nmp的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列推薦必買和特價產品懶人包

Bioactive Functionalisation of Silicones With Polysaccharides

為了解決nmp的問題，作者Bracic, Matej/ Strnad, Simona/ Zemljic, Lidija Fras 這樣論述：

This book covers the functionalisation of silicone surfaces with polysaccharides to improve their antimicrobial and antifouling properties, thus reducing the implant-related infections. The authors describe how silicone surfaces were chosen because silicone exhibits excellent biocompatible propertie

s and is already being used for medical implants such as catheters, breast implants, prosthetics etc. The potential of polysaccharides such as cellulose, chitosan, hyaluronic acid, and other natural substances such as natural surfactants as coatings for silicones are also discussed, their effects ar

e evaluated. With the aging of the population, the number of medical implants is growing and with it the number of infections associated with the use of implants. Dr. Matej Bračič is an expert in studying interactions of molecular and polymer dispersions in liquids with solid surfaces and biologic

al evaluation of both surfaces. His research work is focused on the preparation and characterization of nano and micro-dispersion, the preparation and characterization of solid surfaces by electrospinning, spin-coating, dip-coating and dip-casting methods, interactions with biomolecules (proteins, e

nzymes, bacteria) and the transfer of knowledge into the field of sensors for the production of bioactive sensors. His bibliography covers 65 units, of which 21 are original scientific articles, 29 are contributions at national and international conferences and 14 are final reports on national and i

nternational projects. He has 91 pure citations in the last 10 years and an h index of 7. He received an award at the International Conference IN-TECH 2014: Award for Science and Technology Transfer (World Association of Innovative Technologies) on 12 September 2014 in Leiria, Portugal. He is curren

tly working as a postdoctoral researcher at the Laboratory for Characterisation and Processing of Polymers, Institute of Engineering Materials and Design, University of Maribor.Prof. Dr. Simona Strnad, Dr. Tech. Sci. is an expert in structure and properties of fibrous materials and advanced material

s engineering. Her research work is focused on investigations of structure/properties relationships of polymer materials and surface functionalization and characterization. Her bibliography comprises: 351 bibliographic items including 63 scientific papers, 7 Invited lectures, 6 book chapters, 2 pate

nts and more than 60 research and industrial project collaborations, among them FP6 NMP3-CT-2005-500375: EPNOE - Polysaccharides; Network of Excellence ＂Polysaccharides＂ [COBISS.SI-ID 13864470]; FP7 NMP-2007-2.1.1-1 - SURFUNCELL - Nanostructured polymer-matrix composites ＂Surface functionalization o

f cellulose matrices using coatings of functionalised polysaccharides with embedded nano-particles＂; EUREKA FeVal E!5851, EUREKA Vascucharge E!2866, EUREKA Eurocharge E!2821; EUREKA Hightampons E!3602. Currently she has a full professor position at the Institute of Engineering Materials and Design,

University of Maribor.Prof. Dr. Lidija Fras Zemljič (born 1973) received a PhD in Chemistry at University Maribor in 2004 for her research on bio-functionalisation for achieving improved sorption properties. She further develops her skins and gain knowledge during her postdoctoral stay at Laboratory

of ＂Fisica Aplicada＂, University of Granada, Spain and Laboratory for Forest Products Chemistry, Helsinki University of Technology, Finland during 2003-2004 years. She was/is a principal investigator and project manager in many national (ARSS agency) and industry funded research projects (EURECA; C

OST) and collaborated in many FP6, FP7 and H2020 research and industrial project collaborations, among them FP6 NMP3-CT-2005-500375: EPNOE - Polysaccharides; Network of Excellence ＂Polysaccharides＂ [COBISS.SI-ID 13864470]; FP7 NMP-2007-2.1.1-1 - SURFUNCELL - Nanostructured polymer-matrix composites

＂Surface functionalization of cellulose matrices using coatings of functionalised polysaccharides with embedded nano-particles＂, etc.Her bibliography comprises: 304 bibliographic items including 67 scientific papers, 5 Invited lectures, 7 book chapters, 2 patents. Currently she has a full professor

position at the Institute of Engineering Materials and Design, University of Maribor.

nmp進入發燒排行的影片

多功能碳材複合薄膜之製備與性質探討

為了解決nmp的問題，作者林立軒 這樣論述：

本研究之主要目的為製備多功能碳材複合薄膜，並透過探討多形態碳材組成與薄膜性質之相關性，研發出新型多功能導電彈性材料。其係以熱塑性聚氨酯薄膜作為基材，將其表面塗佈多層石墨烯、多壁奈米碳管和導電碳黑等碳材漿料，針對碳材薄膜之電性、延展性與耐磨性與形態結構等物性，進行結果之對照分析。第一部分，在熱塑性聚氨酯表層塗佈石墨烯/PU樹脂分散液，分別比較不同濃度以及不同厚度之石墨烯複合薄膜的性質變化。實驗結果發現G-20薄膜拉伸後之片電阻率能夠穩定維持在105 Ω/s，其耐磨次數可達2000轉；G-10薄膜之最大應力延伸率可達1800 %。第二部分，根據第一部分的實驗結果，將石墨烯/PU樹脂分散液均勻混合

奈米碳管與碳黑，調配出相近碳固含量之漿料進行塗佈，分別測量不同形態碳材之結合對於薄膜的性質變化。實驗數據得知G-T薄膜拉伸後之片電阻率可以穩定維持在105 Ω/sq，其耐磨次數可達2000轉；G-T-B薄膜拉伸後之片電阻率能夠穩定維持在106 Ω/sq和最大延伸率可達1500 %。綜合以上實驗，我們發現石墨烯/PU樹脂分散液濃度和厚度對於薄膜延伸率和電性均有影響，添加了奈米碳管與碳黑後，薄膜之導電性以及耐磨性皆提升，並透過高解析掃描式電子顯微鏡測量薄膜表面形態構造，發現石墨烯(2D)結合碳黑(0D)與奈米碳管(1D)構築出三維碳材結構，碳材以點線面多形態結構組成，創造出優良之導電網路，這將有助

於未來設計新型多功能導電彈性材料。

多 合成副反應（英文）

為了解決nmp的問題，作者YI YANG 這樣論述：

作者在十多年多肽合成第壹手經驗的基礎之上，結合大量相關文獻完成的。全書系統地介紹了多肽合成中最常見的副反應，其產生的機理，以及相應的解決方案。其中很多副反應的產生是在GMP生產條件下被發現並加以研究的，其形成機理與生產工藝的開發緊密相關。多肽雜質的形成對於多肽類API的GMP生產具有非常關鍵的影響，因此檢測和分析多肽雜質對成功的API工業生產至關重要。而掌握多肽副反應產生的機理、分析手段及相應的優化方案，則是整個多肽API工藝開發和生產環節中的核心要素。《多肽合成副反應(英文版)》可供學術界與工業界相關人員參考使用。 Yi Yang，received his PhD from Bielefel

d University，Germany，and has had 10 years of relevant experience in academic research and industrial development.He is currently Senior Research Scientist，Chemical Development，Global Pharmaceutical R & D，Ferring Pharmaceuticals A／S，Copenhagen，Denmark. Preface1 Peptide Fragmentation／Deletio

n Side Reactions1.1 Acidolysis of Peptides Containing N—Ac—N—alkyl—Xaa Motif1.2 Des—Ser／Thr Impurities Induced by O—acyllsodipeptide Boc—Ser／Thr（Fmoc—Xaa）—OH as Building Block for Peptide Synthesis1.3 Acidolysis of—N—acyl—N—alkyl—Aib—Xaa—Bond1.4 Acidolysis of—Asp—Pro—Bond1.5 Autodegradation of Pepti

de N—Terminal H—His—Pro—Xaa—Moiety1.6 Acidolysis of the Peptide C—Terminal—N—Me—Xaa1.7 Acidolysis of Peptides with N—Terminal FITC Modification1.8 Acidolysis of Thioamide Peptide1.9 Deguanidination Side Reaction on Arg1.10 DKP（2，5—Diketopiperazine）FormationReferences2 β—Elimination Side Reactions2.1

β—Elimination of Cys Sulfhydryl Side Chain2.2 β—Elimination of Phosphorylated Ser／Thr References3 Peptide Global Deprotection／Scavenger—Induced Side Reactions3.1 Tert—Butylation Side Reaction on Trp During Peptide Global Deprotection3.2 Trp Alkylation by Resin Linker Cations During Peptide Cleavage

／Global Deprotection3.3 Formation of Trp—EDT and Trp—EDT—TFA Adduct in Peptide Global Deprotection3.4 Trp Dimerization Side Reaction During Peptide Global Deprotection3.5 Trp Reduction During Peptide Global Deprotection3.6 Cys Alkylation During Peptide Global Deprotection3.7 Formation of Cys—EDT Add

ucts in Peptide Global Deprotection Reaction3.8 Peptide Sulfonation in Side Chain Global Deprotection Reaction3.9 Premature Acm Cleavage Off Cys（Acm）and Acm S→O Migration During Peptide Global Deprotection3.10 Methionine Alkylation During Peptide Side Chain Global Deprotection with DODT as Scavenger

3.11 Thioanisole—Induced Side Reactions in Peptide Side Chain Global DeprotectionReferences4 Peptide Rearrangement Side Reactions4.1 Acid Catalyzed Acyl N→O Migration and the Subsequent Peptide Acidolysis4.2 Base Catalyzed Acyl O→N Migration4.3 His—Nim—Induced Acyl MigrationReferences5 Side Reaction

s Upon Amino Acid／Peptide Carboxyl Activation5.1 Formation of N—Acylurea Upon Peptide／Amino Acid—Carboxyl Activation by DIC5.2 Uronium／Guanidinium Salt Coupling Reagents—Induced Amino Group Guanidination Side Reactions5.38—Lactam Formation Upon Arg Activation Reaction5.4 NCA Formation Upon Boc／Z—Ami

no Acid Activation5.5 Dehydration of Side Chain—Unprotected Asn／Gln During Carboxyl—Activation5.6 Formation of H—β—Ala—OSu from HOSu—Carbodiimide Reaction During Amino Acid Carboxyl—Activation5.7 Benzotriazinone Ring Opening and Peptide Chain Termination During Carbodiimide／HOOBt Mediated Coupling R

eactions5.8 Peptide Chain Termination Through the Formation of Peptide N—Terminal Urea in CDI—Mediated Coupling Reaction5.9 Guanidino or Hydantoin—2—Imide Formation from Carbodiimide and Na Group on Amino Acid／Peptide5.10 Side Reactions—Induced by Curtius Rearrangement on Peptide Acyl Azide5.11 Form

ation of Pyrrolidinamide—Induced by Pyrrolidine Impurities in Phosphonium SaltReferences6 Intramolecular Cyclization Side Reactions6.1 AspartimideFormation6.1.1 Factors That Influence Aspartimide Formation6.1.2 Solutions for Aspartimide Formation6.2 Asn／Gln Deamidation and Other Relevant Side Reacti

ons6.2.1 Mechanism of Asn／Gln Deamidation6.2.2 Factors Impacting on Asn／Gln Deamidation6.2.3 Influences of Asn／Gln Deamidation on Peptide Chemical Synthesis6.3 Pyroglutamate Formation6.4 Hydantoin Formation6.5 Side Reactions on N—Terminal Cys（Cam）and N—Bromoacetylated PeptideReferences7 Side Reactio

ns on Amino Groups in Peptide Synthesis7.1 Nα—Acetylation Side Reactions7.2 Trifluoroacetylation Side Reactions7.3 Formylation Side Reactions7.3.1 Trp（For）—Induced Peptide Formylation7.3.2 Formic Acid—Induced Peptide Formylation7.3.3 DMF—Induced Peptide Formylation7.4 Peptide N—Alkylation Side React

ions7.4.1 Chloromethyl Resin Induced Peptide N—Alkylation Side Reactions7.4.2 Peptide N—Alkylation During Deblocking of Nα—Urethane Protecting Group7.4.3 Peptide N—Alkylation During Global Deprotection7.4.4 N—Alkylation Syde Reaction on N—Terminal His via Acetone—Mediated Enamination7.5 Side Reactio

ns During Amino Acid Nα—Protection（Fmoc—OSu Induced Fmoc—β—Ala—OH and Fmoc—β—Ala—AA—OH Dipeptide Formation）References8 Side Reactions on Hydroxyland Carboxyl Groups in Peptide Synthesis8.1 Side Reactions on Asp／Glu Side Chain and Peptide Backbone Carboxylate8.1.1 Base—Catalyzed Asp／Glu（OBzl）Transest

erification Side Reaction During the Loading of Chloromethyl Resin8.1.2 Esterification Side Reactions on Asp／Glu During Peptidyl Resin Cleavage and Product Purification8.2 Side Reactions on Ser／Thr Side Chain Hydroxyl Groups8.2.1 Alkylation Side Reactions on Ser／Thr Side Chain Hydroxyl Groups8.2.2 A

cylation Side Reactions on Ser／Thr Side Chain Hydroxyl Groups8.2.3 β—Elimination Side Reactions on Ser／Thr8.2.4 N—Terminal Ser／Thr—Induced Oxazolidone Formation Side Reactions8.2.5 Ser／Thr—Induced Retro Aldol Cleavage Side Reaction References9 Peptide Oxidation／Reduction Side Reactions9.1 Oxidation

Side Reactions on Cys9.2 Oxidation Side Reactions on Met9.3 Oxidation Side Reactions on Trp9.4 Oxidation Side Reactions on Other Amino Acids and at Nonsynthetic Steps9.5 Peptide Reduction Side ReactionsReferences10 Redundant Amino Acid Coupling Side Reactions10.1 Dipeptide Formation During Amino Aci

d Nα—Fmoc Derivatization10.2 Redundant Amino Acid Coupling via Premature Fmoc Deprotection10.2.1 Lys—Nε—Induced Fmoc Premature Cleavage10.2.2 Nα—Proline—Induced Fmoc Premature Cleavage10.2.3 DMF／NMP—Induced Fmoc Premature Cleavage10.2.4 Residual Piperidine—Induced Fmoc Premature Cleavage10.2.5 DMAP／

DIEA—Induced Fmoc Premature Cleavage10.2.6 Hydrogenation—Induced Fmoc Premature Cleavage10.2.7 Fmoc Deblocking in the Starting Material10.3 Redundant Amino Acid Coupling Induced by NCA Formation10.4 His—Nim Promoted Gly Redundant Incorporation10.5 Redundant Coupling Induced by the Undesired Amino Ac

id—CTC Resin Cleavage10.6 Redundant Amino Acid Coupling Induced by Insuffiaent Resin Rinsing10.7 Redundant Amino Aad Coupling Induced by Overacylation Side ReactionReferences……11 Peptide Racemization12 Side Reactions in Peptide Phosphorylation13 Cys Disulfide—Related Side Reactions in Peptide Synthe

sis14 Solvent—Induced Side Reactions in Peptide SynthesisAppendix Ⅰ Molecular Weight Deviation of Peptide ImpurityAppendix Ⅱ List of AbbreviationsSubject Index

基於單影像之六自由度物體姿態估測

為了解決nmp的問題，作者洪金利 這樣論述：

Dealing with the object pose estimation from a single RGB image is very challenging since 6 degree-of-freedom (6DoF) parameters have to be predicted without using the spatial depth information. Since direct regression of the pose parameters by using the deep neural network was reportedly poor and t

hen attaching with the refinement module to improve the accuracy causes much time consumption, in this work, we propose several techniques of top-down or bottom-up approaches to predict indirect feature maps instead from which single or multiple object poses can be recovered by using sophisticated p

ost-processing algorithms.Since there are four possible scenarios where single/multiple objects in the same/different classes can appear in the image, the corresponding output feature maps are predicted differently. For a single object scenario, unit-vector fields are predicted. These features are c

omposed of many unit-vectors pointing from pixels within the object mask to the pre-defined 2D object keypoints where their corresponding 3D object keypoints are distributed optimally on the 3D object surface based on the keypoint distances and object surface curvatures. From some pairs of the predi

cted unit-vectors, 2D projected keypoints can be voted and determined, so that PnP algorithm can be applied to estimate the pose. To deal with multiple objects even in the same or different classes, sufficient and informative output feature maps need to be predicted. Different from object keypoints,

6D coordinate maps which form the main features can be considered as a bunch of 3D point clouds for pose parameter calculation when their 2D-3D correspondences are also established. 6D coordinate maps contains two parts: front- and rear-view 3D coordinate maps. 3D coordinate map is actually a 2D ma

p where each pixel records 3D coordinates of a point in the object CAD model which projects to that 2D pixel location. Via 3D/6D coordinate maps, instance 2D-3D correspondences of a large point set can be built and PnP algorithm combined with RANSAC scheme to overcome the outliers or noise can be us

ed to estimate multiple object poses. Even though in this case, 2D object keypoints can no longer be used to estimate multiple poses, they can be defined as single/multiple reference points for identifying all object instance masks even in the presence of heavy occlusion. We are also interested in o

vercoming some problems related to the missing information and symmetry ambiguity encountered when generating the ground truth of 6D coordinate maps.Our studies show that our single pose estimation method using unit-vector fields can achieve an outstanding accuracy if compared to other top-down stat

e-of-the-art methods without including refinement modules. It has a good algorithm to identify the designated object keypoints from which the predicted feature maps are trained with the effective loss functions, but it has a slower inference speed when multiple object poses are taken into considerat

ion. On the other hand, our 6D coordinate maps, combining with the information from two opposite views, are capable of providing more constraints for network optimization and hence helpful for pose estimation accuracy. Our methods using 6D coordinate maps can achieve great performances if compared t

o other multiple object pose estimation methods.