Fabrication of heterogeneous biocatalyst tethering artificial prosthetic groups to obtain omega-3-fatty acids by selective hydrolysis of fish oils

The active site of lipase from Bacillus thermocathenolatus was selectively modified with allyl and naphthyl chains at different positions. Lipase immobilization and selective tethering of a naphthyl side chain to its position 320 improve both the hydrolysis rate of fish oils and the selectivity towards the eicosapentaenoic acid acyl chains. © The Royal Society of Chemistry 2016.

A new post-metallocene-ti catalyst with maltolate bidentade ligand: an investigation in heterogeneous polymerization reactions in different mesoporous supports

A new titanium catalyst easily synthesized from ethylmaltol bidentate chelator ligand was studied in homogeneous and heterogeneous ethylene polymerization. The dichlorobis(3-hydroxy-2-ethyl-4-pyrone)titanium(IV) complex was characterized by 1H and 13C NMR (nuclear magnetic resonance), UV-Vis and elemental analysis. Theoretical study by density functional theory (DFT) showed that the complex chlorines exhibit cis configuration, which is important for the activity in olefin polymerization. The complex was supported by two methods, direct impregnation or methylaluminoxane (MAO) pre-treatment, in five mesoporous supports: MCM-41 (micro and nano), SBA-15 and also the corresponding modified Al species. All the catalytic systems were active in ethylene polymerization and the catalytic activity was strongly influenced by the method of immobilization of the catalyst and the type of support.

Heterogeneous Catalysts: Design, Applications and Research Insights

The cyclization of pseudoionone yields a mixture of alpha-ionone, beta-ionone and gamma-ionone. By careful control of reagent and reaction conditions, either the alpha- and beta- isomer can be favoured. The alpha-ionone has violet odour and is widely used in perfumery and flavours. beta-Ionone is the main precursor of Vitamin A and beta-carotene. Traditionally, strong homogeneous catalysts, like sulphuric acid and phosphoric acid have been used. These problems can be overcome by the use of solid acid catalysts. This work reports the cyclization of pseudoionone over USY zeolites, at 80ºC. USY It is observed that the initial activity increases with the Si/Al ratio of zeolite until a maximum, which is obtained with USY3. With higher Si/Al ratio, a decrease in the catalytic activity is observed. Selectivity to ionone isomers is around 42 %, at 75% of pseudoionone conversion, after 24 h of reaction. USY3 zeolite was reused four times with the same catalyst sample in the same condicions. It was observed a stabilization of the catalytic activity, after the second use.

Composites Chitosan/SBA-15 with sulfonic acid as heterogeneous catalysts for biodiesel production

Free fatty acids (palmitic, stearic and oleic acid) were converted into biodiesel with methanol over composites catalysts consisting in SBA-15 with sulfonic acid groups (SBA-15-SO3H) immobilized in Chitosan (CH), at 60ºC. It was observed that the catalytic activity increased with the amount of SBA-15-SO3H dispersed in CH. It was also observed that the catalytic activity decreased in the series: palmitic acid > stearic acid > oleic. The catalytic stability of [SBA-15-SO3H]3/CH composites was studied. A good stability was observed.

Generalities of vertebrate responses to landscape composition and configuration gradients in a highly heterogeneous Mediterranean region

Aim To examine the distributional patterns of vertebrates (including birds, bats, carnivores and lagomorphs) along landscape composition and configuration gradients to better understand the effects of landscape modification on occurrence patterns at both species and community level. Location The region of Alentejo, a forest-dominated area of southern Portugal. Methods The study area was framed using 1647 hexagonal plots, each of 259 ha in size. Composition and configuration gradients were obtained for each plot by integrating the proportions of the main land cover types and their configuration patterns using multivariate analyses. Species-specific vertebrate responses were investigated using data from 75 plots in which carnivores, bats and lagomorphs were sampled, and from 135 plots in the case of birds. Community- level responses were investigated through changes in species richness and beta-diversity in 57 plots where all vertebrate groups were simultaneously sampled. At the species-level, an information-theoretic approach was used to determine the effects of landscape gradients on species’ responses. At the community level, Mantel tests were used to determine between-plot differences in species composition using the Sørensen dissimilarity index. Results We found that the occurrence patterns of most vertebrate species were best predicted by composition-related gradients, although configuration gradients were also frequently included in species-specific occurrence models. We also found a weak correlation between species richness and most landscape gradients suggesting a turnover in the identity of species, something that was corroborated by the stronger correlation between environmental gradients and beta-diversity measures. The amount of forest cover and landscape complexity (estimated as the heterogeneity in the size and number of land cover types) were the main composition and configuration gradients determining vertebrate responses at both species and community level. Main conclusions Our work contributes to a more refined understanding of the mechanisms underlying species distributional patterns in real-world human-modified landscapes. By uncovering generalities of species with multiple ecological requirements and by describing the entire landscape mosaic through landscape gradients, we also suggest that our work greatly helps to fill the gap between existing conceptual landscape models aimed to understand species distributional patterns in human-modified landscapes.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Serverless middlewares to integrate heterogeneous and distributed services in cloud continuum environments

The application of modern ICT technologies is radically changing many fields pushing toward more open and dynamic value chains fostering the cooperation and integration of many connected partners, sensors, and devices. As a valuable example, the emerging Smart Tourism field derived from the application of ICT to Tourism so to create richer and more integrated experiences, making them more accessible and sustainable. From a technological viewpoint, a recurring challenge in these decentralized environments is the integration of heterogeneous services and data spanning multiple administrative domains, each possibly applying different security/privacy policies, device and process control mechanisms, service access, and provisioning schemes, etc. The distribution and heterogeneity of those sources exacerbate the complexity in the development of integrating solutions with consequent high effort and costs for partners seeking them. Taking a step towards addressing these issues, we propose APERTO, a decentralized and distributed architecture that aims at facilitating the blending of data and services. At its core, APERTO relies on APERTO FaaS, a Serverless platform allowing fast prototyping of the business logic, lowering the barrier of entry and development costs to newcomers, (zero) fine-grained scaling of resources servicing end-users, and reduced management overhead. APERTO FaaS infrastructure is based on asynchronous and transparent communications between the components of the architecture, allowing the development of optimized solutions that exploit the peculiarities of distributed and heterogeneous environments. In particular, APERTO addresses the provisioning of scalable and cost-efficient mechanisms targeting: i) function composition allowing the definition of complex workloads from simple, ready-to-use functions, enabling smarter management of complex tasks and improved multiplexing capabilities; ii) the creation of end-to-end differentiated QoS slices minimizing interfaces among application/service running on a shared infrastructure; i) an abstraction providing uniform and optimized access to heterogeneous data sources, iv) a decentralized approach for the verification of access rights to resources.

Protein-based nanomaterials as protein heterogeneous nucleants and structural studies on enzymes from two photosynthetic organisms

Proteins, the most essential biological macromolecules, are involved in nearly every aspect of life. The elucidation of their three-dimensional structures through X-ray analysis has significantly contributed to our understanding of fundamental mechanisms in life processes. However, the obstacle of obtaining high-resolution protein crystals remains significant. Thus, searching for materials that can effectively induce nucleation of crystals is a promising and active field. This thesis work characterizes and prepares albumin nanoparticles as heterogeneous nucleants for protein crystallization. These stable Bovine Serum Albumin nanoparticles were synthesized via the desolvation method, purified efficiently, and characterized in terms of dimension, morphology, and secondary structure. The ability of BSA-NPs to induce macromolecule nucleation was tested on three model proteins, exhibiting significant results, with larger NPs inducing more nucleation. The second part of this work focuses on the structural study, mainly through X-ray crystallography, of five chloroplast and cytosolic enzymes involved in the fundamental cellular processes of two photosynthetic organisms, Chlamydomonas reinhardtii and Arabidopsis thaliana. The structures of three enzymes involved in the Calvin-Benson-Bassham Cycle, phosphoribulokinase, troseposphatisomerase, and ribulosiophosphate epimerase from Chlamydomonas reinhardtii, were solved to investigate their catalytic and regulatory mechanisms. Additionally, the structure of nitrosylated-CrTPI made it possible to identify Cys14 as a target for nitrosylation, and the crystallographic structure of CrRPE was solved for the first time, providing insights into its catalytic and regulatory properties. Finally, the structure of S-nitrosoglutathione reductase, AtGSNOR, was compared with that of AtADH1, revealing differences in their catalytic sites. Overall, seven crystallographic structures, including partially oxidized CrPRK, CrPRK/ATP, CrPRK/ADP/Ru5P, CrTPI-nitrosylated, apo-CrRPE, apo-AtGSNOR, and AtADH1-NADH, were solved and are yet to be deposited in the PDB.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

Investigation on the role of polymeric ligands in heterogeneous nanocatalysis towards the development of hybrid metal-polymer catalysts

The relationship between catalytic properties and the nature of the active phase is well-established, with increased presence typically leading to enhanced catalysis. However, the costs associated with acquiring and processing these metals can become economically and environmentally unsustainable for global industries. Thus, there is potential for a paradigm shift towards utilizing polymeric ligands or other polymeric systems to modulate and enhance catalytic performance. This alternative approach has the potential to reduce the requisite amount of active phase while preserving effective catalytic activity. Such a strategy could yield substantial benefits from both economic and environmental perspectives. The primary objective of this research is to examine the influence of polymeric hydro-soluble ligands on the final properties, such as size and dispersion of the active phase, as well as the catalytic activity, encompassing conversion, selectivity towards desired products, and stability, of colloidal gold nanoparticles supported on active carbon. The goal is to elucidate the impact of polymers systematically, offering a toolbox for fine-tuning catalytic performances from the initial stages of catalyst design. Moreover, investigating the potential to augment conversion and selectivity in specific reactions through tailored polymeric ligands holds promise for reshaping catalyst preparation methodologies, thereby fostering the development of more economically sustainable materials.

Development of a heterogeneous clustering algorithm for particle shower reconstruction in high energy physics using the SYCL abstraction layer

Nei prossimi anni è atteso un aggiornamento sostanziale di LHC, che prevede di aumentare la luminosità integrata di un fattore 10 rispetto a quella attuale. Tale parametro è proporzionale al numero di collisioni per unità di tempo. Per questo, le risorse computazionali necessarie a tutti i livelli della ricostruzione cresceranno notevolmente. Dunque, la collaborazione CMS ha cominciato già da alcuni anni ad esplorare le possibilità offerte dal calcolo eterogeneo, ovvero la pratica di distribuire la computazione tra CPU e altri acceleratori dedicati, come ad esempio schede grafiche (GPU). Una delle difficoltà di questo approccio è la necessità di scrivere, validare e mantenere codice diverso per ogni dispositivo su cui dovrà essere eseguito. Questa tesi presenta la possibilità di usare SYCL per tradurre codice per la ricostruzione di eventi in modo che sia eseguibile ed efficiente su diversi dispositivi senza modifiche sostanziali. SYCL è un livello di astrazione per il calcolo eterogeneo, che rispetta lo standard ISO C++. Questo studio si concentra sul porting di un algoritmo di clustering dei depositi di energia calorimetrici, CLUE, usando oneAPI, l'implementazione SYCL supportata da Intel. Inizialmente, è stato tradotto l'algoritmo nella sua versione standalone, principalmente per prendere familiarità con SYCL e per la comodità di confronto delle performance con le versioni già esistenti. In questo caso, le prestazioni sono molto simili a quelle di codice CUDA nativo, a parità di hardware. Per validare la fisica, l'algoritmo è stato integrato all'interno di una versione ridotta del framework usato da CMS per la ricostruzione. I risultati fisici sono identici alle altre implementazioni mentre, dal punto di vista delle prestazioni computazionali, in alcuni casi, SYCL produce codice più veloce di altri livelli di astrazione adottati da CMS, presentandosi dunque come una possibilità interessante per il futuro del calcolo eterogeneo nella fisica delle alte energie.

Direct C–H silylation and borylation of biomass derivatives by iridium heterogeneous catalysts

Furfural and its derivatives represent renewable and readily available platforms for a wide range of chemicals. Much attention has been devoted to their functionalization over the last years. TM-catalysed C–H activation has emerged as a powerful tool for synthesizing new C–C and C–X bonds. Moreover, it provides a sustainable way to obtain molecules by reducing waste and saving steps. At the same time, iridium catalysts have proven to be very active in some C–H functionalizations of several (hetero)arenes. Although very promising, this technique is still poorly applied on an industrial scale due to the severe conditions required. Continuous flow chemistry using heterogeneous catalysts appears to be a valuable way to overcome these problems. In this work, we present different solutions for the immobilization of homogeneous iridium complexes on silica gels, using bidentate amines and phosphines as anchoring ligands. We successfully employed the catalysts in C–H silylation and borylation of furfural, using C2 located directing group. In this way, we finally obtained a suitable catalyst that could be potentially applied in continuous-flow chemistry.

Niobium-based heterogeneous catalysts synthesised in supercritical carbon dioxide for selective olefin epoxidation

In this work, two different protocols for the synthesis of Nb2O5-SiO2 with a sol-gel route in which supercritical carbon dioxide was used as solvent have been developed. The tailored design of the reactor allowed the reactants to come into contact only when supercritical CO2 is present, and the high-throughput experimentation scCO2 unit allowed the screening of synthetic parameters, that led to a Nb2O5 incorporation into the silica matrix of 2.5 wt%. N2-physisorption revealed high surface areas and the presence of meso- and micropores. XRD allowed to demonstrate the amorphous character of these materials. SEM-EDX proved the excellent dispersion of Nb2O5 into the silica matrix. These materials were tested in the epoxidation of cyclooctene with hydrogen peroxide, which is considered an environmentally friendly oxidant. The catalysts were virtually inactive in an organic, polar, aprotic solvent (1,4-dioxane). However, the most active scCO2 Nb2O5-SiO2 catalyst achieved a cyclooctene conversion of 44% with a selectivity of 88% towards the epoxide when tested in ethanol. Catalytic tests on cyclohexene revealed the presence of the epoxide, which is remarkable, considering that this substrate is easily oxidised to the diol. The behaviour in protic and aprotic solvents is compared to that of TS-1.

Sviluppo di Algoritmi di Localizzazione 3D Passiva per UAVs

Gli UAV, o meglio conosciuti come ‘droni’, sono aeromobili a pilotaggio remoto il cui utilizzo si estende dal settore militare a quello civile. Quest’ultimi, possono essere attrezzati con numerosi dispositivi accessori, come ad esempio disturbatori di frequenze. La simbiosi UAV-jammer attacca le comunicazioni wireless tramite interferenze a radiofrequenza, per degradare o interrompere il servizio offerto dalle reti. Questo elaborato, si concentra sull’analisi di algoritmi di localizzazione passiva, per stimare la posizione dell’UAV e interrompere l’interferenza. Inizialmente, viene descritto il segnale emesso dall’UAV, che utilizza lo standard di comunicazione 802.11a. A seguire, dato che la localizzazione passiva si basa sulle misure TDOA rilevate da una stazione di monitoraggio a terra, vengono presentati tre algoritmi di stima TDOA, tra i quali fast TDOA, adaptive threshold-based first tap detection e un algoritmo sviluppato per i nuovi sistemi GNSS. Successivamente, vengono esaminati tre algoritmi di localizzazione passiva, che sfruttano il principio dei minimi quadrati (LS), ovvero il CTLS, LCLS e CWLS. Infine, le prestazioni degli algoritmi di localizzazione vengono valutate in un ambiente di simulazione realistico, con canale AWGN o con canale ITU Extended pedestrian A.

Basilar Invagination: Surgical Results.

Basilar invagination (BI) is a congenital craniocervical junction (CCJ) anomaly represented by a prolapsed spine into the skull-base that can result in severe neurological impairment. In this paper, we retrospective evaluate the surgical treatment of 26 patients surgically treated for symptomatic BI. BI was classified according to instability and neural abnormalities findings. Clinical outcome was evaluated using the Nürick grade system. A total of 26 patients were included in this paper. Their age ranged from 15 to 67 years old (mean 38). Of which, 10 patients were male (38%) and 16 (62%) were female. All patients had some degree of tonsillar herniation, with 25 patients treated with foramen magnum decompression. Nine patients required a craniocervical fixation. Six patients had undergone prior surgery and required a new surgical procedure for progression of neurological symptoms associated with new compression or instability. Most of patients with neurological symptoms secondary to brainstem compression had some improvement during the follow-up. There was mortality in this series, 1 month after surgery, associated with a late removal of the tracheal cannula. Management of BI requires can provide improvements in neurological outcomes, but requires analysis of the neural and bony anatomy of the CCJ, as well as occult instability. The complexity and heterogeneous presentation requires attention to occult instability on examination and attention to airway problems secondary to concomitant facial malformations.