Characterization of starch fractions from maize endosperm mutants

For starch to be useful in food systems and other industrial applications, one should understand the functional properties of starch (gelatinization, pasting, and retrogradation). Starch functionality depends on the molecular structure, size, and weight of its components. The objectives of this study were to (a) characterize the thermal and functional properties of the starch from a wild-type (normal) starch and amylose extender25, dull39, sugary2, and sugary1 maize mutants with the same genetic background, and (b) isolate, determine and compare the fine structures of starch fractions obtained from these starch types by using different isolation methods. The separations were performed by fractionation on a GPC column, by precipitation with 1-butanol, and by preferential precipitation with 1-butanol and isoamyl alcohol. All methods revealed that a clear separation among the starch molecules is not possible since there are no strict limits for the fractionation. All medium-molecular-weight (MMW) fractions had an increased amount of shorter chains, decreased number of longer chains, and a lower detectable DP than that observed for the larger-molecular-weight (LMW) fractions. From the HPSEC analysis there was a considerable amount of longer chains in MMW fractions whose detection was limited by the use of HPAEC-ENZ-PAD. The 1-butanol method was not successful in quantitatively isolating starch fractions because of the relatively low recovery of the total starch, whereas, the method based on preferential precipitation with 1-butanol and isoamyl alcohol had an increased recovery of total starch (81.1 to 88.2 %). Isoamyl alcohol preferably formed a complex with structures having a greater proportion of shorter chains. The profiles of MMW and soluble fractions provided by the different methods combined high proportions of shorter chains and the presence of longer chains beyond the range of the corresponding LMW or soluble fractions. Correlation analyses indicated that amylose content and branch-chain-length profiles of the starch molecules play an important role in the functional properties of the whole starch. The significant contributions of the shorter chains to the thermal properties and those of the longer chains to the pasting properties of starch suggest the importance of knowing the structural features needed for specific applications

Enhancing optimization algorithms for non-convex settings : federated and decentralized learning

In the last decade, the rise and unprecedented success of neural networks have drawn significant attention from the machine learning community to non-convex optimization. This thesis focuses on federated and decentralized learning within the framework of non-convex optimization, aiming to deepen the understanding of the field and derive novel results. Specifically, the first part of this work addresses two major challenges encountered in the context of Federated Learning: (i) data heterogeneity, where data distribution can vary substantially across clients, and (ii) system heterogeneity, where the computational power of clients can differ significantly. To tackle these challenges, we propose and analyze federated meta-algorithms that leverage ideas from the realm of representation learning. These algorithms incorporate the statistical characteristics of clients' data to adaptively select the clients, thereby speeding up the learning process. Our methods exhibit robust performance in the presence of stragglers, outperforming well-established baselines for both convex and non-convex loss functions. The ability to handle the complexities of federated environments with varying participation structures and resource constraints underscores their practical relevance and potential for real-world deployment. In the second part of this thesis, we delve into Fully Decentralized Learning. We explore the limitations of prior literature and strive to design a novel method that converges to a second-order stationary point in non-convex smooth settings. Our approach involves coupling the gradient tracking scheme with perturbation techniques inspired from the centralized regime. This novel combination allows us to provide, for the first time, polynomial convergence rate guarantees with respect to the last iterate. Our experimental validation demonstrates that our proposed method efficiently escapes saddle points, achieving superior performance compared to existing decentralized algorithms.Electrical and Computer Engineerin

Online Shortest Path with Switching Cost

Ένα χαρακτηριστικό on-line πρόβλημα διεξάγεται σε γύρους, όπου σε κάθε γύρο ένας on-line αλγόριθμος δέχεται ένα αίτημα και οφείλει να το ικανοποιήσει. Θα επικεντρωθούμε σε μία συγκεκριμένη οικογένεια on-line προβλημάτων γνωστά ως Smooth On-line Convex Optimization (SOCO) προβήματα. Δύο γνωστά επιστημονικά πεδία που μελετούν τέτοια προβλήματα είναι το πεδίο competitive analysis και το πεδίο on-line learning. Θα εμβαθύνουμε στη σχέση των δύο πεδίων και θα εξηγήσουμε πως μπορούμε να επωφεληθούμε εισάγωντας την τεχνική regularization από το πεδίο του on-line learning στο competitive analysis. Στη συνέχεια θα εστιάσουμε σε μία τεχνική rounding η οποία εμφανίστηκε στη βιβλιογραφία τα τελευταία χρόνια και ονομάζεται exponential clocks. Τέλος, θα ορίσουμε ένα νέο πρόβλημα της οικογένειας SOCO, το On-line Shortest Paths with Switching Cost. Χρησιμοποιώντας εργαλεία από τη βιβλιογραφία θα πάρουμε μία on-line fractional λύση του προβλήματος θυσιάζοντας ένα λογαριθμικό παράγοντα. Θα ολοκληρώσουμε παρουσιάζοντας ένα νέο rounding αλγόριθμο χρησιμοποιώντας exponential clocks, ο οποίος θα επιτύχει μια O(logmlog n)- προσέγγιστική λύση για το πρόβλημα On-line Shortest Path with Switching Cost.A typical on-line problem proceeds in rounds, where in each round an on-line algorithm is given a request and needs to serve it. We will focus on a specific class of on-line problems known as Smooth On-line Convex Optimization (SOCO) problems. Two mature research fields that study such problems are competitive analysis and on-line learning. We will dive into their interrelationship and we will explain how we can benefit by introducing regularization, a standard technique from on-line learning in the framework of competitive analysis. Subsequently, we will turn our attention towards a rounding technique introduced over the last couple of years, called exponential clocks. Finally, we will define a new problem in the class SOCO, namely On-line Shortest Path with Switching Cost. Using the toolbox provided by the literature we will obtain an on-line fractional solution sacrificing a logarithmic factor. We will wrap up presenting a new on-line rounding algorithm using exponential clocks which will derive a O(logmlog n)-approximation for the On-line Shortest Path with Switching Cost problem

6G: Η επόμενη γενιά ασύρματων επικοινωνιών

Οι δραστηριότητες τυποποίησης των επικοινωνιών πέμπτης γενιάς έχουν σαφώς ολοκληρωθεί και η εφαρμογή του στην αγορά έχει ξεκινήσει παγκοσμίως. Για να διατηρηθεί το ανταγωνιστικό πλεονέκτημα των ασύρματων δικτύων, η βιομηχανική και η ακαδημαϊκή κοινότητα έχουν αρχίσει να μελετούν την επόμενη γενιά συστημάτων ασύρματης επικοινωνίας (δηλαδή, την έκτη γενιά, (6G)) με στόχο να θέσουν τα θεμέλια για τη διαστρωμάτωση των επικοινωνιακών αναγκών της δεκαετίας του 2030. Προς την υποστήριξη αυτού του οράματος, αυτή η εργασία αναδεικνύει τις πιο υποσχόμενες γραμμές έρευνας από την πρόσφατη βιβλιογραφία σε κοινές κατευθύνσεις για το έργο 6G. Η εργασία διερευνά κρίσιμα ζητήματα και βασικά πιθανά χαρακτηριστικά των επικοινωνιών 6G, όπως: (i) όραμα και βασικά χαρακτηριστικά, (ii) προκλήσεις και πιθανές λύσεις. και (iii) μελλοντικές ερευνητικές δραστηριότητες. Πιο συγκεκριμένα η εργασία χωρίζεται σε 5 βασικά κεφάλαια: Στο πρώτο κεφάλαιο γίνεται μια σύντομη ανασκόπηση στα προηγούμενα δίκτυα 1G-4G, εστιάζοντας στο τρέχον υπό ανάπτυξη ακόμα δίκτυο 5G και στην μετάβασή του που θα οδηγήσει στο 6G. Στο δεύτερο κεφάλαιο γίνεται μια εκτενής αναφορά στις τεχνολογίες που θα χρησιμοποιήσει το 6G και βασικά χαρακτηριστικά που θα πρέπει να πληροί, όπως δυναμικές απαιτήσεις για μικρές καθυστερήσεις, μεγάλο φάσμα και μηδενική σχεδόν ανοχή σε τρωτά σημεία στην ασφάλεια. Στο κεφάλαιο 3, με βάση εκτενή διεθνή βιβλιογραφία, αναζητούνται πιθανά προβλήματα που οι απαιτήσεις του θα επιφέρουν και λύσεις σε αυτές, στον τομέα της ασφάλειας, της υγείας, της πολυπλοκότητας και της εξοικονόμησης πόρων και ενέργειας. Στο κεφάλαιο 4, μελετώνται μελλοντικές εφαρμογές του 6G, όπως: στη διαχείριση δικτύου, στην αυτονομία των δικτύων, στην υγεία, στις κατασκευές, στο έξυπνο σπίτι, στο σύστημα μεταφορών, στα έ ξυπνα δίκτυα, στα μη επανδρωμένα οχήματα, στις επικοινωνίες όχημα προς πάντα (Vehicle to Everything), κλπ. Τέλος, στο κεφάλαιο 5, γίνεται μια σύνοψη της μελέτης, προβληματιζόμενοι από σημαντικά θέματα που θα πρέπει να επιλυθούν μέχρι την εφαρμογή του 6G.Fifth generation communications standardization activities have clearly been completed and its market implementation has begun worldwide. To maintain the competitive advantage of wireless networks, industrial and academic communities have begun to study the next generation of wireless communication systems (the sixth generation, (6G)) with the aim of laying the foundation for layering the communication needs of 2030s. In support of this vision, this project highlights the most promising lines of research from the recent literature on common directions for the 6G project. The paper explores critical issues and key potential features of 6G communications, such as: (i) vision and key features, (ii) challenges and potential solutions. and (iii) future research activities. More specifically, the work is divided into 5 main chapters: In the first chapter, a brief review of the previous 1G-4G networks is given, focusing on the current still under development 5G network and its transition leading to 6G. In the second chapter there is an extensive reference to the technologies that 6G will use and key features that it will have to meet, such as dynamic requirements for low delays, large spectrum and almost zero tolerance for security vulnerabilities. In chapter 3, based on extensive international literature, potential problems that its requirements will bring and solutions to them are sought, in the field of safety, health, complexity and resource and energy saving. In chapter 4, future applications of 6G are studied, such as: in network management, network autonomy, health, construction, smart home, transportation system, smart networks, unmanned vehicles, vehicle-to-everything communications, etc. Finally, in chapter 5, a summary of the study is made, concerned with important issues that should be resolved until the implementation of 6G

Molecular transformation and degradation of refractory dissolved organic matter in the Atlantic and Southern Ocean

More than 90% of the global ocean dissolved organic carbon (DOC) is refractory, has an average age of 4,000–6,000 years and a lifespan from months to millennia. The fraction of dissolved organic matter (DOM) that is resistant to degradation is a long-term buffer in the global carbon cycle but its chemical composition, structure, and biochemical formation and degradation mechanisms are still unresolved. We have compiled the most comprehensive molecular data set of 197 Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analyses from solid-phase extracted marine DOM covering two major oceans, the Atlantic sector of the Southern Ocean and the East Atlantic Ocean (ranging from 50° N to 70° S). Molecular trends and radiocarbon dating of 34 DOM samples (comprising Δ14C values from -229 to -495‰) were combined to model an integrated degradation rate for bulk DOC resulting in a predicted age of >24 ka for the most persistent DOM fraction. First order kinetic degradation rates for 1,557 mass peaks indicate that numerous DOM molecules cycle on timescales much longer than the turnover of the bulk DOC pool (estimated residence times of >100 ka) and the range of validity of radiocarbon dating. Changes in elemental composition were determined by assigning molecular formulae to the detected mass peaks. The combination of residence times with molecular information enabled modelling of the average elemental composition of the slowest degrading fraction of the DOM pool. In our dataset, a group of 361 molecular formulae represented the most stable composition in the oceanic environment (“island of stability”). These most persistent compounds encompass only a narrow range of the elemental ratios H/C (average of 1.17 ± 0.13), and O/C (average of 0.52 ± 0.10) and molecular masses (360 ± 28 and 497 ± 51 Da). In the Weddell Sea DOC concentrations in the surface waters were low (46.3 ± 3.3 μM) while the organic radiocarbon was significantly more depleted than that of the East Atlantic, indicating average surface water DOM ages of 4,920 ± 180 a. These results are in accordance with a highly degraded DOM in the Weddell Sea surface water as also shown by the molecular degradation index IDEG obtained from FT-ICR MS data. Further, we identified 339 molecular formulae which probably contribute to an increased DOC concentration in the Southern Ocean and potentially reflect an accumulation or enhanced sequestration of refractory DOC in the Weddell Sea. These results will contribute to a better understanding of the persistent nature of marine DOM and its role as an oceanic carbon buffer in a changing climate

Dissolved organic matter in sea spray: a transfer study from marine surface water to aerosols

Atmospheric aerosols impose direct and indirect effects on the climate system, for example, by absorption of radiation in relation to cloud droplets size, on chemical and organic composition and cloud dynamics. The first step in the formation of Organic primary aerosols, i.e. the transfer of dissolved organic matter from the marine surface into the atmosphere, was studied. We present a molecular level description of this phenomenon using the high resolution analytical tools of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and nuclear magnetic resonance spectroscopy (NMR). Our experiments confirm the chemoselective transfer of natural organic molecules, especially of aliphatic compounds from the surface water into the atmosphere via bubble bursting processes. Transfer from marine surface water to the atmosphere involves a chemical gradient governed by the physicochemical properties of the involved molecules when comparing elemental compositions and differentiating CHO, CHNO, CHOS and CHNOS bearing compounds. Typical chemical fingerprints of compounds enriched in the aerosol phase were CHO and CHOS molecular series, smaller molecules of higher aliphaticity and lower oxygen content, and typical surfactants. A non-targeted metabolomics analysis demonstrated that many of these molecules corresponded to homologous series of oxo-, hydroxy-, methoxy-, branched fatty acids and mono-, di- and tricarboxylic acids as well as monoterpenes and sugars. These surface active biomolecules were preferentially transferred from surface water into the atmosphere via bubble bursting processes to form a significant fraction of primary organic aerosols. This way of sea spray production leaves a selective biological signature of the surface water in the corresponding aerosol that may be transported into higher altitudes up to the lower atmosphere, thus contributing to the formation of secondary organic aerosol on a global scale or transported laterally with possible deposition in the context of global biogeocycling

Machine Learning und Netzwerkanalyse mittels mathematischer Optimierung in massenspektrometrischer Bioinformatik

In this work we develop and present a set of novel computational techniques which address the problems of ICR-FT-MS data mining. The described methodology focuses mainly on two scopes of biogeochemical research, namely the analysis of natural organic matter (NOM) and metabolomics. The development of our approaches focuses on the fields of graph theory, machine learning, and combinatorics. Detailed results of our methods are produced, presented, and evaluated within their corresponding sections.In dieser Arbeit wird ein Set neuer rechnerischer Techniken, welches ICR-FT-MS data mining Probleme adressiert, erarbeitet. Die beschriebenen Methoden konzentrieren sich auf die Analyse natürlicher organischer Materie (NOM) und Metabolomik. Die Entwickelten Ansätze fussen in den Disziplinen der Graphentheorie, Machine Learning und Kombinatorik. Resultate werden in den einzelnen Sektionen detailliert erarbeitet, präsentiert und evaluiert

Machine learning and network analysis using mathematical optimisation in mass spectrometry bioinformatics.

In this work we develop and present a set of novel computational techniques which address the problems of ICR-FT-MS data mining. The described methodology focuses mainly on two scopes of biogeochemical research, namely the analysis of natural organic matter (NOM) and metabolomics. The development of our approaches focuses on the fields of graph theory, machine learning, and combinatorics. Detailed results of our methods are produced, presented, and evaluated within their corresponding sections