Selected papers from the 15th and 16th international conference on Computational Intelligence Methods for Bioinformatics and Biostatistics

Funding Information: CIBB 2019 was held at the Department of Human and Social Sciences of the University of Bergamo, Italy, from the 4th to the 6th of September 2019 []. The organization of this edition of CIBB was supported by the Department of Informatics, Systems and Communication of the University of Milano-Bicocca, Italy, and by the Institute of Biomedical Technologies of the National Research Council, Italy. Besides the papers focused on computational intelligence methods applied to open problems of bioinformatics and biostatistics, the works submitted to CIBB 2019 dealt with algebraic and computational methods to study RNA behaviour, intelligence methods for molecular characterization and dynamics in translational medicine, modeling and simulation methods for computational biology and systems medicine, and machine learning in healthcare informatics and medical biology. A supplement published in BMC Medical Informatics and Decision Making journal [] collected three revised and extended papers focused on the latter topic.publishersversionpublishe

Determination of the cultivar and aging of Sicilian olive oils using HPLC-MS and linear discriminant analysis

A large number of certified samples (84) of Sicilian olive oils arising from the eight cultivars most represented in Sicily (Biancolilla, Cerasuola, Moresca, Nocellara del Belice, Nocellara Etnea, Oglialora Messinese, Brandofino and Tonda Iblea) have been collected and analyzed by HPLC/MS using an atmospheric pressure chemical ionization (APCI) source. The sample preparation is very simple; in fact, the oil samples are diluted without any chemical derivatization. A following statistical data treatment by general discriminant analysis (GDA) allows the determination of the olive oil cultivar. Furthermore, changes in the composition of glyceridic components of the olive oils lead to easy discrimination between fresh oils and 1-year-old samples

Analysis of normal human retinal vascular network architecture using multifractal geometry

AIM: To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS: Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software. RESULTS: The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα=αmax - αmin) and the spectrum arms’ heights difference (│Δf│) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, D0=1.7014±0.0057; D1=1.6507±0.0058; D2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions, D0=1.6303±0.0051; D1=1.6012±0.0059; D2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα) and the spectrum arms’ heights difference (│Δf│) of the segmented versions was slightly greater than the skeletonised versions. CONCLUSION: The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases

Chapter Introduction

Through studies of beheaded Irish traitors, smugglers hung in chains on the English coast, suicides subjected to the surgeon's knife in Dresden and the burial of executed Nazi war criminals, this volume provides a fresh perspective on the history of capital punishment. This book has two open access chapters under a CC BY license

Introduction: A Global History of Execution and the Criminal Corpse

Capital punishment is an historical universal — it has been practiced at some point in the history of virtually all known societies and places. That is not to say, however, that it is an historical constant — the use, form, function and meaning of execution has varied greatly across different historical contexts. This is likewise true for an important — although relatively neglected — aspect of capital punishment: the fate of the criminal body after execution. This chapter is an introduction to the volume. This is a chapter from A Global History of Execution and the Criminal Corpse edited by Richard Ward. This chapter is available open access under a CC BY license

Improvement of phonemic fluency following leftward prism adaptation

Anatomo functional studies of prism adaptation (PA) have been shown to modulate a brain frontal-parieto-temporal network, increasing activation of this network in the hemisphere ipsilateral to the side of prism deviation. This effect raises the hypothesis that left prism adaptation, modulating frontal areas of the left hemisphere, could modify subjects' performance on linguistic tasks that map on those areas. To test this hypothesis, 51 healthy subjects participated in experiments in which leftward or rightward prism adaptation were applied before the execution of a phonemic fluency task, i.e., a task with strict left hemispheric lateralization onto frontal areas. Results showed that leftward PA significantly increased the number of words produced whereas rightward PA did not significantly modulate phonemic fluency. The present findings document modulation of a language ability following prism adaptation. The results could have a huge clinical impact in neurological populations, opening new strategies of intervention for language and executive dysfunctions

Tight Upper and Lower Bounds on Suffix Tree Breadth

The suffix tree - the compacted trie of all the suffixes of a string - is the most important and widely-used data structure in string processing. We consider a natural combinatorial question about suffix trees: for a string S of length n, how many nodes nu(S)(d) can there be at (string) depth d in its suffix tree? We prove nu(n, d) = max(S) (is an element of Sigma n) nu(S)(d) is O ((n/d) log(n/d)), and show that this bound is asymptotically tight, describing strings for which nu(S)(d) is Omega((n/d)log(n/d)). (C) 2020 Elsevier B.V. All rights reserved.Peer reviewe

Thirty-Eighth Annual Commencement Exercises

Order of Exercises Processional: Rabbi Herbert C. Dobrinsky, Vice President for University Affairs, Yeshiva University; Herald Presiding: Selma Botman, Provost and Vice President for Academic Affairs, Yeshiva University; Chief Marshal Richard M. Joel, President, Yeshiva University National Anthem: Cantor Ira W. Heller, Class of 2008 Invocation: Rabbi Ozer Glickman, Adjunct Professor, Benjamin N. Cardozo School of Law Welcome: Shai Y. Waisman, Vice Chair, Cardozo Board of Overseers, Benjamin N. Cardozo School of Law; Class of 1996 Remarks: Melanie Leslie, Dean, Benjamin N. Cardozo School of Law Commencement Address: The Honorable Robert Katzmann, Chief Judge, United States Court of Appeals, Second Circuit Alumni Greeting: Alissa D. Makower, Chair, Alumni Association, Benjamin N. Cardozo School of Law; Class of 1992 Student Remarks: Terel R. Watson, Class of 2016 Student Bar Association Awards: Zachary S. Beal, Class of 2016 Awards and Honors: Richard Bierschbach, Vice Dean, Benjamin N. Cardozo School of Law; Head Marshal Conferring of Honorary Doctor of Laws: President Joel Conferring of Master of Laws Degrees: President Joel Dean Leslie Conferring of Juris Doctor Degrees: President Joel Dean Leslie Hatikvah: Cantor Heller Recessionalhttps://larc.cardozo.yu.edu/pre-19-programs/1036/thumbnail.jp