Bone diagenesis: the mysteries of the petrous pyramid

The discovery of petrous bone as an excellent repository for ancient biomolecules has been a turning point in biomolecular archaeology, especially in the recovery of ancient genomes. Although the information extracted by the biochemical analyses of petrous bone can be valuable, the processes are destructive, expensive and time consuming, while excessive and uncontrolled sampling could result in loss of this valuable resource for future research. This study reports on the histological (optical microscopy), physical (FTIR-ATR), elemental (CN), biomechanical (nanoindentation) and biochemical (collagen and DNA analysis) preservation of 272 bones spanning from c. 10.000 BC to c. 1850 AD, including 108 petrous bones. Through the combined application of a number of diagenetic parameters (general histological index; infrared splitting factor; carbonate/phosphate ratio; amide/phosphate ratio; col wt. %; % C, % N and C/N of whole bone and collagen; hardness, elastic modulus, % endogenous DNA), new insights into petrous bone micromorphological and diagenetic characteristics, inter-site, intra-site, intra-individual and intra-bone diagenetic variability, and new evidence to enhance successful screening of archaeological bone prior to aDNA and collagen analysis is presented. Specifically, the petrous bone microstructure consists of highly osteocytic woven and lamellar-like tissues, and osteons occur in at least two directions (transverse and longitudinal). Despite its stunning micromorphological characteristics, the biomechanical properties and diagenetic characteristics of petrous bone do not differ significantly from those of long bones. Inter-site and intra-site diagenetic variability is mostly affected by the site hydrology, while different types of burials can influence the microenvironment conditions and leave distinctive marks on bone histology. No intra-individual patterns, which could also favour the gut origin of microbial attack in bone, or intra-bone variability are observed in any of the diagenetic parameters. Screening archaeological bone for collagen preservation can be enhanced using the % C of whole bone which is equally strong as % N of whole bone collagen predictor, while the IRSF ( 0.15) indices can distinguish bones containing >1 % endogenous DNA with a success rate of c. 85 % as bioapatite preservation is associated with loss of DNA

An evaluation of time series forecasting models on water consumption data: A case study of Greece

In recent years, the increased urbanization and industrialization has led to a rising water demand and resources, thus increasing the gap between demand and supply. Proper water distribution and forecasting of water consumption are key factors in mitigating the imbalance of supply and demand by improving operations, planning and management of water resources. To this end, in this paper, several well-known forecasting algorithms are evaluated over time series, water consumption data from Greece, a country with diverse socio-economic and urbanization issues. The forecasting algorithms are evaluated on a real-world dataset provided by the Water Supply and Sewerage Company of Greece revealing key insights about each algorithm and its use

Preparation of bone powder for FTIR-ATR analysis: the particle size effect : The particle size effect

Fourier transform infrared (FTIR) spectroscopy using attenuated total reflection (ATR) is commonly used for the examination of bone. During sample preparation bone is commonly ground, changing the particle size distribution. Although previous studies have examined changes in crystallinity caused by the intensity of grinding using FTIR, the effect of sample preparation (i.e. particle size and bone tissue type) on the FTIR data is still unknown. This study reports on the bone powder particle size effects on mid-IR spectra and within sample variation (i.e. periosteal, mesosteal, trabecular) using FTIR-ATR. Twenty-four archaeological human and faunal bone samples (5 heated and 19 unheated) of different chronological age (Neolithic to post-Medieval) and origin (Belgium, Britain, Denmark, Greece) were ground using either (1) a ball-mill grinder, or (2) an agate pestle and mortar, and split into grain fractions (>500 μm, 250–500 μm, 125–250 μm, 63–125 μm, and 20–63 μm). Bone powder particle size has a strong but predictable effect on the infrared splitting factor (IRSF), carbonate/phosphate (C/P) ratio, and amide/phosphate (Am/P) values. The absorbance and positions of the main peaks, the 2nd derivative components of the phosphate and carbonate bands, as well as the full width at half maximum (FWHM) of the 1010 cm−1 phosphate peak are particle size dependent. This is likely to be because of the impact of the particle size on the short- and long-range crystal order, as well as the contact between the sample and the prism, and hence the penetration depth of the IR light. Variations can be also observed between periosteal, cortical and trabecular areas of bone. We therefore propose a standard preparation method for bone powder for FTIR-ATR analysis that significantly improves accuracy, consistency, reliability, replicability and comparability of the data, enabling systematic evaluation of bone in archaeological, anthropological, paleontological, forensic and biomedical studies

Deploying Semantic Web Technologies for Information Fusion of Terrorism-related Content and Threat Detection on the Web

The Web and social media nowadays play an increasingly significant role in spreading terrorism-related propaganda and content. In order to deploy counterterrorism measures, authorities rely on automated systems for analysing text, multimedia, and social media content on the Web. However, since each of these systems is an isolated solution, investigators often face the challenge of having to cope with a diverse array of heterogeneous sources and formats that generate vast volumes of data. Semantic Web technologies can alleviate this problem by delivering a toolset of mechanisms for knowledge representation, information fusion, semantic search, and sophisticated analyses of terrorist networks and spatiotemporal information. In the Semantic Web environment, ontologies play a key role by offering a shared, uniform model for semantically integrating information from multimodal heterogeneous sources. An additional benefit is that ontologies can be augmented with powerful tools for semantic enrichment and reasoning. This paper presents such a unified semantic infrastructure for information fusion of terrorism-related content and threat detection on theWeb. The framework is deployed within the TENSOR EU-funded project, and consists of an ontology and an adaptable semantic reasoning mechanism. We strongly believe that, in the short- and long-term, these techniques can greatly assist Law Enforcement Agencies in their investigational operations

Screening archaeological bone for palaeogenetic and palaeoproteomic studies.

The recovery and analysis of ancient DNA and protein from archaeological bone is time-consuming and expensive to carry out, while it involves the partial or complete destruction of valuable or rare specimens. The fields of palaeogenetic and palaeoproteomic research would benefit greatly from techniques that can assess the molecular quality prior to sampling. To be relevant, such screening methods should be effective, minimally-destructive, and rapid. This study reports results based on spectroscopic (Fourier-transform infrared spectroscopy in attenuated total reflectance [FTIR-ATR]; n = 266), palaeoproteomic (collagen content; n = 226), and palaeogenetic (endogenous DNA content; n = 88) techniques. We establish thresholds for three different FTIR indices, a) the infrared splitting factor [IRSF] that assesses relative changes in bioapatite crystals' size and homogeneity; b) the carbonate-to-phosphate [C/P] ratio as a relative measure of carbonate content in bioapatite crystals; and c) the amide-to-phosphate ratio [Am/P] for assessing the relative organic content preserved in bone. These thresholds are both extremely reliable and easy to apply for the successful and rapid distinction between well- and poorly-preserved specimens. This is a milestone for choosing appropriate samples prior to genomic and collagen analyses, with important implications for biomolecular archaeology and palaeontology

Le projet CRUMBEL et l'apport de la recherche l'archéométrique

The CRUMBEL project aims to investigate the mobility of the former population in Belgium from the Neolithic period until the Early Middle Ages. To reach these research goals different topics will be studied. In a preliminary phase, the ancient collections of cremated bone will be documented. A selection of these funerary sites will be studied to understand the mobility using different archaeometric approaches as stable isotopes and radiocarbon dating to obtain reliable information on earlier mobility in Belgium

Diagenesis of archaeological bone and tooth

An understanding of the structural complexity of mineralised tissues is fundamental for exploration into the field of diagenesis. Here we review aspects of current and past research on bone and tooth diagenesis using the most comprehensive collection of literature on diagenesis to date. Environmental factors such as soil pH, soil hydrology and ambient temperature, which influence the preservation of skeletal tissues are assessed, while the different diagenetic pathways such as microbial degradation, loss of organics, mineral changes, and DNA degradation are surveyed. Fluctuating water levels in and around the bone is the most harmful for preservation and lead to rapid skeletal destruction. Diagenetic mechanisms are found to work in conjunction with each other, altering the biogenic composition of skeletal material. This illustrates that researchers must examine multiple diagenetic pathways to fully understand the post-mortem interactions of archaeological skeletal material and the burial environment

Ανάλυση σε πραγματικό χρόνο δεδομένων κινητικότητας και ειδικά η ανάπτυξη μεθοδολογιών για την αποτελεσματική ανίχνευση μη αναμενόμενων συμπεριφορών και την κατηγοριοποίηση τροχιών

Nowadays, the increasing number of moving objects tracking sensors, results in the continuous flow of high-frequency and high-volume data streams. This phenomenon can especially be observed in the maritime domain since most of the vessels worldwide are now transmitting their positions periodically. Therefore, there is a strong necessity to extract meaningful information and identify mobility patterns from such tracking data in an automated fashion, eliminating the need for experts' input. Furthermore, this increase of vessel tracking data has posed new challenges in the data mining community in terms of efficient analytics and knowledge extraction out of such data. The compulsory use of Automatic Identification System (AIS) -- a vessel tracking system -- for many vessel types, which has been enforced by naval regulations, has opened new opportunities for maritime surveillance. AIS transponders are rich sources of information that everyone can collect using an RF receiver and provide real-time information about vessels' positions. Properly taking advantage of AIS data, can uncover potential illegal behavior, offer real-time alerts and notify the authorities for any kind of anomalous vessel behavior. One major challenge in vessel tracking and surveillance is the ability to detect events of interest out of the voluminous and high-velocity streams of data in real-time. What is even more challenging is the deployment of applications on-site and on the terrestrial receivers that have a limited processing capacity. On top of that, the noisy and erroneous streams of vessel tracking data, makes the accurate detection of events of interest even more challenging. In this thesis, we aim to address the above challenges. Towards this direction, we propose a distributed architecture able to identify erroneous or noisy events in streams of vessel tracking data such as spoofing and the switch-off of the vessel tracking transponder in real-time. Moreover, we introduce an extension of an existing network abstraction of maritime traffic, that is based on nodes (called way-points) that correspond to naval areas of long stays or major turns for vessels (e.g. ports, capes, offshore platforms etc.) and edges (called traversals) that correspond to the routes followed by vessels between two consecutive way-points. The focus is the connections of the network abstraction and the enrichment with semantic information about the different ways that vessels employ when traversing an edge. For achieving this, sparse historic vessel tracking data and polynomial interpolation are employed in order to extract shipping lanes; an alternative of the popular density based clustering algorithm DBSCAN is proposed over a distributed architecture, which modifies the proximity parameter of the algorithm. The proposed alternative employs in tandem the difference in i) speed, ii) course and iii) position for defining the distance between two consecutive vessel positions (two consecutive AIS signals received from the same vessel). Furthermore, novel approaches are presented for the classification of vessel activity from real-time data streams. A solution is presented that splits vessel trajectories into multiple overlapping segments and distinguishes the ones in which a vessel is engaged in trawling or longlining operation (e.g. fishing activity) from other segments that a vessel is simply underway from its departure towards its destination. Moreover, a fusion of the research fields of computer vision and trajectory classification is introduced. The aim of this fusion is the delivery of a high-precision classification of mobility patterns through deep learning schemes in near real-time, tackling the Big Data challenges of volume and velocity. Finally, towards the solution of the same challenges a wide range of several well-known trajectory compression algorithms is presented and evaluated on data originating from vessel trajectories. Trajectory compression algorithms included in this research are suitable for either historical data (offline compression) or real-time data streams (online compression). The performance evaluation is three-fold and each algorithm is evaluated in terms of compression ratio, execution speed and information loss. We present our results and findings intended for both researchers and practitioners in the field of intelligent ship tracking and surveillance.Στην εποχή μας, ο αυξανόμενος αριθμός των αισθητήρων των κινητών αντικειμένων έχει ως αποτέ-λεσμα τη συνεχόμενη παραγωγή ροών δεδομένων υψηλής συχνότητας και μεγάλου όγκου. Αυτό το φαινόμενο παρατηρείται πολύ στον τομέα της ναυτιλίας όπου τα περισσότερα πλοία παγκοσμίως μεταδίδουν την τοποθεσία τους περιοδικά. Επομένως, υπάρχει μεγάλη ανάγκη για εξαγωγή χρήσιμης πληροφορίας και αναγνώριση μοτίβων κίνησης από αυτά τα δεδομένα με έναν αυτόματο τρόπο. Επιπλέον, η αύξηση αυτών των δεδομένων θέτει νέες προκλήσεις στην κοινότητα της εξαγωγής δεδομένων όσον αφορά την αποδοτική ανάλυση και εξαγωγή γνώσης. Η υποχρεωτική χρήση του αυτόματου συστήματος αναγνώρισης (Automatic Identification System - AIS) -- ένα σύστημα παρακολούθησης πλοίων -- σε πολλά πλοία, που έχει επιβληθεί από τους κανονισμούς ναυτιλίας, έχει ανοίξει νέες ευκαιρίες για τη ναυτιλιακή παρακολούθηση. Οι μεταδότες AIS είναι πλούσια πηγή πληροφοριών που ο καθένας μπορεί να συλλέξει με τη χρήση ενός δέκτη RF και παρέχουν πληροφορίες σε πραγματικό χρόνο για τις θέσεις των πλοίων. Η εκμετάλλευση δεδομένων AIS μπορεί να αποκαλύψει παράνομη συμπεριφορά, να προσφέρει ειδο-ποιήσεις σε πραγματικό χρόνο και να ενημερώσει τις αρχές για κάθε είδος παράξενης συμπεριφοράς. Μια μεγάλη πρόκληση στην παρακολούθηση πλοίων είναι η αναγνώριση γεγονότων ενδιαφέροντος μέσα από ογκώδεις και υψηλής συχνότητας ροές δεδομένων σε πραγματικό χρόνο. Ακόμη μεγαλύτε-ρη πρόκληση είναι η ανάπτυξη εφαρμογών στους επίγειους δέκτες που έχουν περιορισμένη ικανότη-τα επεξεργασίας. Επιπροσθέτως, οι γεμάτες λάθη και θόρυβο ροές δεδομένων παρακολούθησης πλοίων κάνει την ακριβή ανίχνευση γεγονότων ενδιαφέροντος ακόμη πιο δύσκολη. Σε αυτήν τη διατριβή προσπαθούμε να αντιμετωπίσου-με τις παραπάνω προκλήσεις. Συνεπώς, προτείνουμε μια κατανεμημένη αρχιτεκτονική ικανή να αναγνωρίζει γεγονότα μέσα από λανθασμένες και θορυβώδεις ροές δεδομένων παρακολούθησης πλοίων όπως το spoofing και το κλείσιμο των δεκτών μετάδοσης σε πραγματικό χρόνο. Επιπλέον, παρουσιάζουμε μια επέκταση ενός υπάρχοντος δικτύου ναυτιλιακής κίνησης που βασίζεται σε κόμβους που αντιστοιχούν σε ναυτικές περιοχές παρατεταμένης παραμονής πλοίων ή μεγάλων στροφών (παραδείγματος χάριν, λιμάνια, ακρωτήρια, πλατφόρμες) και ακμές που αντιστοιχούν σε διαδρομές πλοίων μεταξύ δύο διαδοχικών κόμβων. Η εστίαση του προβλήματος είναι στις συνδέσεις του δικτύου και στον εμπλουτισμό με σημασιολογική πληροφορία σχετικά με τον τρόπο διάσχισης μιας ακμής. Επομένως, αραιά ιστορικά δεδομένα παρακολούθησης πλοίων και πολυωνυμι-κή παρεμβολή χρησιμοποιούνται για την εξαγωγή διαδρομών πλοίων. Προτείνεται μια παραλλαγή του αλγορίθμου ομαδοποίησης DBSCAN πάνω από μια κατανεμημένη αρχιτεκτονική, όπου οι παράμετροι εγγύτητας του αλγορίθ-μου αλλάζουν. Η παραλλαγή του αλγορίθμου εκμεταλλεύεται τη διαφορά στην ταχύτητα, πορεία και θέση για να οριστεί η απόσταση μεταξύ δύο διαδοχικών θέσεων πλοίων. Επιπλέον, καινοτόμες προσεγγίσεις παρουσιάζονται για την κατηγοριοποίηση δραστηριότη-τας πλοίων από ροές δεδομένων σε πραγματικό χρόνο. Παρουσιάζεται μια λύση που τμηματοποι-εί τροχιές πλοίων σε πολλές μικρότερες τροχιές και ξεχωρίζει τα τμήματα στα οποία τα πλοία ψαρεύουν από άλλα τμήματα στα οποία τα πλοία απλά έχουν χαράξει πορεία προς τον προορισμό τους. Επίσης, παρουσιάζεται μια συγχώνευση των ερευνητικών τομέων του computer vision και της κατηγοριοποίησης τροχιών (trajectory classification). Ο στόχος αυτής της συγχώνευσης είναι να αυξήσει την ακρίβεια αναγνώρισης των μοτίβων κίνησης των πλοίων μέσα από τεχνικές deep learning σε πραγματικό χρόνο, υπερνικώντας τις προκλήσεις των μεγάλων δεδομένων όπως ο όγκος και η ταχύτητα. Τέλος, προς επίλυση των ίδιων προκλήσεων, διάφοροι αλγόριθμοι συμπίεσης τροχιών παρουσιάζονται και αξιολογούνται σε δεδομένα προερχόμενα από τροχιές πλοίων. Οι αλγόριθμοι συμπίεσης τροχιών που παρουσιάζονται σε αυτήν την έρευνα είναι κατάλληλοι είτε για ιστορικά δεδομένα είτε για δεδομένα πραγματικού χρόνου. Οι αλγόριθμοι αξιολογούνται ως προς το βαθμό συμπίεσης, την ταχύτητα εκτέλεσης και την απώλεια πληροφορίας. Παρουσιάζουμε τα ευρήματα αυτής της έρευνας που προορίζονται σε ερευνητές στον τομέα της έξυπνης παρακολούθη-σης πλοίων