Lehrstuhl für Umweltchemie und Analytische Chemie

C-11 could drastically increase the inhibitory activity. The paraconic acid (2S,3R,4S)-4-methyl-5-oxo-2-pentyl-tetrahydro-furan-3-carboxylic acid (12) was discovered to only inhibit tested Acinetobacter spp [...] including 1D and 2D NMR, HRMS, ECD spectra, UV, and IR as well as single crystal X-ray diffraction and quantum chemistry calculation, their structures were identified to be azaphilones sharing a 3,6a-dime [...] phodiesterase EDI3 in glycogen metabolism ( 2020 ) Leonhardt, Gregor M. ; Hengstler, Jan Georg ; Watzl, Carsten Show more The glycerophosphodiesterase EDI3 (endometrial differential 3) is a key enzyme …

(7) Not applicable 18×2 8× 2 0.72 10−2 Male vs female names Career vs family (9) 39k 0.72 10−2 8× 2 8× 2 1.89 10−4 Math vs arts Male vs female terms (9) 28k 0.82 < 10−2 8× 2 8× 2 0.97 .027 Science vs arts [...] 10−24 8× 2 8× 2 1.24 10−2 Mental vs physical disease Temporary vs permanent (23) 135 1.01 10−3 6× 2 7× 2 1.30 .012 Young vs old people’s names Pleasant vs unpleasant (9) 43k 1.42 < 10−2 8× 2 8× 2 −.08 0 [...] 16×2 25×2 1.50 10−4 Eur.-American vs Afr.-American names Pleasant vs unpleasant from (9) (7) Not applicable 16×2 8× 2 1.28 10−3 Male vs female names Career vs family (9) 39k 0.72 < 10−2 8× 2 8× 2 1.81 …

Multi-objective Analysis of Machine Learning Algorithms Using Model-based Optimization Techniques

●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● 1e−02 1e−01 1e+00 1e+01 1e+02 0.1 0.2 0.3 0.4 0.5 MMCE tra in in g tim e 0.05 0.2 0.5 Subsample Rate (b) SMBO Figure 3.3 Results from the multi-objective tunings [...] HYPERPARAMETER TUNING −10 0 10 −10 0 10 log2(C) lo g 2 (γ ) 0.1 0.2 0.3 0.4 MMCE (a) Grid Search −10 0 10 −10 0 10 log2(C) lo g 2 (γ ) 0.1 0.2 0.3 0.4 MMCE (b) SMBO Figure 3.2 Results of the single-objective tuning [...] 1 2 Optimization 3 2.1 Example: Support Vector Machines 5 2.2 Sequential model-based optimization 7 2.3 Multi-objective optimization 10 2.4 Contributed publications 12 3 Hyperparameter Tuning 15 3.1 The …

.................. 64 2.2.2 The model sample ........................................................................................................................... 64 2.2.3 Predictions of collective [...] proteins (PDB IDs 2NUZ, 2FMC). ʕʒ πhIŜƭƛȄ ˒Ґ πртϲ ˕Ґ πптϲ π̡ǎƘŜŜǘ ό9ȄǘŜƴŘŜŘ ǎǘNJdzŎǘdzNJŜύ wŀƴŘƻƳ /ƻƛƭ ǎƛŘŜ ŎƘŀƛƴǎ tNJƻǘŜƛƴ ōŀŎƪōƻƴŜ омлπƘŜƭƛȄ π̄ƘŜƭƛȄ ˒Ґ πмолϲ ˕Ґ молϲ ¢dzNJƴ INTRODUCTION ɀ 3. Protein structural [...] ............... 86 2.3.1. Introduction ..................................................................................................................................... 86 2.3.2. General initial assessment …

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a novel IST algorithm2 was proposed for solving GS- (i.e., where ) 2The authors refer to this as an EM algorithm, which, in this case, is an IST algorithm; see [37]. and GS- (i.e., where ) problems. • [...] no. 3, pp. 600–616, Mar. 1997. [48] R. Griesse and D. Lorenz, “A semismooth Newton method for Tikhonov functionals with sparsity constraints,” Inverse Probl., vol. 24, no. 3, 2008. [49] L. Grippo, F. L [...] (BPDN) in [15]) (2) where , (usually ), , denotes the standard Euclidean norm, and stands for the norm (for ), defined as . Problem (2) is closely related to the following two formulations: (3) frequently referred …

wild-type S E S 0 mutant 1 V Q E 3 mutant 2 M Y T 3 mutant 3 D Y D 3 mutant 4 G R A 3 mutant 5 G S Q 3 mutant 6 F G R 3 mutant 7 D R K 3 mutant 8 R V A 3 mutant 9 D S A 3 mutant 10 R D G 3 mutant 11 Q D F 3 mutant [...] perturbation buffer ka kd SES 3 1 2 VQE 1 2 3 MYT 1 3 3 DYD 2 5 5 GRA 2 2 4 GSQ 1 1 6 FGR 1 4 3 DRK 1 2 2 RVA 2 8 4 DSA 1 3 3 RDG 2 5 10 QDF 1 5 2 NES 2 8 11 SEA 2 2 2 SAS 2 6 4 AES 1 1 2 EES 1 5 5 Table 5.4: Number [...] 44 19 22 6 32 22 17 3. 5 3. 88 3. 54 3. 15 -3 .2 1 H is ti d in e 15 5. 2 9 6 16 1 16 20 2 45 .1 4. 29 4. 00 3. 47 -3 .7 3 Is ol eu ci n e 13 1. 2 80 50 49 28 72 53 83 44 .4 4. 02 3. 66 3. 08 -1 .7 6 L …

Case Study 4.1.2 The Mixed Methodology 4.2. Framework for Analysis 4.2.1 The Theoretical Framework 4.2.2 The Conceptual Framework 4.2.3 Analytical Framework 4.3 Methods of Data Collection 4.3.1 Study Sites [...] 1.1.2 Why Plan for Small Island Landscapes? 1.2 Rationale for Small Island Planning 1.3 The Research Objectives 1.4 Assumptions and Limitations in Doing Island Studies 1 2 2 3 3 4 4 5 Chapter Two 2. Theoretical [...] Three 3. Research Gap and Research Agenda 3.1 Small Islands Research Gaps 3.1.1 Spatial and Economic Integration of Small Islands 3.1.2 The Research Questions and Assumptions 3.2 The Research Agenda 3.2.1 …

Academic institutional entrepreneurs in Germany: navigating and shaping multi-level research commerc

Empreendedores Científicos e Gerentes de Pesquisa na formação do contexto de Hélice Tríplice. Definindo em documentos institucionais e em profundas entrevistas com Gerentes de Pesquisa e Cientistas no estado [...] Helix (2018) 5:13 Page 2 of 23 (Continued from previous page) automotivados e altamente criativos. Os Empreendedores Científicos estudados negociam seus arranjos institucionais e encontram soluções flexíveis [...] contratuais e de suas carreiras. O estudo identifica dois tipos de atuação usadas para formar o contexto de Hélice- Tríplice - auto-empreendedorismo e empreendedorismo institucional. Atividades autônomas e a confiança …

Microsoft Word - ITS_European_Congress_Helsinki_INSIGHT_v16.docx

Systems (ITS) in Dublin City, Ireland Dermot Kinane 1* , François Schnitzler 2 , Shie Mannor 2 , Thomas Liebig 3 , Katharina Morik 3 , Jakub Marecek 4 , Bernard Gorman 4 , Nikolaos Zygouras 5 , Yannis Katakis [...] 12 A. Artikis, M. Weidlich, F. Schnitzler, I. Boutsis, T. Liebig, N. Piatkowski, C. Bockermann, K. Morik, V. Kalogeraki, J. Marecek, A. Gal, S. Mannor, D. Gunopulos, and D. Kinane. (2014). “Heterogeneous [...] Kinane, D. (2013). INSIGHT Work Package 6 Document. Dublin. Land, K., Slosar, A., Lintott, C., Andreescu, D., Bamford, S., Murray, P., Nichol, R., Raddick, J., Schawinski,K., Szalay, A., Thomas, D., and …