This document discusses personal content management on PDAs for healthcare applications. It describes scenarios for using mobile medical content, such as continuing medical education and emergency protocols. It also discusses the technical requirements for accessing and managing this medical content on a PDA in an intelligent way. The architecture uses the AXMEDIS format to semantically organize content and provide an intelligent PDA organizer application to enable personalized recommendations and offline access to medical resources.
This talk introduces Linked Data and Semantic Web by using two examples - population sciences grid and semantAqua - a semantically enabled environmental monitoring. It shows a few tools and the semantic methodology and opens discussion for LOD and team science
Modern learning models require linking experiences in training environments with experiences in the real-world. However, data about real-world experiences is notoriously hard to collect. Social spaces bring new opportunities to tackle this challenge, supplying digital traces where people talk about their real-world experiences. These traces can become valuable resource, especially in ill-defined domains that embed multiple interpretations. The paper presents a unique approach to aggregate content from social spaces into a semantic-enriched data browser to facilitate informal learning in ill-defined domains. This work pioneers a new way to exploit digital traces about real-world experiences as authentic examples in informal learning contexts. An exploratory study is used to determine both strengths and areas needing attention. The results suggest that semantics can be successfully used in social spaces for informal learning – especially when combined with carefully designed nudges.
This talk introduces Linked Data and Semantic Web by using two examples - population sciences grid and semantAqua - a semantically enabled environmental monitoring. It shows a few tools and the semantic methodology and opens discussion for LOD and team science
Modern learning models require linking experiences in training environments with experiences in the real-world. However, data about real-world experiences is notoriously hard to collect. Social spaces bring new opportunities to tackle this challenge, supplying digital traces where people talk about their real-world experiences. These traces can become valuable resource, especially in ill-defined domains that embed multiple interpretations. The paper presents a unique approach to aggregate content from social spaces into a semantic-enriched data browser to facilitate informal learning in ill-defined domains. This work pioneers a new way to exploit digital traces about real-world experiences as authentic examples in informal learning contexts. An exploratory study is used to determine both strengths and areas needing attention. The results suggest that semantics can be successfully used in social spaces for informal learning – especially when combined with carefully designed nudges.
Technologies for Enhancing Knowledge and Training, the future of e-learning t...Paolo Nesi
E-learning infrastructure
Tools for e-learning/distance learning
References
Support for blended learning
Distance testing and assessment
Advanced aspects with respect to Moodle, Atutor, etc.
Content production and development
Content management and distribution
anywhere learning
certified e-learning
social learning and networking
Knowledge management
Legal, Intellectual property management and conditional access (enabling and actuating legal control)
Scalability: Hardware/Software
ECLAP: life long learning, social learning
http://www.eclap.eu
FirstClass: certified blended learning, paid courses
http://fad.fclass.it
IUF.Csavri: blended learning for entrepreneurs incubation and spin-offs
http://iuf.csavri.org
APRETOSCANA: formation for researchers
http://www.apretoscana.org
DISIT.DINFO.UNIFI.IT: research management and dissemination
http://www.disit.dinfo.uinifi.it
OSIM.UNIFI: knowledge management for UNIFI
http://openmind.disit.org
Linked Open Graph: browsing multiple SPARQL entry points to build your own LO...Paolo Nesi
A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. In this paper, the Linked Open Graph, LOG, is presented. It is a web tool for collaborative browsing and navigation on multiple SPARQL entry points. The paper presented an overview of major problems to be addressed, a comparison with the state of the arts tools, and some details about the LOG graph computation to cope with high complexity of large Linked Open Dada graphs. The LOG.disit.org tool is also presented by means of a set of examples involving multiple RDF stores and putting in evidence the new provided features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and it has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence / knowledge mining and analysis. Keywords LOD, LOD browsing, knowledge base browsing, SPARQL entry points.
Modelli Semantici e Gestione della Conoscenza: Social Network vs Knowledge Ma...Paolo Nesi
Modelli Semantici e Gestione della Conoscenza: Social Network vs Knowledge Management Systems. Seminario per il dottorato in Ingegneria Informatica e delle telecomunicazioni, Univ. Studi di Firenze, 2013
ICT e per la Gestione soccorso integrato nelle maxi emergenzePaolo Nesi
ICT e per la Gestione
Corso per il Master di I Livello, “ Il soccorso integrato nelle maxi emergenze: il management sanitario”, AA. 2012‐2013
Paolo Nesi, Ivan Bruno
Distributed and Internet Technology Lab, Dipartimento di Ingegneria dell’informazione
Paolo.nesi@unifi.it, Http://www.disit.dinfo.unifi.it
Parti: Le reti di calcolatori, Protocolli ed Internet, WEB, Architetture Client Server, Pagine HTML, Comunicazioni Wireless e protocolli, Reti WiFi e Cellulari, Esercitazioni varie, Comunicazioni in condizioni di emergenza, Sistemi di Comunicazione Satellitari, Sistemi Operativi per Sistemi Mobili, Sensori dei Sistemi Mobili, La proposta di Mobile Emergency
ECLAP 2013 tutorial at Porto, April 2013Paolo Nesi
ECLAP tutorial, from metadata to architecutre, from lod and social media to content aggregation, from semantic computing to automated content processing, social graph, . mystoryplayer
DISIT lab Overview on Tourism and Training, June 2014Paolo Nesi
Semantic Model and Tools
• OSIM, knowledge mining, competence management
• RDF stores, Open Data, Linked Open Data management
• Content Tools
• Content modeling, indexing and querying, recommendations
• Content management and distribution
• Intellectual property management and conditional access (enabling
and actuating legal control)
• Devices:
• iOS Apple, Android, Windows Phone, Smart TV
• Tourism
• Open Data and Smart City data
• Training E‐learning
• Tools for e‐learning/distance/blended learning, anywhere learning,
certified e‐learning, social learning and networking
Towards Socially Intelligent Media ComputingPaolo Nesi
Towards Socially Intelligent Media Computing
Keynote at KESS 2nd International Symposium on
Intelligent Interactive Multimedia Systems and Services, IIMSS09
Mogliano Veneto, Venice, Italy, organized by University of Milan, July 2009
Technologies for Enhancing Knowledge and Training, the future of e-learning t...Paolo Nesi
E-learning infrastructure
Tools for e-learning/distance learning
References
Support for blended learning
Distance testing and assessment
Advanced aspects with respect to Moodle, Atutor, etc.
Content production and development
Content management and distribution
anywhere learning
certified e-learning
social learning and networking
Knowledge management
Legal, Intellectual property management and conditional access (enabling and actuating legal control)
Scalability: Hardware/Software
ECLAP: life long learning, social learning
http://www.eclap.eu
FirstClass: certified blended learning, paid courses
http://fad.fclass.it
IUF.Csavri: blended learning for entrepreneurs incubation and spin-offs
http://iuf.csavri.org
APRETOSCANA: formation for researchers
http://www.apretoscana.org
DISIT.DINFO.UNIFI.IT: research management and dissemination
http://www.disit.dinfo.uinifi.it
OSIM.UNIFI: knowledge management for UNIFI
http://openmind.disit.org
Linked Open Graph: browsing multiple SPARQL entry points to build your own LO...Paolo Nesi
A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. In this paper, the Linked Open Graph, LOG, is presented. It is a web tool for collaborative browsing and navigation on multiple SPARQL entry points. The paper presented an overview of major problems to be addressed, a comparison with the state of the arts tools, and some details about the LOG graph computation to cope with high complexity of large Linked Open Dada graphs. The LOG.disit.org tool is also presented by means of a set of examples involving multiple RDF stores and putting in evidence the new provided features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and it has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence / knowledge mining and analysis. Keywords LOD, LOD browsing, knowledge base browsing, SPARQL entry points.
Modelli Semantici e Gestione della Conoscenza: Social Network vs Knowledge Ma...Paolo Nesi
Modelli Semantici e Gestione della Conoscenza: Social Network vs Knowledge Management Systems. Seminario per il dottorato in Ingegneria Informatica e delle telecomunicazioni, Univ. Studi di Firenze, 2013
ICT e per la Gestione soccorso integrato nelle maxi emergenzePaolo Nesi
ICT e per la Gestione
Corso per il Master di I Livello, “ Il soccorso integrato nelle maxi emergenze: il management sanitario”, AA. 2012‐2013
Paolo Nesi, Ivan Bruno
Distributed and Internet Technology Lab, Dipartimento di Ingegneria dell’informazione
Paolo.nesi@unifi.it, Http://www.disit.dinfo.unifi.it
Parti: Le reti di calcolatori, Protocolli ed Internet, WEB, Architetture Client Server, Pagine HTML, Comunicazioni Wireless e protocolli, Reti WiFi e Cellulari, Esercitazioni varie, Comunicazioni in condizioni di emergenza, Sistemi di Comunicazione Satellitari, Sistemi Operativi per Sistemi Mobili, Sensori dei Sistemi Mobili, La proposta di Mobile Emergency
ECLAP 2013 tutorial at Porto, April 2013Paolo Nesi
ECLAP tutorial, from metadata to architecutre, from lod and social media to content aggregation, from semantic computing to automated content processing, social graph, . mystoryplayer
DISIT lab Overview on Tourism and Training, June 2014Paolo Nesi
Semantic Model and Tools
• OSIM, knowledge mining, competence management
• RDF stores, Open Data, Linked Open Data management
• Content Tools
• Content modeling, indexing and querying, recommendations
• Content management and distribution
• Intellectual property management and conditional access (enabling
and actuating legal control)
• Devices:
• iOS Apple, Android, Windows Phone, Smart TV
• Tourism
• Open Data and Smart City data
• Training E‐learning
• Tools for e‐learning/distance/blended learning, anywhere learning,
certified e‐learning, social learning and networking
Towards Socially Intelligent Media ComputingPaolo Nesi
Towards Socially Intelligent Media Computing
Keynote at KESS 2nd International Symposium on
Intelligent Interactive Multimedia Systems and Services, IIMSS09
Mogliano Veneto, Venice, Italy, organized by University of Milan, July 2009
Personium - Open Source PDS envisioning the Web of MyData暁生 下野
How can we citizens maximize the benefits of the new right to data portability, which is now rapidly being recognized globally?
Personal Data Store is a technology that will receive all “My Data” from hundreds of services. It aggregates and integrates them, and at times discloses a portion of them to others under user’s control for creating new values.
This talk will introduce an open-source Personal Data Store (PDS) server “Personium”, providing details on its technical implementation, the underpinning business models, and the actual implemented and future use cases.
Microsoft Research - Turning Ideas into Realitygoodfriday
This talk focuses on some of the key projects that Microsoft Research is developing in their research labs, worldwide. The key project discussion will be supplemented by a number of prototype demos from the 55 areas of computer science research which our labs are engaged in.
Building a healthy data ecosystem around Kafka and Hadoop: Lessons learned at...Yael Garten
2017 StrataHadoop SJC conference talk. https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/56047
Description:
So, you finally have a data ecosystem with Kafka and Hadoop both deployed and operating correctly at scale. Congratulations. Are you done? Far from it.
As the birthplace of Kafka and an early adopter of Hadoop, LinkedIn has 13 years of combined experience using Kafka and Hadoop at scale to run a data-driven company. Both Kafka and Hadoop are flexible, scalable infrastructure pieces, but using these technologies without a clear idea of what the higher-level data ecosystem should be is perilous. Shirshanka Das and Yael Garten share best practices around data models and formats, choosing the right level of granularity of Kafka topics and Hadoop tables, and moving data efficiently and correctly between Kafka and Hadoop and explore a data abstraction layer, Dali, that can help you to process data seamlessly across Kafka and Hadoop.
Beyond pure technology, Shirshanka and Yael outline the three components of a great data culture and ecosystem and explain how to create maintainable data contracts between data producers and data consumers (like data scientists and data analysts) and how to standardize data effectively in a growing organization to enable (and not slow down) innovation and agility. They then look to the future, envisioning a world where you can successfully deploy a data abstraction of views on Hadoop data, like a data API as a protective and enabling shield. Along the way, Shirshanka and Yael discuss observations on how to enable teams to be good data citizens in producing, consuming, and owning datasets and offer an overview of LinkedIn’s governance model: the tools, process and teams that ensure that its data ecosystem can handle change and sustain #DataScienceHappiness.
Strata 2017 (San Jose): Building a healthy data ecosystem around Kafka and Ha...Shirshanka Das
So, you finally have a data ecosystem with Kafka and Hadoop both deployed and operating correctly at scale. Congratulations. Are you done? Far from it.
As the birthplace of Kafka and an early adopter of Hadoop, LinkedIn has 13 years of combined experience using Kafka and Hadoop at scale to run a data-driven company. Both Kafka and Hadoop are flexible, scalable infrastructure pieces, but using these technologies without a clear idea of what the higher-level data ecosystem should be is perilous. Shirshanka Das and Yael Garten share best practices around data models and formats, choosing the right level of granularity of Kafka topics and Hadoop tables, and moving data efficiently and correctly between Kafka and Hadoop and explore a data abstraction layer, Dali, that can help you to process data seamlessly across Kafka and Hadoop.
Beyond pure technology, Shirshanka and Yael outline the three components of a great data culture and ecosystem and explain how to create maintainable data contracts between data producers and data consumers (like data scientists and data analysts) and how to standardize data effectively in a growing organization to enable (and not slow down) innovation and agility. They then look to the future, envisioning a world where you can successfully deploy a data abstraction of views on Hadoop data, like a data API as a protective and enabling shield. Along the way, Shirshanka and Yael discuss observations on how to enable teams to be good data citizens in producing, consuming, and owning datasets and offer an overview of LinkedIn’s governance model: the tools, process and teams that ensure that its data ecosystem can handle change and sustain #datasciencehappiness.
IEEE CCNC 2011: Kalman Graffi - LifeSocial.KOM: A Secure and P2P-based Soluti...Kalman Graffi
The phenomenon of online social networks reaches millions of users in the Internet nowadays. In these, users present themselves, their interests and their social links which they use to interact with other users. We present in this paper LifeSocial.KOM, a p2p-based platform for secure online social networks which provides the functionality of common online social networks in a totally distributed and secure manner. It is plugin-based, thus extendible in its functionality, providing secure communication and access-controlled storage as well as monitored quality of service, addressing the needs of both, users and system providers. The platform operates solely on the resources of the users, eliminating the concentration of crucial operational costs for one provider. In a testbed evaluation, we show the feasibility of the approach and point out the potential of the p2p paradigm in the field of online social networks.
Choosing the right software for your research study : an overview of leading ...Merlien Institute
Choosing the right software for your research study : an overview of leading CAQDAS packages by Christina Silver. This presentation is part of the proceedings of the International workshop on Computer-Aided Qualitative Research organised by Merlien Institute. This workshop was held on the 4-5 June in Utrecht, The Netherlands
this technical note describes in details the funtionalities available in the Cross Media Finder (XMF) solution, the tool that alolow to set up Multichannel WebTV, IPTV VOD with Social Networking. Visit http://mobmed.axmedis.org and http://xmf.axmedis.org for real applications.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Integrating Ayurveda into Parkinson’s Management: A Holistic ApproachAyurveda ForAll
Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
- Video recording of this lecture in English language: https://youtu.be/kqbnxVAZs-0
- Video recording of this lecture in Arabic language: https://youtu.be/SINlygW1Mpc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
These lecture slides, by Dr Sidra Arshad, offer a quick overview of the physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar lead (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
6. Describe the flow of current around the heart during the cardiac cycle
7. Discuss the placement and polarity of the leads of electrocardiograph
8. Describe the normal electrocardiograms recorded from the limb leads and explain the physiological basis of the different records that are obtained
9. Define mean electrical vector (axis) of the heart and give the normal range
10. Define the mean QRS vector
11. Describe the axes of leads (hexagonal reference system)
12. Comprehend the vectorial analysis of the normal ECG
13. Determine the mean electrical axis of the ventricular QRS and appreciate the mean axis deviation
14. Explain the concepts of current of injury, J point, and their significance
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
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NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Colonic and anorectal physiology with surgical implications
Personal Content Management on PDA for Health Care Applications
1. Personal Content Management on
PDA for Health Care Applications
http://mobmed.axmedis.org
Pierfrancesco Bellini, Ivan Bruno, Daniele
Bellini Bruno
Cenni, Paolo Nesi, Michela Paolucci
DISIT Lab: Sistemi Distribuiti e Tecnologie Internet
Dipartimento di Sistemi e Informatica
Università degli Studi di Firenze
nesi@dsi.unifi.it, http://www.disit.dsi.unifi.it
SCMS, Berkeley, CA, USA, Sept. 2009 1
2. Outline
Scenarios
Mobile Medicine Content Examples
Content Access and technical requirements
Intelligent content
AXMEDIS format and model
The architecture of Mobile Medicine
PDA Organizer for content
Mobile Medicine: Content production
Conclusions
SCMS, Berkeley, CA, USA, Sept. 2009 2
3. Scenarios of Mobile Medicine
intelligent solution in the hands of doctors and
assistants for:
Continuous Medical Educations, CME, during the
doctor life and continuous update;
Calculation of dosages, status/conditions, risks,..
g , , ,
Education: medical University/School level;
Emergency help medical personnel to take
g y p p
decisions and remind procedures/protocols, etc.;
Collect data from patients that cannot be easily collected
p y
or that are too expensive to be collected with mobile
instruments; ;
EPR: Electronic Patient Record report, excerpts
Simple, usable and accessible OFF-LINE
p ,
SCMS, Berkeley, CA, USA, Sept. 2009 3
4. Mobile Medicine: Content examples
Content Examples:
Educational:
Sliding Shows, video, document, audio, images…
Procedures/protocols: (mini applications)
Emergency, routines,
Emergency routines …
Dosages for intensive therapy: (mini applications)
Formulas, ranges,
Formulas ranges different application cases
Calculators for several aspects: (mini applications)
Risk analysis, …e.g.: pulmonary emboli….
Classification of conditions/damages, …
Needs of customizing:
user interface, behavior, accessibility rights, etc.
SCMS, Berkeley, CA, USA, Sept. 2009 4
6. Mobile Medicine Content Access
Collect content on their mobile device, PDA
Access to personal collection in any conditions
Navigate into the ll ti
N i t i t th collection via several views:
i l i
medical, taxonomy, classif., description, etc.
Use data based: less used, most, recent, etc.
Querying into the collection
Keep updated the content collection automatically
Keep the same content accessible on PC/PDA
Licensing and rights controls to access and use
(patience info and/or record)
SCMS, Berkeley, CA, USA, Sept. 2009 6
7. Technical Content Requirements
have to be indexed with all its metadata and semantic information
into the local d t b
i t th l l database
may arrive into the device via any channel and solution
has to be automatically updated into the device without the user
intervention
may present links with other content elements
may change behavior on the basis of
user preferences/profile, device capabilities, network capabilities, general
context description device status
description,
may request to user to provide info;
e.g.: collection of patient data perform actions on a checklists do
data, checklists,
annotations, to create a multimedia scrapbooks, to provide user
generated content, etc
may communicate with some central server some messages;
i t ith t l
for example: to mark that a content segment has been completed, report
obtained data, decision taken, or possibilities browsed, ..
SCMS, Berkeley, CA, USA, Sept. 2009 7
8. Intelligent Content
g
A number of cross media content formats: SCORM,
MXF, NewsML, MPEG-21, Flash, HTML, etc.
Major Issues for cross media content (DMS 2008):
Packaging: Metadata and descriptors + essences
Distribution: d
Di ib i download, streaming, progressive, P2P
l d i i P2P,..
Hierarchical nesting levels: IPR, Metadata, etc.
g
Intelligence: profiling, decision, scripting
Tools: Players and Authoring tools
Automated production, repurposing, delivering
Protection: CAS vs DRM
…
. SCMS, Berkeley, CA, USA, Sept. 2009
8
9. Interactive and intelligent content Final users
Browse, search
New content formats
New TV formats User generated
p
proactive
integrated media info
Multichannel
p
proactive with the
users
attractive experience
personalized User generated
multichannel
interoperable Saving experience
device interoperable
p
9
10. AXMEDIS Object/Package Model
unique content description
identification mandatory special B2B metadata
AxOID + …. AxInfo
AxDublinCore
A D bli C
AxMetadata
AxMetadata
AxMetadata
AxObject
AxMetadata
AxMetadata
AxContent
AxResource
MPEG21 AxMetadata
Digital Item
Di it l It
AxMetadata
AxMethods AxObject
resource embedding AxReferred
hierarchical composition
external content referencing Object
j
Intelligent, l i & b h i
I t lli t logic behavior AxMethods
A M th d
10
11. Examples: Intelligent Content
Single Files:
audio, video, documenti,
immages, etc..
Interactive Content:
HTML or SMIL as technology of
User interaction
Guides, games, etc.
Valoriz. of Cultural Heritage
content
Educational Content
Proactive Wizard:
Video messg. Recording, UGC
Assisted upload
Production of licenses
User profile processing
Taking decision
Local indexing/searching
Local assistant
….
11
12. AXMEDIS/MPEG 21
AXMEDIS/MPEG-21
Structure: hierarchical, links, etc.
Distribution: download, p2p, progressive, stream
Classification: DC, taxonomy, any MD, descriptors
y y p
Identification: any IDs, for DRM AXOID
Behavior: change on the basis of context descriptors
context, descriptors,
axmethod code
Processing: axmethod as in the AXCP plugins
AXCP, plugins,..
Presentational/interaction: SMIL, MPEG-4, HTML, …
Activation of methods, forms,
methods forms
File format: direct play without unpack of video, ….
DRM/prot via MPEG 21 models and AXMEDIS implementation
DRM/ t i MPEG-21 d l d i l t ti
Annotations: possible
SCMS, Berkeley, CA, USA, Sept. 2009 12
13. Mobile Medicine
Automated
Back office
-PC, MACos, linux, …
-iPhone, iPod,
Windows Mobile,
Android(*), ….
Complex content
SCMS, Berkeley, CA, USA, Sept. 2009 13
14. Mobile Medicine
AXCP Quick Start,
Monitoring &
g
Your
Yo r tools commands,
commands Reporting
Workflow systems,… AXMEDIS
DRM Server
AXCP GRID Internet, WEB,
VOD, POD..
AXCP Scheduler
Mobile Medicine
databases AXCP Node WEB Server
AXCP Node for PC and Mobile,
FTP, WS, etc.
Content Upload
AXCP Node Mobiles, PDA, etc.
AXMEDIS AXCP GRID backoffice server: semantic computing p g
AXMEDIS DRM: for Rights control and security
Mobile Medicine portal for the multichannel distribution:
p
PC, PDA, iPhone, iPod, mobile, etc.
Production tools and players, for PC and PDA
SCMS, Berkeley, CA, USA, Sept. 2009 14
15. Personal Mobile Social Intelligence
AxObjectFinder
HTML & CSS Based Presentation Engine AxPDAPlayer
Media Player
/updateM
Search Engine
owser
havior
orer
PDF player
ion
ual
my
collection
File Explo
Local Bro
User Beh
Download/
Taxonom
Contextu
informati
E
Browser
anager
….. player
Content Indexer, semantic ingestion/processing
Local PDA SQLite DB
files
SCMS, Berkeley, CA, USA, Sept. 2009
15
16. Semantic flows
•User Profile •Local User Profile
•User behavior •Local User behavior
•Use data •Local Use data + Content
•Content •Content action data
•DC+IDs
DC ID •DC+IDs
DC ID
•AXInfo: ver, •AXInfo: ver, prod,
prod., rights,.. rights, ....
•Descriptors •Descriptors
•Taxonomy •Taxonomy
G p
•Groups •Groups
G p
•Recommendation •Local Recommendation
•Suggestions on the •Local Suggestions on the
basis of user behavior basis of user behavior and
local content
SCMS, Berkeley, CA, USA, Sept. 2009 16
17. Conclusions
Accessible since June 2009
Several objects and mini-applications,
calculators for dosages verification etc
dosages, verification, etc.
Intelligent Content Organizer for PDA WM5/6
Medical taxonomy allows to make navigation into
content
local recommendations
Offline/online
iPhone supported via
regular portal, only
for online
SCMS, Berkeley, CA, USA, Sept. 2009 17
18. Content Production
Automated
User: backoffice:
upload/propose Transcode, adapt,
..
Single file content
directly
ADMIN, validate,
send in
publication
User: study and
design complex
content, then
upload
Produce the
complex content
with authoring tool
SCMS, Berkeley, CA, USA, Sept. 2009 18
20. Some references
Mobile Medicine: http://mobmed.axmedis.org
p g
Manuale: http://mobmed.axmedis.org/Mobile-Medicine-Manual.pdf
Development and production tools
AXMEDIS: http://www.axmedis.org
Report and documentation, development tools and demos
DISIT L b U i Fi
Lab, Univ. Firenze, DSI: htt //
DSI http://www.disit.dsi.unifi.it/
di it d i ifi it/
P. Bellini, I. Bruno, A. Fuzier, P. Nesi, M. Paolucci, “Semantic Processing and
Management for MultiChannel Cross Media Social Networking”, NEM
g g,
conference, Saint Malo, France, September 2009.
----this paper----: P. Bellini, I. Bruno, D. Cenni, P. Nesi, M. Paolucci,
"Personal Content Management on PDA for Health Care Applications" 2009
Applications",
IEEE International Workshop on Semantic Computing and Multimedia
Systems (IEEE-SCMS 2009), Berkeley, CA, USA - September 14-16, 2009
Congresso SIAARTI, Firenze, Agosto 2009 20
21. Personal Content Management on
PDA for Health Care Applications
http://mobmed.axmedis.org
Pierfrancesco Bellini, Ivan Bruno, Daniele
Bellini Bruno
Cenni, Paolo Nesi, Michela Paolucci
DISIT Lab: Sistemi Distribuiti e Tecnologie Internet
Dipartimento di Sistemi e Informatica
Università degli Studi di Firenze
nesi@dsi.unifi.it, http://www.disit.dsi.unifi.it
SCMS, Berkeley, CA, USA, Sept. 2009 21