The Invention of Everything Else

The Invention of Everything Else
Samantha Hunt | 2008-02-07 00:00:00 | Blackstone Audio Inc. | 0 | Historical
From the moment she first catches sight of Nikola Tesla on New Year's Day, 1943, Louisa, obsessed with radio dramas and the secret lives of the hotel guests, is determined to befriend this strange man. Winning his attention through their shared love of pigeons, Louisa eventually uncovers the extraordinary story of Tesla's life as a Serbian immigrant and a visionary genius. Meanwhile, Louisa finds herself facing her father's imminent departure in a time machine.
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Hunt is a phenomenal writer, don't get me wrong, but I couldn't for the life of me finish this book. It is so overly dull and dry; although, I was somewhat entertained with the storyline of Louisa. Telsa's flashbacks are somewhat... boring. I really tried to like this book. And believe it or not, I have been reading this book for four months and I'm only halfway through. This book is definitely not for me.
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Knowing Tesla from other readings, some of the AC theories that he created, and having navigated the numerous Internet pages on this man, I felt sorely let down by the writings. Perhaps I had expected too much. But I simply could not "get into the book". I kept it on my desk for months, opened it to my last read page, and struggled to savor the writings of Samantha Hunt. I had such hopes for this book when I first read of its release. Alas, the menu was more interesting than the meal.
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What better way to understand the enigma that was Nikola Tesla than via the eyes of a character in his life, even if that character is fictional? After all, Tesla's life from inside Tesla's brain would be way too perplexing for us mere mortals.

Through the perspective of Tesla's chambermaid, Samantha Hunt pulls off an engrossing tale of Tesla's final days and, along the way, weaves into his life the participation of assorted famous inventors, entrepreneurs, financiers, and literary figures.

My only objection -- almost strong enough to prevent me from getting to page 1, in fact -- was the unfortunate inclusion of a quotation purportedly by Charles Duell, the Commissioner of Patents in 1899 to the effect that everything has been invented. He never said that. (Check out snopes.com.)

But I'm glad I persevered beyond that quotation page.


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I've read some of the other reviews here and am absolutely baffled by the enthusiasm for this book. I've spent a couple days with THE INVENTION OF EVERYTHING ELSE, and must toss it in the same bucket with David Alan Gold's CARTER BEATS THE DEVIL -- awesome concepts featuring fantastical/magical period characters, that utterly fail to deliver.



THE INVENTION OF EVERYTHING ELSE focuses on two characters - Nikola Tesla (discovered living, in his later years, in rooms at The New Yorker hotel) and Louisa (a young housemaid at the hotel). Inevitably they meet. I was very hopeful that Tesla would emerge fully imagined and authentic in these pages - but Hunt fails completely. It is a high challenge to convincingly present a genius. Hunt's Tesla doesn't emerge as a genius - rather, Tesla's voice sounds distinctly feminine, and rather pedestrian of intellect. Worse, he emerges *without* character - we are told that he is of Serbian ancestry, from the Czech republic, brilliant, etc., but despite all that richness, he sounds exactly like a rather pedestrian American.



Louisa we have met before - she is one of the millions of innocent/virginal waifs that people young adult novels. Her musings are adolescent and rather infantile. There is nothing in this book - repeat, nothing - that separates Louisa as a unique character from any others of her ilk. In one scene, Hunt has her fancying that she is about to be bitten by a vampire - which immediately reminded me of the appeal of the TWILIGHT novels to adolescent girls: basically, the sexuality inherent in vampire stories. Thus, I suggest a new rule: When publishing novels, any combination of innocent girls with any mention whatsoever of vampires merits shelving such novels in the young adult section. That's where THE INVENTION OF EVERYTHING ELSE belongs.



Other famous people of the age appear in THE INVENTION OF EVERYTHING ELSE - Sam Clemens, among others. All of them sound interchangeable. None of them emerge as unique characters.



The prose is meandering, sometimes purple. The plotting is meandering, sometimes aimless, and not particularly involving - even when the action crosses into the fantastic.



I will say this for THE INVENTION OF EVERYTHING ELSE - it may reside in the same bucket as CARTER BEATS THE DEVIL, but it's a better book. CARTER BEATS THE DEVIL was amateurish on every level. THE INVENTION OF EVERYTHING ELSE at least is the product of a writer, albeit a young adult writer.
Reviews
Ms. Hunt has created a very original piece of fiction in "Invention of Everything Else." The characters are endearing and vulnerable, funny and courageous--all in their own ways. The love story involves everyone and is believable even if Ms. Hunt uses a type of fantasy realism and whimsy that defies definition. I guess I was hoping for more than the ending was able to provide. Well, maybe I just didn't want a very good read to end.

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Hepatology and Transplant Hepatology: A Case Based Approach

Hepatology and Transplant Hepatology: A Case Based Approach
Jawad Ahmad | 2010-11-01 00:00:00 | Springer | 440 | Internal Medicine
Hepatology and Transplant Hepatology: A Case Based Approach presents a collection of interesting cases in liver disease seen at a very busy and large liver transplant center in the United States. These cases cover the full range of pathology that an internist or gastroenterologist may expect to see in a lifetime of taking care of patients with acute or chronic liver disease, before or after liver transplant. Each case is presented as you would see it in a clinical situation where a patient presents a complaint or something is noted on exam or blood work. The question/answer format will help one through the problem of making a diagnosis or in considering a differential diagnosis and also point to the best way to manage each condition. The volume is divided into pre-transplant and post-transplant hepatology. Each case is 3 pages with the first page presenting the case and pertinent lab data and 3-4 questions (i.e. differential diagnosis, tests to order, x-rays/CT required).The second page illustrates the tests, scans, biopsies and asks for the pertinent findings. The third page provides the diagnosis and what may have been expected with other diagnoses. Here is a single source dealing with questions specific for patients with complications of advanced liver disease and also clinical situations seen in transplant hepatology. Hepatology and Transplant Hepatology: A Case Based Approach will have great appeal to anyone in hepatology/transplant hepatology and also to residents/fellows and internists interested in gastroenterology.

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ADV IN CARBOHYDRATE CHEM & BIOCHEM VOL24, Volume 24 (v. 24)

ADV IN CARBOHYDRATE CHEM & BIOCHEM VOL24, Volume 24 (v. 24)
Author Unknown | 1970-04-11 00:00:00 | Academic Press | 520 | Organic

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Master TOEFL Vocabulary

Master TOEFL Vocabulary
Thomson Arco | 2006-01-01 00:00:00 | Arco | 208 | English
Test preparation for the vocabulary section of the latest TOEFL test
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Variations on a Theme: Quilts With Easy Options

Variations on a Theme: Quilts With Easy Options
Terry Martin | 2006-01-01 00:00:00 | That Patchwork Place | 82 | Do It Yourself
Discover how easy—and fantastically fun!—it is to spotlight novelty fabrics in these easy-to-stitch quilts. Learn top tricks for quilting with all kinds of theme fabrics, from seasonal and holiday prints to animal motifs.
• Add an instant theme to 12 projects—designs feature anywhere from 1 to 20 fabrics
• Get tips for using the bright colors, large motifs, and directional designs that often appear in novelty fabrics
• Bonus! Includes photos of alternate settings and colorways
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Anatomy Coloring Book

Anatomy Coloring Book
Stephanie Mccann,Eric Wise | 2008-08-05 00:00:00 | Kaplan Publishing | 384 | Anatomy

• Hundreds of clear, concise illustrations, with a labeling key for each
• 15 chapters representing major body systems (Skeletal, Nervous, Cardiovascular,) as well as Cells and Tissues, Muscles, Development, and more
• A descriptive overview of each illustration including major features, key points, and coloring guidelines
• 96 tear-out muscle flashcards
• Nomina Anatomica labels, an international standard of anatomical nomenclature

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Book came in Great Condition. Shipment took a while, but that was due to the terrible weather of the 2010 winter.
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This book arrived in a timely manner and was in excellent condition. It was just in time for her class. Thank you.
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My Anatomy Coloring Book came very early and was wrapped in something really cool. It was in perfect condition, even though it was a paperback book, and it was like still in a "Never Been Touched" condition.
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I'm very disappointed in this book. I in fact didn't buy it but I'm currently tutoring a student and she bought the book and I have already found one big piece of information that was incorrect. So if you want accuracy and if you want to really understand the anatomy don't used this book. The descriptions are 3rd rate and that is even if they are correct. I would recommend the Anatomy Coloring book by Kapit and Elson. Much better descriptions and more detailed coloring.
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product is exactly as described, but I didn't feel it was overly helpful for me. i used it at the beginning of my anatomy class but that lasted for about 5 pages -- would be a good item for first time anatomy students, but i wouldn't recommend this for graduate level students like myself...

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Causality: Models, Reasoning, and Inference

Causality: Models, Reasoning, and Inference
Judea Pearl | 2000-03-13 00:00:00 | Cambridge University Press | 384 | Artificial Intelligence
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
Reviews
Judea Pearl is one of the leading researchers in the topic of casuality. What is causality? In the exploration of statistical data we are often able to find relationships or correlations between two variables. We are often tempted to attribute the results of one variable, say A as an outcome (being high or low)that is due to the result (high or low) of the other, say B. We want to say that B is the cause of the outcome of A. Significant correlation by itself only suggests relationships. It cannot tell you whether A causes B or B causes A or neither. Causility is the study of designing experiments to allow you to determine if a relationship has a cause and effect. The subject matter is very philosophical and somewhat controversial. But a lot of research effort has gone into providing mathematical rigor to the concept. Pearl is one of those rare scientists who can contribute to such theory and explain it. But as Aickin suggests in his amazon review this is not a subject for a novice. Previous exposure to statistical methods such as correlation and regression is important to a clear unbderstanding of this book.
Reviews
This is a very interesing book that Judea Pearl worte. The topic is currently of general interest for diverse fields as economics, social sciences and biology, however, this book is not intended for practitoners from these field who face a special problem and search for a possible solution. If you want to buy this book for this reason you will not be able to extract this information for this book. The reason therefor is that important technics like Bayesian Networks or Structural Equations are treated in 3 pages in each case. Judea Pearl assumes that the reader is already familiar with such methods beforehand. (Readers interested in the later subject are strongly refered to Bollen's book "Structural Equations with latent variables".)



Moreover, I do not think that this book presents state of the art information about our current knowledge of this subject. For example, the important problem to extract a network structure (structure learning) from data rather than estimating the parameters of a given networks structure is completely missing.



Nevertheless, this is a good book, because it might give you in the long run (you can not read it in one piece) insights you did not have before. Of course not to all topics causality is involved (see, e.g., above) but the given topics are thorough explained albeit on an advanced level.



Update: I add one star (total three) to my evaluation, because in the meanwhile I appreciate the historical development described in the book including references to the literature.






Reviews

Pearl included an Epilogue containing a lecture he gave in 1996 entitled, "The Art and Science of Cause and Effect."

Pearl concludes the lecture by comparing his theory of causality to the first mathematical tool,the abacus: "But the really challenging problems are still ahead: We still do not have a causal understanding of poverty and cancer and intolerance, and only the accumulation of data and the insight of great minds will eventually lead to such understanding. "The data is all over the place, the insight is yours, and now an abacus is at your disposal, too. I hope the combination amplifies each of these components."



Unfortunately, virtually no advances have been made in learning the causation of intolerance nor how to rid us of it. And Judea Pearl suffered immensely because of that . . . Daniel Pearl, his son, was killed in Iraq due to intolerance. :-(



BTW, the book is great.
Reviews
The scientific research community has adopted rigorous methods to eliminate the need for subjective judgments about many things, but when it comes to testing whether X causes Y, they revert to intuition and hand-waving. This book makes a strong argument that we shouldn't accept that. It demonstrates that it is possible to turn intuitions about causation into hypotheses that are unambiguous and testable.

But the style is sufficiently dense and dry we will need some additional books with more practical styles before these ideas become widely understood. The style is fairly good by the standards of books whose main goal is rigorous proof, but it's still hard work to learn a large number of new concepts that are mostly referred to by terse symbols whose meaning can't be found via a glossary or index. Pearl occasionally introduces a memorable word, such as do(x), the way a software engineer who wants readable code would, but mostly sticks to single-character symbols that seem unreasonably hard (at least for us programmers who are used to descriptive names) to remember.

If you're uncertain whether reading this book is worth the effort, I strongly recommend reading the afterword first. It ought to have been used as the introduction, and without it many readers will be left wondering why they should believe they will be rewarded for slogging through so much dry material.
Reviews
This is a pioneering book dealing exhaustively with the subject of causation. Its contribution to the field of "Uncertainty in AI" is unmeasureable. It dealt with graphical models for reasoning in depth. For computer scientists looking for an encyclopedia of algorithms and applications on causation, there can not be a better book. I highly recommend this book for researchers in UAI. A word of caution: This is not a book for starters and those who do not have a well developed concept of uncertainty.

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