SKU: 26745256103
nutcase fahrradhelm m

nutcase fahrradhelm m Nutcase Street Tweet Me Mips

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Description

nutcase fahrradhelm m Nutcase Street Tweet Me MipsOriginal, urban und jetzt mit MIPS. Wichtige Passform: Die Gre der neuen Modelle ist aufgrund des Mips Einsatzes kleiner als von Nutcase angegeben. Unsere Einschtzung ist, dass Sie 1 2 cm. zur Kopfgre hinzufgen sollten. Der Nutcase Street Tweet Me Mips ist jetzt verbessert. Die brandneue Nutcase Street Serie prsentiert MIPS Sicherheit auf jedem Helm. Am Hinterkopf befindet sich ein FlexFit Verstellrad, und am Kinn kann der Helm mit einem Fidlock

Original, urban und jetzt mit MIPS.

Wichtige Passform: Die Größe der neuen Modelle ist aufgrund des Mips-Einsatzes kleiner als von Nutcase angegeben. Unsere Einschätzung ist, dass Sie 1-2 cm. zur Kopfgröße hinzufügen sollten.

Der Nutcase Street Tweet Me Mips ist jetzt verbessert. Die brandneue Nutcase Street Serie präsentiert MIPS Sicherheit auf jedem Helm. Am Hinterkopf befindet sich ein FlexFit Verstellrad, und am Kinn kann der Helm mit einem Fidlock Magnetverschluss mit Einklemmschutz befestigt werden.

Mips: Durch die Integration der Mips-Technologie, kann nicht nur ein vertikaler Aufprall, sondern auch die Auswirkungen von Rotationsenergie absorbiert werden, welche ein ernsthaftes Problem bei Stürzen darstellen kann. Diese bahnbrechende, patentierte Technologie ermöglicht eine Drehung oder Rotation der inneren Schale im Verhältnis zur äußeren. So kann die Energie des Aufpralls bis zu 40 % reduziert werden und die entstehende Belastung auf das Gehirn wird wesentlich verringert. Schädigungen des Gehirns können so reduziert oder gar vermieden werden.


Typ Fahrrad, skate, bmx & sport
Farbe Multi mit Motiv
Gewicht S 510 g - M 540 g - L 570 g
Verstellsystem Verstellrad & schaumpolster
Belüftungsöffnungen 11 Stück
Kinnverschluss Magnetverschluss
Prüfzeichen CE EN 1078
Konstruktion ABS Hartschale
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SKU: 26745256103

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4.9 ★★★★★
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Z
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Zay
Birmingham, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
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Reviewed in the United States on October 23, 2024
R
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Rory Derrick
New York, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
C
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Cory P.
Massapequa, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
F
Verified Purchase
Frank Gonzalez
Phoenix, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
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Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Belleville, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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