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Dr. Seuss’s Green Eggs and Ham: With 12 Silly Sounds!

為了解決Rosetta的問題，作者Dr Seuss 這樣論述：

Dr. Seuss’s classic story starring Sam-I-Am is now an interactive board book featuring twelve different sounds! Children will love pressing the buttons to make music and singing or dancing along!Do you like green eggs and ham?So begins this interactive adaptation of Dr. Seuss’s beloved tale about tr

ying new things. As Sam-I-Am tries to persuade the grumpy narrator to try green eggs and ham--in a house, with a mouse, on a train, in the rain . . . everywhere, in every way!--children can spot the Seussian icons on the page, press the matching buttons, and listen to sounds that bring each scenario

to life. From a train whistle and ship horn to the sizzle of a fried egg and the bleat of a goat, the twelve sounds featured complement the text and add a level of interactivity to this classic story, inviting young readers to experience it in a new way. Try them! Try them!And you may.Try them and

you may, I say.The colorful sound module comes with a handy on/off switch, and batteries can be easily replaced. With famously simple vocabulary, hilarious rhymes, and iconic characters, this sound book is the perfect way to introduce a new generation of readers to the imaginative world of Dr. Seuss

! THEODOR SEUSS GEISEL--aka Dr. Seuss--is one of the most beloved children’s book authors of all time. From The Cat in the Hat to Oh, the Places You’ll Go!, his iconic characters, stories, and art style have been a lasting influence on generations of children and adults. The books he wrote and ill

ustrated under the name Dr. Seuss (and others that he wrote but did not illustrate, including some under the pseudonyms Theo. LeSieg and Rosetta Stone) have been translated into thirty languages. Hundreds of millions of copies have found their way into homes and hearts around the world. Dr. Seuss’s

long list of awards includes three Caldecott Honors, the Pulitzer Prize, and eight honorary doctorates. Works based on his original stories have won three Oscars, three Emmys, three Grammys, and a Peabody. To learn more about Dr. Seuss’s life and books--and for fun games and activities--visit Seussv

ille.com!

Rosetta進入發燒排行的影片

以結構力學統計學習闡明蛋白質功能性質的分子機制

為了解決Rosetta的問題，作者尼克森 這樣論述：

摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiList of Figure

s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Research problems . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Roles of backbone and side chains in protein folding and function . . . . . . . 31.3 Overview of molecular dynamics simulation . . . . . . . . . . . . . . . . . . . 41.3.1 Basic Theory . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . 41.3.2 Inter-atomic potentials . . . . . . . . . . . . . . . . . . . . . . . . . . 61.4 Coarse-grained approaches of protein simulation . . . . . . . . . . . . . . . . 71.5 Network analysis of proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.5.1 Elastic Network Models (

ENM) . . . . . . . . . . . . . . . . . . . . . 81.5.2 Graph theory to analyze protein structural network . . . . . . . . . . . 91.5.3 Allosteric regulation mechanisms through network based approaches . 101.6 The protein model systems under investigation . . . . . . . . . . . . . . . . . 121.6.1 Seri

ne protease: rat trypsin . . . . . . . . . . . . . . . . . . . . . . . . 131.6.2 PDZ3 domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131.7 Outline of research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Computational Methods . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . 162.1 All-atom molecular dynamic simulations . . . . . . . . . . . . . . . . . . . . . 162.2 Parameterization of bsENM by structure-mechanics statistical learning . . . . . 172.2.1 Atomic-to-CG mapping . . . . . . . . . . . . . . . . . . . . . . . . . 172.2.2 Compu

ting spring constants using fluctuation matching . . . . . . . . . 182.2.3 Determination of optimal lc cutoff . . . . . . . . . . . . . . . . . . . . 192.3 Construction of inter-residue rigidity graphs from statistically learned springconstants . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . 202.4 Similarity analysis of rigidity graphs . . . . . . . . . . . . . . . . . . . . . . . 212.5 Protein rigidity graphs – statistical analysis . . . . . . . . . . . . . . . . . . . 222.5.1 Analysis of the statistical fluctuations of rigidity graph through theirmean-modes . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . 222.5.2 Calculation of mean-mode contents in an analysis time window . . . . 232.5.3 Identification of prominent eigenmodes of a rigidity graph . . . . . . . 242.6 Calculation of the residue rigidity scores for backbone and side-chains of themode

l proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252.7 Determination of prominent mechanical responses upon substrate binding/dissociationin the model proteins . . . . . . . . . . . . . . . . . . . . . . . . . . 262.8 Multiple sequence alignment for PDZ3 . . . . . . . .

. . . . . . . . . . . . . . 263 Results and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283.1 How does the protein mechanical coupling network differ from the structuraltopology? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.1.1 The co

llective modes of Laplacian matrices are related to skeleton springs 303.1.2 Non-skeleton springs ofKreveal chemically specific patterns in the proteinmechanical coupling network . . . . . . . . . . . . . . . . . . . . 303.1.3 Protein mechanical coupling network is sparse . . . . . . . . . . . . . 3

13.2 Protein mechanical couplings have heavy-tailed and scale-free network properties 323.2.1 The mechanical coupling networks in rat trypsin . . . . . . . . . . . . 333.2.2 The mechanical coupling networks in PDZ3 domain . . . . . . . . . . 343.3 Backbone and side-chain couplings exhibit different

patterns in their mechanicalhotspots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353.3.1 Mechanical hotspots of backbone-backbone couplings primarily locatein β-strands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363.3.2 Mechanical hotspots of side

-chain-side-chain couplings are different frombackbone-backbone couplings . . . . . . . . . . . . . . . . . . . . . . 373.3.3 Mechanical hotspots of backbone-side-chain have scattered couplings . 383.4 Emergence of long-range mechanical couplings from the prominent modes inrigidity graphs . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.5 Residue rigidity scores defined for backbone and side-chain mechanical couplings– a useful metric for biological functions . . . . . . . . . . . . . . . . . 413.6 Mechanical relay in rat trypsin due to unbinding of BPTI . . . . . . .

. . . . . 433.6.1 The mechanical relay in catalytic domain rearrangement . . . . . . . . 453.6.2 The mechanical relay leads to collapse of calcium-binding loop . . . . 453.6.3 Dynamic allostery from the catalytic domain to the activation domain . 463.7 Mechanical relay in PDZ3 domain due to binding

of CRIPT peptide . . . . . . 473.7.1 Mechanical relay due to hydrogen bonding . . . . . . . . . . . . . . . 473.7.2 Mechanical relay of hydrophobic interactions spread across the β-sandwich 483.7.3 Hotspots in mechanical relay are mostly functional residues . . . . . . 483.7.4 MSA motivated by mecha

nical relay illustrates the evolutionary constraintsof inter-domain allostery . . . . . . . . . . . . . . . . . . . . . 494 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 Figures and Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . 53Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Appendix A 附錄標題. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109List of Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Dr. Seuss Discovers: The Ocean

為了解決Rosetta的問題，作者Dr Seuss 這樣論述：

Theodor Seuss Geisel--aka Dr. Seuss--is one of the most beloved children’s book authors of all time. From The Cat in the Hat to Oh, the Places You’ll Go!, his iconic characters, stories, and art style have been a lasting influence on generations of children and adults. The books he wrote and illust

rated under the name Dr. Seuss (and others that he wrote but did not illustrate, including some under the pseudonyms Theo. LeSieg and Rosetta Stone) have been translated into 45 languages. Hundreds of millions of copies have found their way into homes and hearts around the world. Dr. Seuss’s long li

st of awards includes Caldecott Honors, the Pulitzer Prize, and eight honorary doctorates. Works based on his original stories have won three Oscars, three Emmys, three Grammys, and a Peabody.

產後女性經歷身體變化之經驗探究：照片引談法的嘗試

為了解決Rosetta的問題，作者鄭雯璞 這樣論述：

本研究旨在探討在「產後快速回復身材的美麗媽媽」之形象建構漸趨普遍的台灣社會中，產後女性的產後身體經驗為何？為了貼近研究參與者的日常生活與身體實作，本研究嘗試使用照片引談法搭配訪談，並以「身體」為焦點，以敘事取向分析3位研究參與者的照片及故事。本研究發現研究參與者的經驗植基於台灣社會女性特質的母職及身形常規中。「產後快速恢復身材」、「看起來不像媽媽」等形象成為產後女性理所當然的目標。但產後女性並未從傳統母職中解放，逐漸興起的「美麗媽媽」標準疊加在既有母職要求之上。產後的日常身體實作要同時「做母親」，也要「做身材」。然而理想母職的複數內涵對於資源有限的中產階級女性來說難以達標，「做母親」與「做身

材」的身體實作時常互斥，兩者衝突之時，她們通常選擇放棄「做身材」，或以「為了家庭好」之名「做身材」。本研究同時發現情緒扮演的關鍵角色。若違反母職或身形常規，產後女性會感受到強烈的自我厭惡與羞愧自責因而自我規訓。違反常規的情緒持續擠壓她們「做自己」的身體與心理空間。社會對女性的規訓、相斥的身體實作、相對應的情緒與身體經驗持續交織，形成邊界動態變化的「做自己」。在這個過程中，透過情緒，「做自己」與「美麗媽媽」在產後女性心中產生連結，進一步鞏固了「美麗媽媽」等於「有自我」的理想，卻同時製造了不合格的「不夠美麗且沒有自己的媽媽」。根據以上結果，本研究建議助人工作者可以透過時刻反思，看見產後女性所處的結

構壓迫與違反常規的自我厭惡與愧疚自責，進而創造「容許不公平感受」的空間，以作為解構的可能。