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[O112.Ebook] Download PDF No Magic Bullet: A Social History of Venereal Disease in the United States Since 1880, by Allan M. Brandt

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From Victorian anxieties about syphilis to the current hysteria over herpes and AIDS, the history of venereal disease in America forces us to examine social attitudes as well as purely medical concerns. In No Magic Bullet, Allan M. Brandt recounts the various medical, military, and public health responses that have arisen over the years--a broad spectrum that ranges from the incarceration of prostitutes during World War I to the establishment of required premarital blood tests.

Brandt demostrates that Americans' concerns about venereal disease have centered around a set of social and cultural values related to sexuality, gender, ethnicity, and class. At the heart of our efforts to combat these infections, he argues, has been the tendency to view venereal disease as both a punishment for sexual misconduct and an index of social decay. This tension between medical and moral approaches has significantly impeded efforts to develop "magic bullets"--drugs that would rid us of the disease--as well as effective policies for controlling the infections' spread.

Sales Rank: #2852632 in Books
Published on: 1985-03-07
Original language: English
Number of items: 1
Dimensions: 9.50" h x .92" w x 6.44" l,
Binding: Hardcover
245 pages

Review
"A welcome addition to the growing literature related to sex in American history....It is a major contribution to both medical and social history."--American Historical Review

"Brandt bases his case on a well-documented analysis of public policy concerning venereal diseases during the last one hundred years....No Magic Bullet deserves a broad audience."--Journal of American History

"Brandt has served up an analytical feast....No Magic Bullet may remain the definitive social history of [venereal disease] for many years to come."--Bulletin of the History of Medicine

"A significant contribution to our understanding of public responses to STDs in the United States....Useful and timely."--Arthur R. Williams, University of Florida, Gainesville

"An audacious examination of American attitudes toward sexually transmitted disease...A chilling reminder of a forgotten history."--The Village Voice

"An excellent short treatment of venereal disease in this country. It is clearly written and with the addition of the chapter on AIDS, most appropriate and updated."--William A. Sodeman, Jr., M.D., University of Southern Florida, Tampa

"A thoroughly researched...intriguing book...Brandt argues persuasively that many of the underlying attitudes of the Victorian period continue to hinder the control of venereal diseases."--Philadelphia Inquirer

"A subtle and convincing book...an eloquent chapter in the history of sex in America."--Psychology Today

"Well-researched, accurate, and clearly written...This historical perspective has much to offer readers in the fields of public health and infectious disease at a time when important policy decisions regarding the control of AIDS must be made."--New England Journal of Medicine

"A major contribution to the social history of medicine and public policy in the United States."--Isis

From the Back Cover
This book is devoted to tracing the historical record of this distinctive set of infectious diseases from the late nineteenth century to current epidemics of herpes and Acquired Immune Deficiency Syndrome (AIDS).

About the Author
Allan M. Brandt is Professor of the History of Science at Harvard University Faculty of Arts and Sciences and Kass Professor of the History of Medicine at Harvard Medical School.

Most helpful customer reviews

5 of 5 people found the following review helpful.
A Great History of Morality and Medicine
By Jack H.
No Magic Bullet creates a very detailed, extremely well researched volume on the evolution of healthcare. The progression through the various phases of modern thought may seem entertaining or absurd in hindsight yet Brandt very carefully recreates the time period making the rise and fall of each idea seem appropriate, regardless of their absurdity.

If you are looking for an entertaining read, look elsewhere. No Magic Bullet is geared towards academics or professionals. It is not a difficult volume but it is not a whimsical read either. The level of detail and research put into this text indicate a profound passion and understanding of medicine in the proper historical context.

I'll agree with the first review, some of the information may seem dated, but if you're writing about history it makes little difference. If you're looking for cutting edge information on AIDS and the developments made in the past ten years; look elsewhere. But if you want a social progression spanning through some of medicine's interesting periods this is an excellent resource.

I highly recommend this volume for anyone that might be remotely interested in sociology, healthcare, or history.

0 of 0 people found the following review helpful.
Four Stars
By Harris
Interesting how mores have changed in so short a time

0 of 0 people found the following review helpful.
This was a really interesting examination of disease and morality ...
By Sarah
This was a really interesting examination of disease and morality in the United States, as well as how these shift in response to social changes, such as immigration.

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Rabu, 17 Juli 2013

[D334.Ebook] Ebook Introduction to Data Mining, by Pang-Ning Tan, Michael Steinbach, Vipin Kumar

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Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

Sales Rank: #31361 in Books
Brand: Tan, Pang-Ning/ Steinbach, Michael/ Kumar, Vipin
Published on: 2005-05-12
Original language: English
Number of items: 1
Dimensions: 9.40" h x 1.60" w x 7.40" l, 2.60 pounds
Binding: Hardcover
769 pages

Most helpful customer reviews

78 of 79 people found the following review helpful.
Data mining book focusing on clustering
By Sandro Saitta
I decided to start with this book as I think it is the most convenient to start in the data mining field. One big advantage of the book is the way data mining techniques are explained. It is mainly based on textual and graphical explanations. There is little equations, only what is necessary to implement the algorithms.

This book widely cover areas such as data preparation and understanding, classification, anomaly detection, association analysis and clusering. Although the book has a strong emphasis on the two last ones, nearly all standard data mining techniques are at least briefly discussed. However, this book does only have a fiew pages about kernel methods for example. Indeed, it is normal, as kernel methods are more suitable for machine learning (I mean making prediction) than data mining (I mean looking for description).

Therefore, this book is:

* able to explain data mining without thousands of equations

* a good way to start with data mining

* covering nearly all standard data mining techniques

* focused on association analysis and clustering

and it is not:

* a good book for kernel methods and other advanced techniques

* written in the statistical nor in the database perspective

My comment: if you are in the data mining field and not comming from mathematics or databases, then you really should buy this book.

56 of 59 people found the following review helpful.
superb description of clusters
By W Boudville
As databases keep growing unabatedly, so too has the need for smart data mining. For a competitive edge in business, it helps to be able to analyse your data in unique ways. This text gives you a thorough education in state of the art data mining. Appropriate for both a student and a professional in the field.

The extensive problem sets are well suited for the student. These often expand on concepts in the narrative, and are worth tackling.

The central theme in the book is how to classify data, or find associations or clusters within it.

Cluster analysis gets two chapters that are superbly done. These summarise decades of research into methods of grouping data into clusters. Usually hard to do, because an element of subjectivity can creep into the results. If your data is scattered in some n-dimensional space, then clusters might exist. But how to find them? The chapters show that the number of clusters and the constituents of these can depend on which method you adopt, and various initial conditions, like [essentially] seed values for clusters, if you choose a prototype cluster method like K-means.

The descriptions of the cluster algorithms are succinct. Why is this useful? Because it helps you easily understand the operations of the algorithms, without drowning you in low level detail. Plus, by presenting a meta-level comparison between the algorithms, you can develop insight into rolling your own methods, specific to your data.

Part of my research involves finding new ways to make clusters, and the text was very useful in explaining the existing ideas.

41 of 45 people found the following review helpful.
Good overview, but needs to include real-world case studies
By Dr. Lee D. Carlson
Data mining could be considered to be "Artificial Intelligence Lite", since it deals with many of the same issues in learning, classification, and analysis as they occur in the field of artificial intelligence but does not have as its goal the construction of "thinking machines." Instead, the emphasis is on practical problems that are important in business and industry, even though the solutions of many of these problems makes use of techniques that a thinking machine should be expected to have. Data mining has become an enormous industry, and has even been the subject of political and legal concerns due to the efforts of some governments to mine data on its citizens. This book gives a general overview of data mining with emphasis on classification and associative analysis. Anyone who is interested in data mining could read the book, but some rather sophisticated background in mathematics will be needed to read some of the sections. Pseudocode is given throughout the book to illustrate the different data mining algorithms. There are also exercises at the end of each chapter, but noticeably missing in the book is the inclusion of real case studies in data mining. The inclusion of these case studies would alert the reader to the fact that data mining is of great interest from the standpoint of business and industry, and would lessen the belief that data mining is just another academic field or just another branch of statistics.

Speaking somewhat loosely, the goal of data mining is to find interesting patterns in massive amounts of data or the classification of such patterns. This entails of course that one have a notion of what is "interesting" and one of the main problems in data mining is to find suitable `interestingness measures'. And since one is typically dealing with large amounts of data, one must use various statistical sampling and preprocessing techniques to massage the data and obtain a `representative' sample of the original data. In addition, one must be able to handle data that is `anomalous', i.e. data that has characteristics that are markedly different from most of the other data, or that has attributes that are unusual if compared with typical values for those attributes. These issues and techniques are discussed in detail in the first three chapters of the book, where the authors outline some of the bread-and-butter topics needed for effective manipulation of data.

The real substance and power of data mining comes from its role in classification and for discovering interesting patterns in huge data sets. The authors, in chapters 4 - 7, discuss various powerful techniques for data classification and association analysis. Association analysis in particular has been used quite extensively in recent years, due to the use of market basket transactions in on-line purchasing and the goal of marketers to learn the purchasing behavior of their customers. Association analysis uncovers relationships in the marketing data in the form of `association rules'. For disjoint itemsets X and Y, an association rule is a logical implication expression between these itemsets that has a certain `strength' that is measured by its `support' and `confidence.' The support measures how often a rule is applicable to a given data set, while the confidence measures how frequently the items in Y appear in X. The support reflects the ability of the rule to be not due to chance alone, while the confidence measures the reliability of the rule inference. The collection of all association rules that can be formed from a data set is too large to be practical and so strategies must be developed to prune the number of rules. The authors discuss in detail various methods for dealing with this computational drawback, such as `frequent itemset generation' and `rule generation.'

The detection of anomalies consists of the identification of `outliers', which as the name implies are data objects that lie "far away" from the other data objects. It remains of course to quantity what it means to be "far away" and for this reason this branch of data mining, as the author points out, is sometimes called `deviation detection' or `exception mining'. The omission of outliers is sometimes justified, since they are merely artifacts that only serve to alter the statistics of a particular data set. However, sometimes their presence signals important information, if not a major scientific discovery. Data mining therefore must contain tools that detect anomalies intelligently and efficiently. The authors discuss anomaly detection in fair detail, emphasizing the statistical techniques that are available to do it. They classify the techniques for anomaly detection as being `unsupervised', `supervised', and `semi-supervised'. As the name implies, supervised anomaly detection requires the existence of a training set with both anomalous and "normal" data with each class being labeled as such. When these labels are unavailable, one has to perform unsupervised anomaly detection, and for this approach to work the anomalies must be distinct from one another. If the normal data is labeled but the anomalies are not, one must do semi-supervised anomaly detection. The only weakness in the authors' discussion is that they do not include real-world case studies that illustrate the different techniques, such as clustering and density methods.

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Sabtu, 13 Juli 2013

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Sales Rank: #1452911 in Books
Published on: 1991
Binding: Single Issue Magazine
198 pages

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Sales Rank: #820378 in eBooks
Published on: 2015-10-24
Released on: 2015-10-24
Format: Kindle eBook

About the Author
Matt Sinclair is a journalist and fiction writer. In 2012, he established Elephant's Bookshelf Press, which to date has published a total of ten short story anthologies and novels. The goal of EBP is to help talented writers gain and develop an audience. Since 2012, EBP has been the initial fiction publisher of at least a dozen writers. Learn more at www.elephantsbookshelfpress.com

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6 of 6 people found the following review helpful.
Creepy Tales!
By Precy
These are awesomely creepy tales!

THE DREAM HOUSE : I wrote this so of course I love it! hehehe :)

BLOOD AND INK by Mindy McGinnis : Quite unexpected ending that may have sent me snickering (because I'm sometimes immature)--but I'm sure it's a horrific end for...some people.

THE SOUND OF THE CHAIN by R.S. Mellette : Okay, this one terrified me. I had that uncomfortable, inward-cringing feeling because, while this is not your typical blood-and-gore horror (there's no gore and it's still terrifying!), the idea of this story coming true to life is enough to curdle one's blood. The expert build-up of suspense had me on my toes, too. Well done!

A SECRET KEPT IN SHAME by A.M. Supinger : I had the pleasure of beta-reading this, and let me just say that A.M. Supinger knows how to evoke vivid imagery, as well as create intriguing characters that you can oddly sympathize with despite their villain status.

THE GODS WITHIN by Justin Holley : Justin Holley is a master horror writer (I have had the pleasure of beta-reading his novel-length works), and this one is grim and disturbing in a creeptastic way!

THE WILD HUNT by Sarah Glenn Marsh : I loved the suspense in this story, and not knowing where it was heading to, or what I was going to find in the end. And the ending didn't disappoint, bringing the story to full circle!

CORRUPT by Kim Graff : Disturbing on so many levels. How do you decide who's right and who's wrong, especially when you've been brought up to believe in a certain truth? This reminds me of cults and the brainwashing that goes with their teaching. Except there are no cults in this story.

TIME TO PRAY by E.B. Black : Another favorite of mine! I'm still unnerved by this.

LOST SOLES by Madeline Mora-Summonte : A bit heartbreaking. Very suspenseful.

THE TROLLS by Kay Elam: Loved this one, too. Strange and unexpected and excellent character voice!

THE ICE TREE by Charlee Vale : Pretty imagery with a sad, creepy conclusion.

LOST by Matt Sinclair : Short but emotion-filled. Honestly, I felt sad reading this. But there's also just the right amount of spine-tingling factor to close this anthology with that ending.

2 of 2 people found the following review helpful.
A quality variety of horror
By Amazon Customer
Excellent choice for those who are looking to pee their pants. The great thing about horror, as a genre, is that people are frightened by different things; sometimes redundant tropes make it hard to get into a scary story, but this anthology has a nightmare or two for everyone.

I suggest reading it at night, under the covers, during a thunderstorm...:)

1 of 1 people found the following review helpful.
These aren't bedtime stories to read to your children!
By NashFlash
This is the kind of book we used to read with a flashlight under the covers. It's scary, but not always in an obvious way. The twelve authors approached their subject matter from twelve different ways. I suspect I'll still be thinking about some of the stories in the days and weeks to come. The stories are short enough that they are a quick read, but long enough to leave a lasting impression. Not for the weak at heart!

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Horrors: Real, Imagined, and Deadly, by Matt Sinclair, Mindy McGinnis, Sarah Glenn Marsh, R.S. Mellette, Justin Holley, Precy Larkins, Kim PDF
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