforcement.
Drilling for natural gas using the drilling technique of hydraulic fracturing (fracking) and exploring for natural gas beyond the reconnaissance phase is prohibited within the Borough of Highland Park, Middlesex County, New Jersey.
"Hydraulic fracturing" shall mean the drilling technique of expanding existing fractures or creating new fractures in rock by injecting water, often with chemicals, sand, or other substances, and often under pressure, into or underneath the surface of the rock for purposes, including, but not limited to, well drilling and natural gas exploration and production. The term "hydraulic fracturing" shall include "fracking," "hydrofracking," "hydrofracturing," and other colloquial terms for this drilling technique.
No wastewater, wastewater solids, sludge, drill cuttings or other byproducts resulting from hydraulic fracturing for the purpose of natural gas exploration or production may be treated, discharged, disposed of, applied to a roadway or otherwise released into the environment, or stored in the Borough of Highland Park.
Any person or entity violating the provisions of this article, upon conviction before a Municipal Court Judge of the Borough, shall be subject to a fine of not less than $2,500 and not more than $10,000 at the discretion of the Municipal Court Judge.
In addition to any other remedies provided for in this article, the Borough Attorney, or his or her designee, may commence an action in the Superior Court of New Jersey to enjoin a person or entity that has violated this article and for any other appropriate remedies at law or equity.


This album like Anderson .Paak's last has a fair bit of funk to it. It's not really my style of listening, but I think it's a good piece of work overall. He's got some pretty good features and maybe I'll give it another try some other day.


text:
BlackBerry Q10 Release Date in the USA Set for June 5
T-Mobile USA confirms the official release date for BlackBerry Q10 in the United States, also revealing its pricing.
While the BlackBerry Z10 flagship mobile casino device is already conquering the hearts and wallets of technophiles and gamers, the second device is about to hit the shelves in America. The Q10 is also running on the brand new BB10 OS, but comes with a full QWERTY keyboard die-hard BlackBerry fans will surely appreciate.
The BlackBerry mobile casino device comes with LTE support and will surely make full use of the T-Mobile's 4G network where available. Other features include a 3.1-inch, 720×720 SuperAMOLED screen with 328ppi, an 8MP snapper, and is powered by a dual-core Cortex-A9 1.5GHz processor.
The connectivity suit of the upcoming BlackBerry gambling tool is quite extensive and besides the LTE includes Bluetooth 4.0, Wi-Fi a/b/g/n, and much more. As for the software: the BlackBerry Messenger is in tact, naturally, but now featuring video chat as if texting wasn't enough.
The carrier offers the BlackBerry Q10 for $100 on a two-year contract, while the SIM-free version will set mobile casino games lovers $580. It seems that T-Mobile will be the first American network to feature the smartphone, while there's still no word on when it will hit the competitors.
Tags: BB10, BlackBerry, BlackBerry gambling tool, BlackBerry mobile casino device, mobile casino device, Q10, T-Mobile, USA, Z10
BlackBerry Z10 American Release Date Announced by AT&T
BlackBerry Z10 is preparing to hit the US market through AT&T carrier with dates and...
BlackBerry R-Series Said to Deliver Mid-range Specs and Price
Following the two BlackBerry flagship devices, another smartphone running on the BB10 OS has been...
BlackBerry Q10 Release Date to Coincide with the BB10.1 Update
BB10 OS from BlackBerry is about to receive its first major update coinciding with the...
BlackBerry R10 Release Date Rumored for Q3 2013
The newest BlackBerry OS is gaining ground and the launch of Q10 is nearing fast,...
BlackBerry 10.2 Update is Scheduled to Reach Devices by the End of Year
The second major update is scheduled to hit the brand new BlackBerry devices running on...


text:
using System;
using System.Collections.Generic;
using System.Linq;
using System.Reflection;
using JetBrains.Annotations;
using LinqToDB;
using NUnit.Framework;
using Tests.Model;

namespace Tests.Linq
{

	[AttributeUsage(AttributeTargets.Method, AllowMultiple = true)]
	public class ExtensionChoiseAttribute : Attribute
	{
		public ExtensionChoiseAttribute(string configuration, string expression, [NotNull] params Type[] types)
		{
			if (types == null) throw new ArgumentNullException(nameof(types));

			Configuration = configuration;
			Expression    = expression;
			Types         = types;
		}

		public string Configuration { get;         set; }
		public string Expression    { get;         set; }
		public Type[] Types         { get; private set; }
	}

	class GenericBuilder : Sql.IExtensionCallBuilder
	{
		string Match(Type[] current, ExtensionChoiseAttribute[] choices)
		{
			var found = new List<ExtensionChoiseAttribute>();
			foreach (var c in choices)
			{
				var notMatched = false;
				for (int i = 0; i < Math.Min(current.Length, c.Types.Length); i++)
				{
					if (c.Types[i] != null && c.Types[i] != current[i])
					{
						notMatched = true;
						break;
					}
				}

				if (!notMatched)
					found.Add(c);
			}

			if (found.Count > 1)
				found = found.Where(f => f.Types.Any(t => t != null)).ToList();

			if (found.Count == 0)
				throw new InvalidOperationException("Can not deduce pattern for types squence: " +
				                                    string.Join(", ", current.Select(t => t.Name)));

			if (found.Count > 1)
				throw new InvalidOperationException("Ambigous patterns found:\n" +
				                                    string.Join("\n",
					                                    found.Select(f => string.Join(", ",
						                                    f.Types.Select(t => t == null ? "null" : t.Name)))));
			return found[0].Expression;
		}

		public void Build(Sql.ISqExtensionBuilder builder)
		{
			var method = builder.Member as MethodInfo;

			if (method != null && method.IsGenericMethod)
			{
				var typeParameters = method.GetGenericArguments();
				builder.Expression = Match(typeParameters,
					builder.Mapping.GetAttributes<ExtensionChoiseAttribute>(builder.Member.DeclaringType, method, a => a.Configuration));
			}
			else
				throw new InvalidOperationException("This extension could be applied only to methods with type parameters.");
		}
	}

	public static class GenericExtensionsFunctions
	{

		[Sql.Extension(typeof(GenericBuilder))]
		[ExtensionChoise("", "'T1=UNSUPPORTED PARAMETERS'",                                                                                null,           null          )]
		[ExtensionChoise("", "'T2=(BYTE: ' + CASE WHEN {second} IS NULL THEN 'null' ELSE CAST({second} AS NVARCHAR) END + ')'",                                         null,           typeof(byte?) )]
		[ExtensionChoise("", "'T3=(BYTE: ' + CAST({first} AS NVARCHAR) + ', INT: ' + CASE WHEN {second} IS NULL THEN 'null' ELSE CAST({second} AS NVARCHAR) END + ')'", typeof(byte),   typeof(int?)  )]
		[ExtensionChoise("", "'T4=(BYTE: ' + CAST({first} AS NVARCHAR) + ', INT: ' + CAST({second} AS NVARCHAR) + ')'",                                                 typeof(byte),   typeof(int)   )]
		[ExtensionChoise("", "'T5=(CHAR: ' + CASE WHEN {first} IS NULL THEN 'null' ELSE CAST({first} AS NVARCHAR) END + ', STRING: ' + {second} + ')'",                 typeof(char?),  typeof(string))]
		public static string TestGenericExpression<TFirstValue, TSecondValue>(this Sql.ISqlExtension ext,
			[ExprParameter("first")]  TFirstValue value,
			[ExprParameter("second")] TSecondValue secondValue)
		{
			throw new InvalidOperationException("Server-side call failed");
		}
	}

	class GenericExtensionTests : TestBase
	{

		[Test, IncludeDataContextSource(ProviderName.SqlServer2008, ProviderName.SqlServer2012, ProviderName.SqlServer2014, TestProvName.SqlAzure)]
		public void Issue326(string context)
		{
			using (var db = GetDataContext(context))
			{
				var result = db.GetTable<Parent>()
					.Select(_ => new
					{
						R1 = Sql.Ext.TestGenericExpression<char?, string>('X', "some string"),
						R2 = Sql.Ext.TestGenericExpression<char?, string>(null, "another string"),
						R3 = Sql.Ext.TestGenericExpression<char?, string>(null, null),

						R4 = Sql.Ext.TestGenericExpression<byte, int?>(123, 456),
						R5 = Sql.Ext.TestGenericExpression<byte, int?>(123, null),

						R6 = Sql.Ext.TestGenericExpression<byte, int>(123, 456),

						R7 = Sql.Ext.TestGenericExpression<long, byte?>(123, null),
						R8 = Sql.Ext.TestGenericExpression<short, byte?>(123, 45),

						R9 = Sql.Ext.TestGenericExpression<byte, long>(123, 45)
					}).First();

				Assert.AreEqual("T5=(CHAR: X, STRING: some string)", result.R1);
				Assert.AreEqual("T5=(CHAR: null, STRING: another string)", result.R2);
				Assert.AreEqual(null, result.R3);
				Assert.AreEqual("T3=(BYTE: 123, INT: 456)", result.R4);
				Assert.AreEqual("T3=(BYTE: 123, INT: null)", result.R5);
				Assert.AreEqual("T4=(BYTE: 123, INT: 456)", result.R6);
				Assert.AreEqual("T2=(BYTE: null)", result.R7);
				Assert.AreEqual("T2=(BYTE: 45)", result.R8);
				Assert.AreEqual("T1=UNSUPPORTED PARAMETERS", result.R9);
			}
		}
	}
}

redpajama_set_name: RedPajamaGithub


text:
Manchester United, News, Spanish Football
£33m+ Star Wants Man Utd Deal – reports
December 18, 2014 Spoughts	1 Comment
Manchester United star David De Gea is reportedly set to remain with the Old Trafford club in the January transfer window, and is set to seal a new deal with the Manchester side as a result.
De Gea has been exceptional since the start of the season, the loss away to MK Dons aside, and Man Utd fans were understandably fearful that he might move on, especially as his current contract has only 18 months left to run.
The likes of Real Madrid and Bayern Munich are thought to be floating around with an eye on the Spanish stopper, and Real, in particular, were thought to be willing to make a big offer.
They are said to be so keen on the 24 year old that they would look to break Gianluigi Buffon's 2001 record transfer fee for a goalkeeper, which saw him move to Juventus from Parma for £33 million.
De Gea himself holds the record for a British club, having cost Man Utd £18.9 million.
He could now be set to stay with a new deal, as reported by the Manchester Evening News.
Previous PostLiverpool Keen On £135k Wage 'New Zlatan Ibrahimovic' – reportsNext PostMan Utd Ace Unsure Over Future With Club
One thought on "£33m+ Star Wants Man Utd Deal – reports"
salia sonie says:
Once De Gea sign a new contract, I am happy.


If you should choose to utilise London Electricians' expert services, you can rest easy knowing that you are placing your trust in a electrical company with an outstanding reputation throughout the Hammersmith and Fulham area. From electrical installation to fire alarm repair, the engineers at London Electricians have the experience and the capability to execute jobs smoothly to minimise disruption to our customers.
We ensure that all of our engineers are trained to the highest industry standard, and have obtained a level three certification with NICEIC (National Inspection Council for Electrical Installation Contracting). Whilst working on-site, our engineers are consistent, reliable, and follow strict guidelines to maintain the safety of themselves and those around the site or property.
One integral aspect to our electrical installation service is our 24/7 call-out provision available to all of our customers in the Hammersmith and Fulham area. Should an electrical problem that needs immediate attention arise within your domestic or commercial property, do not hesitate to call our helpline for an instant connection to our professional and helpful team. One of our engineers can be with you within the hour in order to investigate the problem, and if the problem unfortunately cannot be solved on the spot, London Electricians can guarantee that it will only take 24 hours to source the essential part or component and fix the problem for good.
The team here at London Electricians have worked with a vast array of clients in the Hammersmith and Fulham area, from domestic home-owners in need of a plug socket repair to the landlord of a commercial building requiring an entire re-wiring of the electrical system. As we're based in Paddington, we're in an extremely helpful location to provide customers in the area with an extremely quick response time. No job is too big or too small for London Electricians, so be sure to get in contact with the team by calling 020 8728 9179 or by dropping an email to info@london-electricians.com. You can also fill out one of our straightforward online contact forms. Our friendly team has the expertise necessary to arrive at the best solution for your electrical installation issue or enquiry.


Waterford brings a touch of elegance to the dinner table with Aras dinnerware. Aras is derived from the Irish word for home and the pattern is inspired by the breath-taking Irish landscape. The design resembles the shimmering droplets of water from Ireland's beautiful lakes and rivers. The crispness of the pure white fine bone china is embellished with an elegant grey and platinum design that varies on each piece. The layering of the exquisite droplet boarder creates an interesting and textured framework, sure to impress your guests. Ideal for coffee, tea or desserts, this Aras Mug is a perfect addition to this modern collection.
The Aras Mug features layering of the exquisite droplet boarder creates an interesting and textured framework, sure to impress your guests. Ideal for coffee, tea or desserts, this Aras Mug is a perfect addition to this modern collection.