Artificial organs - Biomaterials

Παραδόξως, παρά τις προόδους στον τομέα των μεταμοσχεύσεων μέχρι σήμερα, η ανεπάρκεια οργάνων παραμένει μια κύρια αιτία θνησιμότητας παγκοσμίως. Διάφοροι περιορισμοί, συμπεριλαμβανομένης της διαφοράς μεταξύ της διαθεσιμότητας οργάνων και της συνεχώς αυξανόμενης ανάγκης, έχουν φέρει στο επίκεντρο το πεδίο της βιο-μηχανικής λειτουργικών τεχνητών οργάνων και ιστών. Η μηχανική ιστών αντιπροσωπεύει ένα εξαιρετικά πολλά υποσχόμενο πεδίο για την αντιμετώπιση προβλημάτων που σχετίζονται με την ανεπάρκεια και τη βλάβη ιστών και οργάνων, συνδυάζοντας κύτταρα, βιοϋλικά, βιοχημικά και φυσικά σήματα για την παραγωγή δομών που βασίζονται σε ιστούς. Τα βιοτεχνητά όργανα κατασκευάζονται με τη χρήση κατάλληλων βιοϋλικών μέσω διαφόρων τεχνολογιών κατασκευής με στόχο την επιτυχή αντικατάσταση ή αποκατάσταση των εγγενών οργάνων. Οι τεχνολογίες τρισδιάστατης (3D) βιοεκτύπωσης αντιπροσωπεύουν τις υπερσύγχρονες τεχνολογίες κατασκευής πρόσθετων που χρησιμοποιούνται για το σχεδιασμό, την κατασκευή και τη βελτίωση βιονικών μοντέλων ιστών, οργάνων, οργανοειδών, καθώς και οργάνων σε τσιπ. Στόχος της παρούσας μελέτης είναι να παράσχει μια επισκόπηση των τεχνολογιών κατασκευής βιοτεχνητών οργάνων που μπορούν να χρησιμοποιηθούν για την παραγωγή ανθρώπινων οργάνων με βάση βιονικές αρχές, καθώς και να εντοπίσει μεθόδους για τη διασφάλιση της ποιότητάς τους με βάση το υπάρχον ευρωπαϊκό και αμερικανικό κανονιστικό πλαίσιο . Παρά το γεγονός ότι ο τομέας της βιομηχανικής οργάνων έχει αναπτυχθεί τρομερά τις τελευταίες δεκαετίες, υπάρχουν ακόμη κάποιες βελτιώσεις που πρέπει να γίνουν για την κλινική εφαρμογή και την εφαρμογή των διαφόρων υποσχόμενων εφαρμογών βιομηχανικών ιστών και οργάνων, που προβλέπει ένα σπουδαίο μέλλον.Paradoxically, despite advances in the field of transplantation to date, organ failure remains a major cause of mortality worldwide. Various constraints, including the disparity between organ availability and the ever-increasing need, have brought the field of bioengineering of functional artificial organs and tissues into focus. Tissue engineering represents an extremely promising field to address problems associated with tissue and organ failure and damage by combining cells, biomaterials, biochemical and physical signals to produce tissue-based structures. Bioartificial organs are constructed by using appropriate biomaterials through various manufacturing technologies with the goal of successfully replacing or restoring native organs. Three-dimensional (3D) bioprinting technologies represent the state-of-the-art additive manufacturing technologies used for the design, construction, and enhancement of bionic models of tissues, organs, organoids, as well as organs-on-a-chip. The aim of the present study is to provide an overview of bioartificial organ manufacturing technologies that can be used for the production of human organs based on bionic principles, as well as to identify methods to ensure their quality based on the existing European and American regulatory framework. Despite the fact that the field of bioengineering of organs has developed tremendously in the last decades, there are still some improvements to be made for the clinical implementation and the implementation of the various promising applications of bioengineered tissues and organs, which predicts a great future

Near-Optimal Online Multiselection in Internal and External Memory

We introduce an online version of the multiselection problem, in which q selection queries are requested on an unsorted array of n elements. We provide the first online algorithm that is 1-competitive with Kaligosi et al. [ICALP 2005] in terms of comparison complexity. Our algorithm also supports online search queries efficiently. We then extend our algorithm to the dynamic setting, while retaining online functionality, by supporting arbitrary insertions and deletions on the array. Assuming that the insertion of an element is immediately preceded by a search for that element, we show that our dynamic online algorithm performs an optimal number of comparisons, up to lower order terms and an additive O(n) term. For the external memory model, we describe the first online multiselection algorithm that is O(1)-competitive. This result improves upon the work of Sibeyn [Journal of Algorithms 2006] when q > m, where m is the number of blocks that can be stored in main memory. We also extend it to support searches, insertions, and deletions of elements efficiently

How Branch Mispredictions Affect Quicksort

We explain the counterintuitive observation that finding “good” pivots (close to the median of the array to be partitioned) may not improve performance of quicksort. Indeed, an intentionally skewed pivot improves performance. The reason is that while the instruction count decreases with the quality of the pivot, the likelihood that the direction of a branch is mispredicted also goes up. We analyze the effect of simple branch prediction schemes and measure the effects on real hardware

Cycle bases of graphs and sampled manifolds

Point samples of a surface in R³ are the dominant output of a multitude of 3D scanning devices. The usefulness of these devices rests on being able to extract properties of the surface from the sample. We show that, under certain sampling conditions, the minimum cycle basis of a nearest neighbor graph of the sample encodes topological information about the surface and yields bases for the trivial and non-trivial loops of the surface. We validate our results by experiments

Theory and Implementation of Online Multiselection Algorithms

Abstract. We introduce a new online algorithm for the multiselection problem which performs a sequence of selection queries on a given unsorted array. We show that our online algorithm is 1-competitive in terms of data comparisons. In particular, we match the bounds (up to lower order terms) from the optimal offline algorithm proposed by Kaligosi et al.[ICALP 2005]. We provide experimental results comparing online and offline algorithms. These experiments show that our online algorithms require fewer comparisons than the best-known offline algorithms. Interestingly, our experiments suggest that our optimal online algorithm (when used to sort the array) requires fewer comparisons than both quicksort and mergesort.