This book constitutes the proceedings of the 9th International Conference on Exploring Services Science, IESS 2018, held in Karlsruhe, Germany, in September 2018. The 30 papers presented in this volume were carefully reviewed and selected from 67 submissions. The book is structured in six parts, each featuring contributions describing current research in a particular domain of service science: Service Design and Innovation; Smart Service Processes; Big Data in Services; Service Topics Open Exploration; Design Science Research in Services. The book offers an extended, ICT-focused vision on services and addresses multiple relevant aspects, including underlying business models, the necessary processes and technological capabilities like big data and machine learning. The academic work showcased at the conference should help to advance service science and its application in practice.

This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure.

This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.

This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.

This research was designed to provide an insight into the state of occlusal patterns, tooth size and arch dimension of the primary dentition in a group of preschool Egyptian and Yemeni children. A total of 1113 Egyptian and Yemeni children aged from 3-5 years were examined. A sample of 597 children (320 girls and 277 boys) was selected from the examined children to meet the following criteria; to have a full complement of primary dentition, no missing teeth, no interproximal carious lesions and to be free from any dental malformations. Children with systemic health disease or children with tendency to bruxism and abnormal habits were excluded. For each subjects an alginate impression was taken for both dental arches and poured in dental stone, to produce dental casts on which the following measurements were recorded for each arch; tooth size, arch dimensions, occlusal relationships and the presence or absence of spacing and crowding. A digital calliper was used to record the measurements. The recorded data was tabulated and statistically analyzed with SPSS 20.0(r) (Statistical Package for Scientific Studies) for Windows.