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-- --------------------------------------------------------
-- Sunucu: 127.0.0.1
-- Sunucu sürümü: 10.1.24-MariaDB - mariadb.org binary distribution
-- Sunucu İşletim Sistemi: Win32
-- HeidiSQL Sürüm: 9.4.0.5125
-- --------------------------------------------------------
/*!40101 SET @OLD_CHARACTER_SET_CLIENT=@@CHARACTER_SET_CLIENT */;
/*!40101 SET NAMES utf8 */;
/*!50503 SET NAMES utf8mb4 */;
/*!40014 SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0 */;
/*!40101 SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE='NO_AUTO_VALUE_ON_ZERO' */;
-- proje2 için veritabanı yapısı dökülüyor
CREATE DATABASE IF NOT EXISTS `proje2` /*!40100 DEFAULT CHARACTER SET latin1 */;
USE `proje2`;
-- tablo yapısı dökülüyor proje2.blog
CREATE TABLE IF NOT EXISTS `blog` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`category_id` int(11) NOT NULL,
`title` varchar(255) COLLATE utf8_unicode_ci NOT NULL,
`slug` varchar(255) COLLATE utf8_unicode_ci NOT NULL,
`content` longtext COLLATE utf8_unicode_ci NOT NULL,
`created_at` datetime NOT NULL,
`updated_at` datetime NOT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `UNIQ_C0155143989D9B62` (`slug`),
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CONSTRAINT `FK_C015514312469DE2` FOREIGN KEY (`category_id`) REFERENCES `category` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=9 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci;
-- proje2.blog: ~0 rows (yaklaşık) tablosu için veriler indiriliyor
/*!40000 ALTER TABLE `blog` DISABLE KEYS */;
INSERT IGNORE INTO `blog` (`id`, `category_id`, `title`, `slug`, `content`, `created_at`, `updated_at`) VALUES
(1, 1, 'Math Shaped', 'math-shaped', 'To prepare a talk for the upcoming MathFest, to be held in Chicago this year, I was ruminating over articulating a clean-cut yet telling narrative. Since the talk subject is on ways to effectively outreach mathematics to general audience, it should at least somewhat bring up core concepts of mathematics. Somehow allude to the essentiality of its graphical and revelatory power, compared to just an instrument to calculate. Meaning mixing in subtler forms of advanced math, even abstract ones. I am sensitive to oversimplifying anything (my take on popular writing). It’s like providing a forced picture—like peas and potato analogy of quantum and cosmic realms in The Theory of Everything—that is far from an actual picture, and importantly dampened down on beauty, and inspiration. The point of outreach is to convey the subject—its significance and elegance that lay in the eyes of those who swim in it—not recite a lullaby. And in my experience audience from all backgrounds, even without math ones, show true enthusiasm only when prompted into intricate and advanced forms of mathematics, yearning for the real sense. It’s there where the real message is, of what mathematics actually is about.\r\n\r\nIn my experience outreaching an advanced scientific field effectively rests on two basic elements. First, tell it the way it is, don’t soften it. That’s the hard part because all those elaborate labyrinthine equations with functionalities, symbols, and notations floating all over them is the very thing that makes some of us flee. And thus the second, present them correlatively as physical entity: Numbers to space, Algebra to geometry, Calculus to continual smooth change, Groups and matrices to potentiality of abstract objects, the list is endless, and that physics itself at the core is mathematics. All those preposterous looking equations are actually quite beautiful and insinuating if you understand that those terms are the pieces of the landscape. The tangled appearance of an equation, like Dirac’s, would dwindle away once one sees what a colossal argument the equation is making.', '2017-07-08 01:13:54', '2017-07-08 01:13:54'),
(4, 2, 'World Transport Emissions On The Rise; Putting The Trend In Reverse', 'world-transport-emissions-on-the-rise-putting-the-trend-in-reverse', 'A growing population means increased mobility; no ifs, ands or buts about it. It’s a given.\r\n\r\nMobility – or more precisely, locomotion – is nothing more than place-to-place moving. And, mobility, at its most fundamental level, is no more complicated than putting one foot in front of the other.\r\n\r\nBut there is more to mobility than just this, obviously – so much more, in fact. And, of course there is the detrimental part – the impacts (collision/crash, congestion/gridlock, air-/noise- pollution aspects, just to name three) – connected to such; a side that goes hand in hand with and in which there seems to be no getting away from – at least not at this juncture, anyway.\r\n\r\n‘Houston: We have a problem!’\r\n\r\nThen there are effects like lower fuel prices coupled with other factors that have manifested themselves into a jump in driving. In fact, an increase of over 52 billion miles in 2016 over the prior-year figures in the United States, up from 3.148 trillion miles traveled in 2015 to more than 3.2 trillion driven miles last year.\r\n\r\nPer-capita driving miles rose too.\r\n\r\nThe overwhelming majority of the types of vehicles purchased coupled with increased driving is “driving” the “problem.” And the “problem,” well, that’s the harmful pollutant emissions aspect from this sector that are continuing to grow.\r\n\r\nThe Institute for Transportation and Development Policy and University of California at Davis in the collaboration’s “Three Revolutions in Urban Transportation” report raises the point that there are 764 million motor vehicles in the world today – more than three-fourths of a billion.\r\n\r\nMeanwhile, there are ideas galore on how or how best to reduce transport emissions. At the same time, whatever has been implemented to date, has had very limited effect, apparently. And, to reiterate once more, the emissions numbers from transportation keep growing.\r\n\r\nRising emissions from transportation\r\n\r\n“Greenhouse gas (GHG) emissions from the transport sector have more than doubled since 1970, and have increased at a faster rate than any other energy end-use sector to reach 7.0 Gt CO2eq in 2010. Around 80% of this increase has come from road vehicles. The final energy consumption for transport reached 28% of total end-use energy in 2010, of which around 40% was used in urban transport,” reported R. Sims, et al. in Climate Change 2014: Mitigation of Climate Change, “Chapter 8: Transport,” Executive Summary, section “8.1: Freight and passenger transport (land, air, sea and water),” p. 605 from the Intergovernmental Panel on Climate Change.1\r\n\r\nSignificantly reducing emissions from said sector will not be easy. But, the place to put the most effort and emphasis on that makes the most sense is road vehicles through behavioral changes, regulatory action and technological development.\r\n\r\nAs it relates, some of what was previously brought to bear in: “An air quality pep-talk primer: Transportation – a rallying cry, really,” bears repeating, and that is:\r\n\r\n“In some European nations and elsewhere, a hardline stance in addressing transpo. pollution is being taken. Limits, for instance, are being imposed on the number of polluting vehicles that are allowed to enter cities’ proper and the ones that are allowed are likely to be charged a fee if it is not that way already. Such action in Paris immediately comes to mind.\r\n\r\n“Getting automobilists to switch to cleaner forms of transportation or adopting the use of cleaner-burning fuels or even embracing notions like non-polluting electric- and fuel-cell-powered vehicles, by doing such, this will have a positive effect on air especially if there is a heightened reliance on such.\r\n\r\n“In the heavy-goods-movement department, putting more of the cargo on trains certainly has an air benefit; even more so when said trains are powered by cleanly (renewably) produced electricity. It is little different for trains carrying people. Improvement with respect to aviation and shipping is absolute; these are most certainly not exempt.”\r\n\r\nThese approaches and then some are all very worthy of serious consideration and it would seem the time is more than ripe for implementation action regarding such on a global scale. In other words, such is long overdue.\r\n\r\nNotes\r\n\r\nSims R., R. Schaeffer, F. Creutzig, X. Cruz-Núñez, M. D’Agosto, D. Dimitriu, M.J. Figueroa Meza, L. Fulton, S. Kobayashi, O. Lah, A. McKinnon, P. Newman, M. Ouyang, J.J. Schauer, D. Sperling, and G. Tiwari, 2014: Transport. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.', '2017-07-08 01:43:19', '2017-07-08 01:43:19'),
(5, 1, 'Neutrons Run Enzyme’s Reactivity For Better Biofuel Production', 'neutrons-run-enzymes-reactivity-better-biofuel-production', 'Producing biofuels like ethanol from plant materials requires various enzymes to break down the cellulosic fibers. Neutrons have identified the specifics of an enzyme-catalyzed reaction that could significantly reduce the total amount of enzymes used, improving production processes and lowering costs.\r\n\r\nResearchers from the Department of Energy’s Oak Ridge National Laboratory and North Carolina State University used a combination of X-ray and neutron crystallography to determine the detailed atomic structure of a specialized fungal enzyme. A deeper understanding of the enzyme reactivity could also lead to improved computational models that will further guide industrial applications for cleaner forms of energy. Their results are published in the journal Angewandte Chemie International Edition.\r\n\r\nPart of a larger family known as lytic polysaccharide monooxygenases, or LPMOs, these oxygen-dependent enzymes act in tandem with hydrolytic enzymes — which chemically break down large complex molecules with water — by oxidizing and breaking the bonds that hold cellulose chains together. The combined enzymes can digest biomass more quickly than currently used enzymes and speed up the biofuel production process.\r\n\r\n“These enzymes are already used in industrial applications, but they’re not well understood,” said lead author Brad O’Dell, a graduate student from NC State working in the Biology and Soft Matter Division of ORNL’s Neutron Sciences Directorate. “Understanding each step in the LPMO mechanism of action will help industry use these enzymes to their full potential and, as a result, make final products cheaper.”\r\n\r\nIn an LPMO enzyme, oxygen and cellulose arrange themselves through a sequence of steps before the biomass deconstruction reaction occurs. Sort of like “on your mark, get set, go,” says O’Dell.\r\n\r\nTo better understand the enzyme’s reaction mechanism, O’Dell and coauthor Flora Meilleur, ORNL instrument scientist and an associate professor of molecular and structural biochemistry at NC State, used the IMAGINE neutron scattering diffractometer at ORNL’s High Flux Isotope Reactor to see how the enzyme and oxygen molecules were behaving in the steps leading up to the reaction—from the “resting state” to the “active state.”\r\n\r\nThe resting state, O’Dell says, is where all the critical components of the enzyme assemble to bind oxygen and carbohydrate. When electrons are delivered to the enzyme, the system moves from the resting state to the active state—i.e., from “on your mark” to “get set.”\r\n\r\nIn the active state, oxygen binds to a copper ion that initiates the reaction. Aided by X-ray and neutron diffraction, O’Dell and Meilleur identified a previously unseen oxygen molecule being stabilized by an amino acid, histidine 157.\r\n\r\nHydrogen is a key element of amino acids like histidine 157. Because neutrons are particularly sensitive to hydrogen atoms, the team was able to determine that histidine 157 plays a significant role in transporting oxygen molecules to the copper ion in the active site, revealing a vital detail about the first step of the LPMO catalytic reaction.\r\n\r\n“Because neutrons allow us to see hydrogen atoms inside the enzyme, we gained essential information in deciphering the protein chemistry. Without that data, the role of histidine 157 would have remained unclear,” Meilleur said. “Neutrons were instrumental in determining how histidine 157 stabilizes oxygen to initiate the first step of the LPMO reaction mechanism.”\r\n\r\nTheir results were subsequently confirmed via quantum chemical calculations performed by coauthor Pratul Agarwal from ORNL’s Computing and Computational Sciences Directorate.\r\n\r\nResearch material preparation was supported by the ORNL Center for Structural Molecular Biology. X-ray data were collected at the Argonne National Laboratory Advanced Photon Source through access provided by the Southeast Regional Collaborative Access Team.\r\n\r\nO’Dell says their results refine the current understanding of LPMOs for science and industry researchers.\r\n\r\n“This is a big step forward in unraveling how LPMO’s initiate the breakdown of carbohydrates,” O’Dell said. “Now we need to characterize the enzyme’s activated state when the protein is also bound to a carbohydrate that mimics cellulose. Then we’ll have the chance to see what structural changes happen when the starting pistol is fired and the reaction takes off.”\r\n\r\nHFIR is a DOE Office of Science User Facility. UT-Battelle manages ORNL for the Office of Science. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.', '2017-07-08 01:43:30', '2017-07-08 01:43:30'),
(6, 1, 'Drinking Alcohol While Pregnant Could Have Transgenerational Effects', 'drinking-alcohol-pregnant-transgenerational-effects', 'Soon-to-be mothers have heard the warning – don’t drink while pregnant. The Centers for Disease Control and Prevention (CDC) has issued numerous statements about the dangers of alcohol consumption during pregnancy, as it can lead to Fetal Alcohol Spectrum Disorders (FASD) in newborns.\r\n\r\nDespite this, many women drink during pregnancy, a choice that scientists have known for years could hurt these mothers’ children. Today, there is a new reason why an expectant mother should put down that glass of wine – drinking alcohol during pregnancy will not only affect her unborn child, but may also impact brain development and lead to adverse outcomes in her future grand- and even great-grandchildren.\r\n\r\nThe new study by Kelly Huffman, psychology professor at the University of California, Riverside, titled “Prenatal Ethanol Exposure and Neocortical Development: A Transgenerational Model of FASD,” was published in the journal Cerebral Cortex.\r\n\r\n“Traditionally, prenatal ethanol exposure (PrEE) from maternal consumption of alcohol, was thought to solely impact directly exposed offspring, the embryo or fetus in the womb. However, we now have evidence that the effects of prenatal alcohol exposure could persist transgenerationally and negatively impact the next-generations of offspring who were never exposed to alcohol,” Huffman said.\r\n\r\nPrevious work from the Huffman Laboratory at UCR has shown that PrEE impacts the anatomy of the neocortex, the part of the brain responsible for complex behavior and cognition in humans, and that PrEE can lead to abnormal motor behavior and increased anxiety in the exposed offspring. Huffman and a group of UCR students have extended this research by providing strong evidence that in utero ethanol exposure generates neurobiological and behavioral effects in subsequent generations of mice that had no ethanol exposure.\r\n\r\nTo determine whether the abnormalities in brain and behavior from prenatal ethanol exposure would pass transgenerationally, Huffman generated a mouse model of FASD and tested many aspects of brain and behavioral development across three generations. As expected, the first generation, the directly exposed offspring, showed atypical gene expression, abnormal development of the neural network within the neocortex and behavioral deficits. However, the main discovery of the research lies in the subsequent, non-exposed generations of mice. These animals had neurodevelopmental and behavioral problems similar to the those of the first, directly exposed generation.\r\n\r\n“We found that body weight and brain size were significantly reduced in all generations of PrEE animals when compared to controls; all generations of PrEE mice showed increased anxiety-like, depressive-like behaviors and sensory-motor deficits. By demonstrating the strong transgenerational effects of prenatal ethanol exposure in a mouse model of FASD, we suggest that FASD may be a heritable condition in humans,” Huffman said.\r\n\r\nThe multi-level analyses in this study suggest that alcohol consumption while pregnant leads to a cascade of nervous system changes that ultimately impact behavior, via mechanisms that can produce transgenerational effects. By gaining an understanding of the neurodevelopmental and behavioral effects of prenatal ethanol exposure that persist across generations, scientists and researchers can begin to create novel therapies and methods of prevention.', '2017-07-08 01:43:39', '2017-07-08 01:43:39'),
(7, 1, 'Algorithm Diagnoses Heart Arrhythmias With Cardiologist-Level Accuracy', 'algorithm-diagnoses-heart-arrhythmias-cardiologist-level-accuracy', 'A new algorithm developed by Stanford computer scientists can sift through hours of heart rhythm data generated by some wearable monitors to find sometimes life-threatening irregular heartbeats, called arrhythmias. The algorithm, detailed in an arXiv paper, performs better than trained cardiologists, and has the added benefit of being able to sort through data from remote locations where people don’t have routine access to cardiologists.\r\n\r\n“One of the big deals about this work, in my opinion, is not just that we do abnormality detection but that we do it with high accuracy across a large number of different types of abnormalities,” said Awni Hannun, a graduate student and co-lead author of the paper. “This is definitely something that you won’t find to this level of accuracy anywhere else.”\r\n\r\nPeople suspected to have an arrhythmia will often get an electrocardiogram (ECG) in a doctor’s office. However, if an in-office ECG doesn’t reveal the problem, the doctor may prescribe the patient a wearable ECG that monitors the heart continuously for two weeks. The resulting hundreds of hours of data would then need to be inspected second by second for any indications of problematic arrhythmias, some of which are extremely difficult to differentiate from harmless heartbeat irregularities.\r\n\r\nResearchers in the Stanford Machine Learning Group, led by Andrew Ng, an adjunct professor of computer science, saw this as a data problem. They set out to develop a deep learning algorithm to detect 14 types of arrhythmia from ECG signals. They collaborated with the heartbeat monitor company iRhythm to collect a massive dataset that they used to train a deep neural network model. In seven months, it was able to diagnose these arrhythmias about as accurately as cardiologists and outperform them in most cases.\r\n\r\nThe researchers believe that this algorithm could someday help make cardiologist-level arrhythmia diagnosis and treatment more accessible to people who are unable to see a cardiologist in person. Ng thinks this is just one of many opportunities for deep learning to improve patients’ quality of care and help doctors save time.\r\n\r\nBuilding heartbeat interpreter\r\n\r\nThe group trained their algorithm on data collected from iRhythm’s wearable ECG monitor. Patients wear a small chest patch for two weeks and carry out their normal day-to-day activities while the device records each heartbeat for analysis. The group took approximately 30,000, 30-second clips from various patients that represented a variety of arrhythmias.\r\n\r\n“The differences in the heartbeat signal can be very subtle but have massive impact in how you choose to tackle these detections,” said Pranav Rajpurkar, a graduate student and co-lead author of the paper. “For example, two forms of the arrhythmia known as second-degree atrioventricular block look very similar, but one requires no treatment while the other requires immediate attention.”\r\n\r\nTo test accuracy of the algorithm, the researchers gave a group of three expert cardiologists 300 undiagnosed clips and asked them to reach a consensus about any arrhythmias present in the recordings. Working with these annotated clips, the algorithm could then predict how those cardiologists would label every second of other ECGs with which it was presented, in essence, giving a diagnosis.\r\n\r\nSuccess and the future\r\n\r\nThe group had six different cardiologists, working individually, diagnose the same 300-clip set. The researchers then compared which more closely matched the consensus opinion – the algorithm or the cardiologists working independently. They found that the algorithm is competitive with the cardiologists, and able to outperform cardiologists on most arrhythmias.\r\n\r\n“There was always an element of suspense when we were running the model and waiting for the result to see if it was going to do better than the experts,” said Rajpurkar. “And we had these exciting moments over and over again as we pushed the model closer and closer to expert performance and then finally went beyond it.”\r\n\r\nIn addition to cardiologist-level accuracy, the algorithm has the advantage that it does not get fatigued and can make arrhythmia detections instantaneously and continuously.\r\n\r\nLong term, the group hopes this algorithm could be a step toward expert-level arrhythmia diagnosis for people who don’t have access to a cardiologist, as in many parts of the developing world and in other rural areas. More immediately, the algorithm could be part of a wearable device that at-risk people keep on at all times that would alert emergency services to potentially deadly heartbeat irregularities as they’re happening.\r\n\r\nAdditional authors of the paper include Masoumeh Haghpanahi and Codie Bourn of iRhythm. Additional information is available at the project website.', '2017-07-08 01:43:55', '2017-07-08 01:43:55'),
(8, 2, 'Drug Restores Cells And Memories In Alzheimer’s Mouse Models', 'drug-restores-cells-memories-alzheimers-mouse-models', 'A new drug can restore memories and connections between brain cells in mice with a model of Alzheimer’s disease, a new Yale-led study suggests.\r\n\r\n“The drug completely erased evidence of Alzheimer’s synapse damage and memory loss in mouse models of the disease,” said Stephen Strittmatter, the Vincent Coates Professor of Neurology and senior author of the study appearing July 5 in the journal Cell Reports.\r\n\r\nResearchers such as Strittmatter have made significant inroads into understanding the biology of Alzheimer’s disease, but identifying effective and safe treatments has been difficult. It is known that amyloid-beta peptides, the hallmark of Alzheimer’s, couple with prion protein at the surface of brain cells and transmit damaging instructions to the interior of the cell. Yale researchers had previously identified a protein on the cell membrane — metabotropic glutamate receptor 5 or mGluR5 — as the gateway that helps transmit damage from the coupling.\r\n\r\nPrevious attempts had been made to target mGluR5, but most drugs also disrupt signaling of glutamate, the most common neurotransmitter in the human brain. The new compound, Silent Allosteric Modulation or SAM (BMS 984923), was created by Bristol Myers Squibb as part of its effort to treat schizophrenia. The drug does not restrict neurotransmitter signaling in culture tissue or living mice, the study found. After four weeks of treatment, memory and synapses linking brain cells had been restored in mice with a model of Alzheimer’s.\r\n\r\n“The drug does not destroy plaques associated with Alzheimer’s, but allows them to co-exist with neurons,” Strittmatter said.\r\n\r\nYale researchers say the next step is to prepare for preliminary trials of the drug’s effects on humans.\r\n\r\nPrimary funding for the research comes from the National Institutes of Health.\r\n\r\nYale’s Laura T. Haas is lead author of the study. Researchers from Bristol-Myers Squibb Research and Development also contributed to the paper.', '2017-07-08 01:44:06', '2017-07-08 01:44:06');
/*!40000 ALTER TABLE `blog` ENABLE KEYS */;
-- tablo yapısı dökülüyor proje2.category
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(1, 'Sciense', 'sciense', '2017-07-08 00:43:58', '2017-07-08 00:43:58'),
(2, 'Health', 'health', '2017-07-08 01:30:06', '2017-07-08 01:30:06');
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-- tablo yapısı dökülüyor proje2.fos_user
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