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Our Grandkids May Be Born From 3. D- Printed Ovaries. Fertility has become a major target for regenerative medicine. What if, the thinking goes, science and medicine could be used to simply restore fertility to women who for one reason or another no longer have it? In mice, scientists have now done just that. In a new paper out Tuesday in Nature Communications, scientists at Northwestern University report that they successfully removed a mouse’s ovary and replaced it with a 3. D- printed one made from its own ovarian follicles. What’s more, using those bioprosthetic ovaries, the mice were able to ovulate just like normal, mate, give birth to healthy mouse pups, and even nurse them. But that’s not even the coolest part. In recent years, other scientists have actually pulled off this feat in mice using 3. D- printing a few times. But human ovaries are a lot bigger and more complicated than mouse ovaries, and there has been concern that the material and method of constructing the ovaries wouldn’t hold up if you tried the same thing in people. They also found that the pattern in which the new ovary was printed had a significant impact on whether the ovary prosthesis actually worked. Hoy una buena noticia me pasan desde File4Safe, el cual acepta nuevos métodos de pago, entre ellos el mas importante para todo sur américa y del cual todos se dan. UpdateStar is compatible with Windows platforms. UpdateStar has been tested to meet all of the technical requirements to be compatible with Windows 10, 8.1, Windows 8. Offers 50 GB of free storage space. Uploaded files are encrypted and only the user holds the decryption keys. Here’s how it works: Scientists removed mouse ovaries in order to sterilize them, then preserved the ovarian tissue and isolated its hormone- producing cells that support immature eggs. Using a 3. D- printer and gelatin, they then printed the basic structure of the ovary, and dosed it with the cultured ovarian follicles. These ovaries were then surgically transplanted back into the mice, where their egg cells then began to mature and ovulate. Blood vessels formed that allowed hormones to circulate within the mouse bloodstream to take care of all the other parts of pregnancy, like lactating after birth. And eventually, the mice gave birth to pups. The pups were also engineered to glow, as a way to keep track of which ones were born from mothers with the bioprosthetic organs. Woodruff said that the ultimate goal was not just to allow women to get pregnant, but to restore the total health of a woman’s endocrine system. It’s part of the overall system of a woman’s health.”There is a lot of interest in using cutting edge technology to restore and improve fertility—and a lot of crazy plans for how to do it. Woodruff’s work, though, may be one of the most realistic approaches yet. The Lego sets I want to focus on are 1977's 853-1 Car Chassis set, one of their firstAlready, it has been proven to work in mice several times over. At this point, much of what’s needed is hammering out the details of how it will best translate to people. Woodruff hopes to address some of the challenges—like finding a method of printing that creates the best chances of the egg cells maturing, and a material that will create a durable organ that lasts in humans. Woodruff’s lab has been on the hairy edge of fertility technology several times over. Offers news on console related development, downloads, reviews, tutorials, and forums. You have not yet voted on this site! If you have already visited the site, please help us classify the good from the bad by voting on this site. The biggest totally free game fix & trainer library online for PC Games Tropical Storm Don, a weakening system that’s now approaching the Windward Islands (Image via Weather Underground) Meteorologists are currently tracking a pair of. Earlier this year, her lab use tissue cultures to create a miniature 3. D model of the female reproductive tract, a “period in a dish.” And they have successfully grown immature egg cells into mature ones in a lab. Federal funding rules have prevented her from taking that research any further and fertilizing the egg to see how it continues to develop, but she’s seeking non- government funding to continue it. The lab’s work will next be tested in pigs, and there is a fair amount of work to be done before its ready for humans. But, Woodruff says, that won’t be too far in the future. Manual de Hiren’s Boot CD: Herramientas para reparar computadoras. Partes del manual de Hiren’s Boot CD. La primera opci. Por otra parte, la segunda opci. 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How to create PDF from Microsoft Word / How to convert DOC to PDFHow to create PDF from Microsoft Word / How to convert DOC to PDF1. Start Microsoft Word. Open a . DOC document (or . DOCx document, which is introduced since.
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We have selected one representative from every input class to design our test cases. Test case values are selected in such a way that largest number of attributes of equivalence class can be exercised. Equivalence partitioning uses fewest test cases to cover maximum requirements. Boundary value analysis: It’s widely recognized that input values at the extreme ends of input domain cause more errors in system. More application errors occur at the boundaries of input domain. You can select multiple valid and invalid values from each equivalence class according to your needs and previous judgments. E. g. Same case for other test cases having invalid data classes. This should be a very basic and simple example to understand the Boundary value analysis and Equivalence partitioning concept. Share your examples below. Interactive Curriculum Based on Models of Mind & Brain. Brains, Minds & Media. Along with research in basic science, the Center for Excellence in Education, Science, and Technology (CELEST) . How our minds work is a great interest to students of all ages as part of their self- discovery; however, models of mind and brain are not incorporated into science and mathematics curriculum for primary and secondary students. CELEST innovations are intended to create a long- term impact on knowledge, research, policy, and practice in the learning sciences. CELEST is solving fundamental problems of learning by integrating experimental and computational brain science, biologically inspired technology, and classroom innovation. The focus of this paper is to describe progress made in curriculum development since the Center's inception as a National Science Foundation Science of Learning Center . The software and support materials are in development and available at http: //cns. Interested parties are invited to contact the author for access. The curriculum is interactive in a number of dimensions. Modules are developed in layers, with the first requiring no specialized previous knowledge. Subsequent layers introduce more advanced materials in a self- contained way. CELEST curriculum supports inquiry- based active learning; discussion, experiment, data collection and analysis, and modeling are integrated to help students achieve a deep understanding of both content and pedagogy. Students learn specific content in science and mathematics related to how they learn, identify and address subject- specific misconceptions, and develop the ability to apply knowledge to new situations. One might expect that the software has to be competitive with commercial games in order to hold the interest of students because they would have high expectations based on their experience with commercial games. However, simple interactive software about perception, cognition, action and emotion motivates students to learn about themselves and others. In addition, the same learning tools can be used to teach practicing scientists and other adult learners about interdisciplinary mind- brain research. CELEST curriculum is designed with two goals in mind. First, develop curriculum materials that can be directly used not only to satisfy present curriculum requirements, but also to employ exciting new examples derived from models and data about mind and brain. These modules may be presented in larger curriculum units, encompassing one or more classes, depending upon the curriculum material that is being augmented. We call the latter materials . Both sorts of modules might inspire students to learn more mathematics and science, and to enter previously unconsidered careers, including careers in science and teaching. In addition, various courses in CELEST departments at the university level are being revised or created to include new material about models of learning. Each curriculum module is designed to fulfill several situation scenarios . CELEST curriculum has been developed with an explicit alignment to the principles discussed in How People Learn: Brain, Mind, Experience, and School . Using CELEST curriculum, students will think about how they learn. Indeed, the process of thinking about thinking is a cornerstone of modeling mind and brain; while experimental data often suggest or validate a particular model, thought- experiments also give rise to models or to modifications of them. Besides supporting teachers and students who appreciate how brain affects behavior and behavior affects brain, CELEST educational objectives include the development of a new generation of scientists who participate in learning research and educational outreach (scientist- educators). A key element of this integration is the CELEST incubator course project: as part of their coursework, graduate students develop classroom, textbook, and web- based educational materials for future incorporation into CELEST curriculum. In addition, graduate students and post- docs have worked on the modules outside of class for sustained periods of time. Along with input from faculty, this is a top- down approach to curriculum development; in other words, the content of the curriculum follows research. CELEST curriculum is universally relevant and readily transferred to everyday experience; however, the key to its acceptance and utility will be its fit to the intended audience. Calibrated to the skill level of the intended audience, CELEST curricula include interdisciplinary information that unifies behavioral data, brain data, theoretical concepts, mathematical models, and computational methods. Extensive field tests by teachers and students interacting with the curriculum are necessary before the educational materials are distributed on the web and used systematically in classrooms. This is a bottom- up approach to curriculum development. Planned formal research on CELEST educational materials should lead to results that will help to improve classroom practice; for example, an impact on student learning and study skills. In field trials, CELEST curriculum has already excited and motivated students to learn about and become more conscious of themselves and others. Future activity might include pre- service programs for prospective teachers, field- days for learning about mind and brain, and integration with museum exhibits. CELEST has and will continue to host workshops for secondary teachers and undergraduate teaching faculty. These programs have included research experiences for teachers, summer undergraduate research fellowships, and a summer program for Boston- area minority high- school students. CELEST is continuing to develop educational modules in conjunction with middle and high school math and science teachers. The effort began two years ago: five teachers participated in 8- week summer programs in 2. During the two- week workshop . During the second week, they engaged in a “How People Learn” workshop, and developed lesson plans that adapted CELEST curriculum for use in their classrooms. Curriculum Development: Interim Results. The modules under development are focused on perception, cognition, emotion and action. Since nearly half of the brain is dedicated to visual processing, Brightness Lab begins the systematic study of vision. Given a goal, how do we decide to move as a reaction to sensory (visual) input? Obstacle Avoidance Navigation explores the question of reactive movement as opposed to memory guided movement. We begin the exploration of memory and learning by studying Sequence Learning of numerical lists and continue through an examination of Recognition. Finally, since perception, action and cognition are all mediated by emotions, we begin to address them in the context of Associative Learning by studying adaptive timing to an aversive stimulus. After sufficient field- testing and revision based on feedback and research results, these modules will be released for general use on the CELEST main website at http: //cns. CELEST/. The following table lists the modules being tested in classrooms with a note naming the scientist- educator contributors (the modules are described in greater detail later): Curriculum module. Description. Brightness Lab . Through a study of visual illusions, normal perception, anatomy and physiology, this module teaches students about how we see bright and dark surfaces. Users perform a perceptual experiment in which they match the brightness of different regions on the screen and then analyze the results. A neural network model of brightness perception uses an ordinary differential equation to characterize the rate of change in neurons that leads to brightness perception. Students are guided through the construction of the neural network model using thought- experiments, an introduction to terminology, graphing symbols, and interactions among excitatory and inhibitory neural connections. Associative Learning . The ability to learn temporal conditioning is a critical survival competence because it enables the learning of which earlier events predict later consequences, as well as which event combinations are not causative. In this way, the individual can make the optimal choices for successful, adaptive behavior. Students begin with an experimental, interactive task that simulates aversive conditioning. Student performance data is presented in multiple formats for analysis. The module uses a neural network model eye- blink conditioning to develop a deeper understanding of the types of memory. Sequence Learning . This module studies the interaction of working memory and long- term memory related to temporal order processing. Students collect experimental data on their own working memory span, perform an analysis thereof, and test the negative effect of distractions and the positive effect of chucking on their memory span. There is also an opportunity to use an advanced neural network models of sequence learning. Other CELEST modules are in development but not yet ready for testing: Curriculum module. Description. Obstacle Avoidance . Given a goal, how do we decide to move as a reaction to sensory input? Navigation by humans often relies on an ability to visually detect where things are in the environment, and plan a path without colliding with obstacles. This module explores several aspects of obstacle avoidance navigation, using 2. D interactive software. Recognition . This module teaches students how humans and machines learn to recognize objects and events. Students categorize different vehicles in a “Cars” database while the computer uses specialized machine learning algorithms such as ARTMAP and KNN. Other databases and algorithms can be used in future. After building on previous knowledge by discussing appropriate challenge questions, and identifying and addressing misconceptions related to the topic, students conduct an experiment to collect data on their individual psychophysical data. Kelly is the second solo studio album by American recording artist Kelly Rowland. It was first released on June 20, 2007 by Columbia Records in collaboration with.Cent - The Kanan Tape. 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