A Web-based Adaptive and Intelligent Tutor by Expert Systems

Todays, Intelligent and web-based E-learning is one of regarded topics. So researchers are trying to optimize and expand its application in the field of education. The aim of this paper is developing of E-learning software which is customizable, dynamic, intelligent and adaptive with Pedagogy view for learners in intelligent schools. This system is an integration of adaptive web-based E-learning with expert systems as well. Learning process in this system is as follows. First intelligent tutor determines learning style and characteristics of learner by a questionnaire and then makes his model. After that the expert system simulator plans a pre-test and then calculates his score. If the learner gets the required score, the concept will be trained. Finally the learner will be evaluated by a post-test. The proposed system can improves the education efficiency highly as well as de-creases the costs and problems of an expert tutor. As a result, every time and eve-rywhere (ETEW) learning would be provided via web in this system. Moreover the learners can enjoy a cheap remote learning even at home in a virtual simulated physical class. So they can learn thousands courses very simple and fast.Comment: 10 pages, 3 figures, The Second International Conference on Advances in Computing and Information Technology (ACITY 2012). arXiv admin note: substantial text overlap with arXiv:1304.404

Effects of oxidized low density lipoprotein, lipid mediators and statins on vascular cell interactions

The integrin heterodimer CD11b/CD18 (alpha M beta 2, Mac-1, CR3) expressed on monocytes or polymorphonuclear leukocytes (PMN) is a receptor for iC3b, fibrinogen, heparin, and for intercellular adhesion molecule (ICAM)-1 on endothelium, crucially contributing to vascular cell interactions in inflammation and atherosclerosis. In this report, we summarize our findings on the effects of lipid mediators and lipid-lowering drugs. Exposure of endothelial cells to oxidized low density lipoprotein (oxLDL) induces upregulation of ICAM-1 and increases adhesion of monocytic cells expressing Mac-1. Inhibition experiments show that monocytes use distinct ligands, i.e. ICAM-1 and heparan sulfate proteoglycans for adhesion to oxLDL-treated endothelium. An albumin-transferable oxLDL activity is inhibited by the antioxidant pyrrolidine dithiocarbamate (PDTC), while 8-epi-prostaglandin F2 alpha (8-epi-PGF2 alpha) or lysophosphatidylcholine had no effect, implicating yet unidentified radicals. Sequential adhesive! and signaling events lead to the firm adhesion of rolling PMN on activated and adherent platelets, which may occupy areas of endothelial denudation. Shear resistant arrest of PMN on thrombin-stimulated platelets in flow conditions requires distinct regions of Mac-1, involving its interactions with fibrinogen bound to platelet alpha llb beta 3, and with other platelet ligands. Both arrest and adhesion strengthening under flow are stimulated by platelet-activating factor and leukotriene B4, but not by the chemokine receptor CXCR2. We tested whether Mac-1-dependent monocyte adhesiveness is affected by inhibitors of hydroxy-methylglutaryl-Coenzyme A reductase (statins) which improve morbidity and survival of patients with coronary heart disease. As compared to controls, adhesion of isolated monocytes to endothelium ex vivo was increased in patients with hypercholesterolemia. Treatment with statins decreased total and low density lipoprotein (LDL) cholesterol plasma levels, surface expression of Mac-1, and resulted in a dramatic reduction of Mac,mediated monocyte adhesion to endothelium. The inhibition of monocyte adhesion was reversed by mevalonate but not LDL in vitro,indicating that isoprenoid precursors are crucial for adhesiveness of Mac-1. Such effects may crucially contribute to the clinical benefit of statins, independent of cholesterol-lowering, and may represent a paradigm for novel, anti-inflammatory mechanisms of action by this class of drugs

On the properties of massive Population III stars and metal-free stellar populations

We present realistic models for massive Population III stars and stellar populations based on non-LTE model atmospheres, recent stellar evolution tracks and up-to-date evolutionary synthesis models, to study their spectral properties, including their dependence on age, star formation history, and IMF. (..) The main results regarding integrated stellar populations are: * For young bursts and the case of a constant SFR, nebular continuous emission - neglected in previous studies - dominates the spectrum redward of Lyman-alpha (...). Therefore predicted emission line equivalent widths are considerably smaller than found in earlier studies, whereas the detection of the continuum is eased. Nebular line and continuous emission strongly affect the broad band photometric properties of Pop III objects. * Due to stellar evolution, the hardness of the ionising spectrum decreases rapidly, leading to the disappearance of the characteristic HeII 1640 recombination lines after ~ 3 Myr in instantaneous bursts. * The relative efficiency of ionising photon energy to heavy element rest mass production, eta, of metal-poor and metal-free populations is increased by factors of ~ 4 to 18 with respect to solar metallicity and for ``standard'' IMFs. * The lowest values of eta ~ 1.6 - 2.2 % are obtained for IMFs exclusively populated with high mass stars (M_low >~ 50 Msun). If correct, the yields dominated by pair creation SNae then predict large overabundances of O/C and Si/C compared to solar abundance ratios. Detailed results are given in tabular form and as fit formulae for implementation in other calculations. (abridged abstract)Comment: Accepted for publication in A&A. LaTeX, 15 pages including 8 figures. Related models are available at http://webast.ast.obs-mip.fr/people/schaerer/ . SEDs will be available by request from the author (mailto:[email protected]). Y-axis of Figs. 5 correcte

How Can Progress Toward Ending the Human Immunodeficiency Virus Epidemic in the United States Be Monitored?

The plan for Ending the HIV (human immunodeficiency virus) Epidemic (EHE) in the United States aims to reduce new infections by 75% by 2025 and by 90% by 2030. For EHE to be successful, it is important to accurately measure changes in numbers of new HIV infections after 5 and 10 years (to determine whether the EHE goals have been achieved) but also over shorter timescales (to monitor progress and intensify prevention efforts if required). In this viewpoint, we aim to demonstrate why the method used to monitor progress toward the EHE goals must be carefully considered. We briefly describe and discuss different methods to estimate numbers of new HIV infections based on longitudinal cohort studies, cross-sectional incidence surveys, and routine surveillance data. We particularly focus on identifying conditions under which unadjusted and adjusted estimates based on routine surveillance data can be used to estimate changes in new HIV infections

The monoclonal antibody EPR1614Y against the stem cell biomarker keratin K15 lacks specificity and reacts with other keratins

Keratin 15 (K15), a type I keratin, which pairs with K5 in epidermis, has been used extensively as a biomarker for stem cells. Two commercial antibodies, LHK15, a mouse monoclonal and EPR1614Y, a rabbit monoclonal, have been widely employed to study K15 expression. Here we report differential reactivity of these antibodies on epithelial cells and tissue sections. Although the two antibodies specifically recognised K15 on western blot, they reacted differently on skin sections and cell lines. LHK15 reacted in patches, whereas EPR1614Y reacted homogenously with the basal keratinocytes in skin sections. In cultured cells, LHK15 did not react with K15 deficient NEB-1, KEB-11, MCF-7 and SW13 cells expressing only exogenous K8 and K18 but reacted when these cells were transduced with K15. On the other hand, EPR1614Y reacted with these cells even though they were devoid of K15. Taken together these results suggest that EPR1614Y recognises a conformational epitope on keratin filaments which can be reconstituted by other keratins as well as by K15. In conclusion, this report highlights that all commercially available antibodies may not be equally specific in identifying the K15 positive stem cell

High-quality health systems in the Sustainable Development Goals era: time for a revolution.

Executive summary: Although health outcomes have improved in low-income and middle-income countries (LMICs) in the past several decades, a new reality is at hand. Changing health needs, growing public expectations, and ambitious new health goals are raising the bar for health systems to produce better health outcomes and greater social value. But staying on current trajectory will not suffice to meet these demands. What is needed are high-quality health systems that optimise health care in each given context by consistently delivering care that improves or maintains health, by being valued and trusted by all people, and by responding to changing population needs. Quality should not be the purview of the elite or an aspiration for some distant future; it should be the DNA of all health systems. Furthermore, the human right to health is meaningless without good quality care because health systems cannot improve health without it. We propose that health systems be judged primarily on their impacts, including better health and its equitable distribution; on the confidence of people in their health system; and on their economic benefit, and processes of care, consisting of competent care and positive user experience. The foundations of high-quality health systems include the population and their health needs and expectations, governance of the health sector and partnerships across sectors, platforms for care delivery, workforce numbers and skills, and tools and resources, from medicines to data. In addition to strong foundations, health systems need to develop the capacity to measure and use data to learn. High-quality health systems should be informed by four values: they are for people, and they are equitable, resilient, and efficient. For this Commission, we examined the literature, analysed surveys, and did qualitative and quantitative research to evaluate the quality of care available to people in LMICs across a range of health needs included in the Sustainable Development Goals (SDGs). We explored the ethical dimensions of high-quality care in resource-constrained settings and reviewed available measures and improvement approaches. We reached five conclusions: The care that people receive is often inadequate, and poor-quality care is common across conditions and countries, with the most vulnerable populations faring the worst Data from a range of countries and conditions show systematic deficits in quality of care. In LMICs, mothers and children receive less than half of recommended clinical actions in a typical preventive or curative visit, less than half of suspected cases of tuberculosis are correctly managed, and fewer than one in ten people diagnosed with major depressive disorder receive minimally adequate treatment. Diagnoses are frequently incorrect for serious conditions, such as pneumonia, myocardial infarction, and newborn asphyxia. Care can be too slow for conditions that require timely action, reducing chances of survival. At the system level, we found major gaps in safety, prevention, integration, and continuity, reflected by poor patient retention and insufficient coordination across platforms of care. One in three people across LMICs cited negative experiences with their health system in the areas of attention, respect, communication, and length of visit (visits of 5 min are common); on the extreme end of these experiences were disrespectful treatment and abuse. Quality of care is worst for vulnerable groups, including the poor, the less educated, adolescents, those with stigmatised conditions, and those at the edges of health systems, such as people in prisons. Universal health coverage (UHC) can be a starting point for improving the quality of health systems. Improving quality should be a core component of UHC initiatives, alongside expanding coverage and financial protection. Governments should start by establishing a national quality guarantee for health services, specifying the level of competence and user experience that people can expect. To ensure that all people will benefit from improved services, expansion should prioritise the poor and their health needs from the start. Progress on UHC should be measured through effective (quality-corrected) coverage. High-quality health systems could save over 8 million lives each year in LMICs More than 8 million people per year in LMICs die from conditions that should be treatable by the health system. In 2015 alone, these deaths resulted in US$6 trillion in economic losses. Poor-quality care is now a bigger barrier to reducing mortality than insufficient access. 60% of deaths from conditions amenable to health care are due to poor-quality care, whereas the remaining deaths result from non-utilisation of the health system. High-quality health systems could prevent 2·5 million deaths from cardiovascular disease, 1 million newborn deaths, 900 000 deaths from tuberculosis, and half of all maternal deaths each year. Quality of care will become an even larger driver of population health as utilisation of health systems increases and as the burden of disease shifts to more complex conditions. The high mortality rates in LMICs for treatable causes, such as injuries and surgical conditions, maternal and newborn complications, cardiovascular disease, and vaccine preventable diseases, illustrate the breadth and depth of the health-care quality challenge. Poor-quality care can lead to other adverse outcomes, including unnecessary health-related suffering, persistent symptoms, loss of function, and a lack of trust and confidence in health systems. Waste of resources and catastrophic expenditures are economic side effects of poor-quality health systems. As a result of this, only one-quarter of people in LMICs believe that their health systems work well. Health systems should measure and report what matters most to people, such as competent care, user experience, health outcomes, and confidence in the system Measurement is key to accountability and improvement, but available measures do not capture many of the processes and outcomes that matter most to people. At the same time, data systems generate many metrics that produce inadequate insight at a substantial cost in funds and health workers' time. For example, although inputs such as medicines and equipment are commonly counted in surveys, these are weakly related to the quality of care that people receive. Indicators such as proportion of births with skilled attendants do not reflect quality of childbirth care and might lead to false complacency about progress in maternal and newborn health. This Commission calls for fewer, but better, measures of health system quality to be generated and used at national and subnational levels. Countries should report health system performance to the public annually by use of a dashboard of key metrics (eg, health outcomes, people's confidence in the system, system competence, and user experience) along with measures of financial protection and equity. Robust vital registries and trustworthy routine health information systems are prerequisites for good performance assessment. Countries need agile new surveys and real-time measures of health facilities and populations that reflect the health systems of today and not those of the past. To generate and interpret data, countries need to invest in national institutions and professionals with strong quantitative and analytical skills. Global development partners can support the generation and testing of public goods for health system measurement (civil and vital registries, routine data systems, and routine health system surveys) and promote national and regional institutions and the training and mentoring of scientists. New research is crucial for the transformation of low-quality health systems to high-quality ones Data on care quality in LMICs do not reflect the current disease burden. In many of these countries, we know little about quality of care for respiratory diseases, cancer, mental health, injuries, and surgery, as well as the care of adolescents and elderly people. There are vast blind spots in areas such as user experience, system competence, confidence in the system, and the wellbeing of people, including patient-reported outcomes. Measuring the quality of the health system as a whole and across the care continuum is essential, but not done. Filling in these gaps will require not only better routine health information systems for monitoring, but also new research, as proposed in the research agenda of this Commission. For example, research will be needed to rigorously evaluate the effects and costs of recommended improvement approaches on health, patient experience, and financial protection. Implementation science studies can help discern the contextual factors that promote or hinder reform. New data collection and research should be explicitly designed to build national and regional research capacity. Improving quality of care will require system-wide action To address the scale and range of quality deficits we documented in this Commission, reforming the foundations of the health system is required. Because health systems are complex adaptive systems that function at multiple interconnected levels, fixes at the micro-level (ie, health-care provider or clinic) alone are unlikely to alter the underlying performance of the whole system. However, we found that interventions aimed at changing provider behaviour dominate the improvement field, even though many of these interventions have a modest effect on provider performance and are difficult to scale and sustain over time. Achieving high-quality health systems requires expanding the space for improvement to structural reforms that act on the foundations of the system. This Commission endorses four universal actions to raise quality across the health system. First, health system leaders need to govern for quality by adopting a shared vision of quality care, a clear quality strategy, strong regulation, and continuous learning. Ministries of health cannot accomplish this alone and need to partner with the private sector, civil society, and sectors outside of health care, such as education, infrastructure, communication, and transport. Second, countries should redesign service delivery to maximise health outcomes rather than geographical access to services alone. Primary care could tackle a greater range of low-acuity conditions, whereas hospitals or specialised health centres should provide care for conditions, such as births, that need advanced clinical expertise or have the risk of unexpected complications. Third, countries should transform the health workforce by adopting competency-based clinical education, introducing training in ethics and respectful care, and better supporting and respecting all workers to deliver the best care possible. Fourth, governments and civil society should ignite demand for quality in the population to empower people to hold systems accountable and actively seek high-quality care. Additional targeted actions in areas such as health financing, management, district-level learning, and others can complement these efforts. What works in one setting might not work elsewhere, and improvement efforts should be adapted for local context and monitored. Funders should align their support with system-wide strategies rather than contribute to the proliferation of micro-level efforts. In this Commission, we assert that providing health services without guaranteeing a minimum level of quality is ineffective, wasteful, and unethical. Moving to a high-quality health system—one that improves health and generates confidence and economic benefits—is primarily a political, not technical, decision. National governments need to invest in high-quality health systems for their own people and make such systems accountable to people through legislation, education about rights, regulation, transparency, and greater public participation. Countries will know that they are on the way towards a high-quality, accountable health system when health workers and policymakers choose to receive health care in their own public institutions.Fil: Kruk, Margaret E.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Gage, Anna D.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Arsenault, Catherine. Harvard University. Harvard School of Public Health; Estados UnidosFil: Jordan, Keely. New York College of Global Public Health; Estados UnidosFil: Leslie, Hannah H.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Roder DeWan, Sanam. Harvard University. Harvard School of Public Health; Estados UnidosFil: Adeyi, Olusoji. Banco Mundial; Estados UnidosFil: Barker, Pierre. Institute For Healthcare Improvement; Estados UnidosFil: Daelmans, Bernadette. Organizacion Mundial de la Salud; SuizaFil: Doubova, Svetlana V.. Instituto Mexicano del Seguro Social; MéxicoFil: English, Mike. KEMRI - Wellcome Trust; KeniaFil: Garcia Elorrio, Ezequiel. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Guanais, Frederico. Banco Interamericano de Desarrollo; Estados UnidosFil: Gureje, Oye. University Of Ibadan; NigeriaFil: Hirschhorn, Lisa R.. Northwestern University; Estados UnidosFil: Jiang, Lixin. National Center For Cardiovascular Diseases; ChinaFil: Kelley, Edward. Organizacion Mundial de la Salud; SuizaFil: Lemango, Ephrem Tekle. Federal Ministry of Health; EtiopíaFil: Liljestrand, Jerker. Bill and Melinda Gates Foundation; Estados UnidosFil: Malata, Address. Malawi University Of Science And Technology; MalauiFil: Marchant, Tanya. London School of Hygiene & Tropical Medicine; Reino UnidoFil: Matsoso, Malebona Precious. National Department of Health of the Republic of South Africa; SudáfricaFil: Meara, John G.. Harvard Medical School; Estados UnidosFil: Mohanan, Manoj. University of Duke; Estados UnidosFil: Ndiaye, Youssoupha. Ministry of Health and Social Action of the Republic of Senegal; SenegalFil: Norheim, Ole F.. University of Bergen; NoruegaFil: Reddy, K. Srinath. Public Health Foundation of India; IndiaFil: Rowe, Alexander K.. Centers for Disease Control and Prevention; Estados UnidosFil: Salomon, Joshua A.. Stanford University School Of Medicine; Estados UnidosFil: Thapa, Gagan. Legislature Parliament Of Nepal; NepalFil: Twum Danso, Nana A. Y.. Maza; GhanaFil: Pate, Muhammad. 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