Sintered Sewage Sludge As Support Material Used In Drinking Water Filtration

The processing of industry and domestic effluents in wastewater treatment plants reduces the amount of polluted material and forms reusable water and dehydrated sludge. the generation of hazardous municipal sludge can be decreased, as well as the impact on surface and underground water and the risk to human health. The aim this study is to verify the possibility to use sintered sewage sludge as support material after thermal treatment in the production of a filtering material to water supply systems. After thermal treatment the sewage sludge ash was characterized by X-ray fluorescence (XRF), leaching test and water solubilization. Dehydration of sludge was performed by controlled heating at temperatures of 180 degrees C, 350 degrees C, 600 degrees C, 850 degrees C and 1000 degrees C for 3 hours.

Designing Hydrogels that Transform their Shape in Response to Molecular Cues

There has been considerable interest in developing shape-changing soft materials for potential applications in drug delivery, microfluidics and biosensing. These shape- changing materials are inspired by the morphological changes exhibited by plants in nature, such as the Venus flytrap. One specific class of shape-change is that from a flat sheet to a folded structure (e.g., a tube). Such “self-folding” materials are usually composed of polymer hydrogels, and these typically fold in response to external stimuli such as pH and temperature. In order to develop these hydrogels for the previously described applications, it is necessary to expand the range of triggers. The focus of this dissertation is the advancement of shape-changing polymer hydrogels that are sensitive to uncommon cues such as specific biomolecules (enzymes), the substrates for such enzymes, or specific multivalent cations. First, we describe a hybrid gel that responds to the presence of low concentrations of a class of enzymes known as matrix metalloproteinases (MMPs). The hybrid gel was created by utilizing photolithographic techniques to combine two or more gels with distinct chemical composition into the same material. Certain portions of the hybrid gel are composed of a biopolymer derivative with crosslinkable groups. The hybrid gel is flat in water; however, in the presence of MMPs, the regions containing the biopolymer are degraded and the flat sheet folds to form a 3D structure. We demonstrate that hydrogels with different patterns can transform into different 3D structures such as tubes, helices and pancakes. Furthermore, this shape change can be made to occur at physiological concentrations of enzymes. Next, we report a gel with two layers that undergoes a shape change in the presence of glucose. The enzyme glucose oxidase (GOx) is immobilized in one of the layers. GOx catalyzes the conversion of glucose to gluconic acid. The production of gluconic acid decreases the local pH. The decrease in local pH causes one of the layers to swell. As a result, the flat sheet folds to form a tube. The tube unfolds to form a flat sheet when it is transferred to a solution with no glucose present. Therefore, this biomolecule- triggered shape transformation is reversible, meaning the glucose sensing gel is reusable. Furthermore, this shape change only occurs in the presence of glucose and it does not occur in the presence of other small sugars such as fructose. In our final study, we report the shape change of a gel with two layers in the presence of multivalent ions such as Ca2+ and Sr2+. The gel consists of a passive layer and an active layer. The passive layer is composed of dimethylyacrylamide (DMAA), which does not interact with multivalent ions. The active layer consists of DMAA and the biopolymer alginate. In the presence of Ca2+ ions, the alginate chains crosslink and the active layer shrinks. As a result, the gel converts from a flat sheet to a folded tube. What is particularly unusual is the direction of folding. In most cases, when flat rectangular gels fold, they do so about their short-side. However, our gels typically fold about their long-side. We hypothesize that non-homogeneous swelling determines the folding axis.

Microfabricated elastomer tactile sensors for robotic fingertip systems

Tactile sensing is an important aspect of robotic systems, and enables safe, dexterous robot-environment interaction. The design and implementation of tactile sensors on robots has been a topic of research over the past 30 years, and current challenges include mechanically flexible “sensing skins”, high dynamic range (DR) sensing (i.e.: high force range and fine force resolution), multi-axis sensing, and integration between the sensors and robot. This dissertation focuses on addressing some of these challenges through a novel manufacturing process that incorporates conductive and dielectric elastomers in a reusable, multilength-scale mold, and new sensor designs for multi-axis sensing that improve force range without sacrificing resolution. A single taxel was integrated into a 1 degree of freedom robotic gripper for closed-loop slip detection. Manufacturing involved casting a composite silicone rubber, polydimethylsiloxane (PDMS) filled with conductive particles such as carbon nanotubes, into a mold to produce microscale flexible features on the order of 10s of microns. Molds were produced via microfabrication of silicon wafers, but were limited in sensing area and were costly. An improved technique was developed that produced molds of acrylic using a computer numerical controlled (CNC) milling machine. This maintained the ability to produce microscale features, and increased the sensing area while reducing costs. New sensing skins had features as small as 20 microns over an area as large as a human hand. Sensor architectures capable of sensing both shear and normal force sensing with high dynamic range were produced. Using this architecture, two sensing modalities were developed: a capacitive approach and a contact resistive approach. The capacitive approach demonstrated better dynamic range, while the contact resistive approach used simpler circuitry. Using the contact resistive approach, normal force range and resolution were 8,000 mN and 1,000 mN, respectively, and shear force range and resolution were 450 mN and 100 mN, respectively. Using the capacitive approach, normal force range and resolution were 10,000 mN and 100 mN, respectively, and shear force range and resolution were 1,500 mN and 50 mN, respectively.

Multivalent reuse of web data about temporary art exhibitions: The Exhibitium Project

Our proposal aims to display the analysis techniques, methodologies as well as the most relevant results expected within the Exhibitium project framework (http://www.exhibitium.com). Awarded by the BBVA Foundation, the Exhibitium project is being developed by an international consortium of several research groups . Its main purpose is to build a comprehensive and structured data repository about temporary art exhibitions, captured from the web, to make them useful and reusable in various domains through open and interoperable data systems.

A novel CE microchip with micro pillars column & double-L injection design for Capacitance Coupled Contactless Conductivity detection technology

This novel capillary electrophoresis microchip, or also known as μTAS (micro total analysis system) was designed to separate complex aqueous based compounds, similar to commercial CE & microchip (capillary electrophoresis) systems, but more compact. This system can be potentially used for mobile/portable chemical analysis equipment. Un-doped silicon wafer & ultra-thin borofloat glass (Pyrex) wafers have been used to fabricate the device. Double-L injection feature, micro pillars column, bypass separation channel & hybrid- referenced C4D electrodes were designed to achieve a high SNR (signal to noise ratio), easy- separation, for a durable and reusable μTAS for CE use.

System innovation and life cycle thinking in packaging value chain: the circularity of plastics.

Compared to other, plastic materials have registered a strong acceleration in production and consumption during the last years. Despite the existence of waste management systems, plastic_based materials are still a pervasive presence in the environment, with negative consequences on marine ecosystem and human health. The recycling is still challenging due to the growing complexity of product design, the so-called overpackaging, the insufficient and inadequate recycling infrastructure, the weak market of recycled plastics and the high cost of waste treatment and disposal. The Circular economy package, the European Strategy for plastics in a circular economy and the recent European Green Deal include very ambitious programmes to rethink the entire plastic value chain. As regards packaging, all plastic packaging will have to be 100% recyclable (or reusable) and 55% recycled by 2030. Regions are consequently called upon to set up a robust plan able to fit the European objectives. It takes on greater importance in Emilia Romagna where the Packaging valley is located. This thesis supports the definition of a strategy aimed to establish an after-use plastics economy in the region. The PhD work has set the basis and the instruments to establish the so-called Circularity Strategy with the aim to turn about 92.000t of plastic waste into profitable secondary resources. System innovation, life cycle thinking and participative backcasting method have allowed to deeply analyse the current system, orientate the problem and explore sustainable solutions through a broad stakeholder participation. A material flow analysis, accompanied by a barrier analysis, has supported the identification of the gaps between the present situation and the 2030 scenario. Eco-design for and from recycling (and a mass _based recycling rate (based on the effective amount of plastic wastes turned into secondary plastics), valorized by a value_based indicator, are the key-points of the action plan.

Peptidomimetic ligands for tuning integrin-mediated signalling: rational design, synthesis and theranostic applications

Integrins are α/β-heterodimeric transmembrane adhesion receptors that mediate cell-cell and cell-ECM interactions. Integrins are bidirectional signalling receptors that respond to external signals (“outside-in” signalling) and in parallel, transduce internal signals to the matrix (“inside-out” signalling), to regulate vital cellular functions including migration, survival, growth and differentiation. Therefore, dysregulation of these tightly regulated processes often results in uncontrolled integrin activation and abnormal tissue expression that is responsible for many diseases. Because of their important roles in physiological and pathological events, they represent a validated target for therapeutic and diagnostic purposes. The aim of the present Thesis was focused on the development of peptidic ligands for α4β1 and αvβ3 integrin subtypes, involved in inflammatory responses (leukocytes recruitment and extravasation) and cancer progression (angiogenesis, tumor growth, metastasis), respectively. Following the peptidomimetic strategy, we designed and synthesized a small library of linear and cyclic hybrid α/β-peptidomimetics based on the phenylureido-LDV scaffolds for the treatment of chronic inflammatory autoimmune diseases. In order to implement a fast and non-invasive diagnostic method for monitoring the course of the inflammatory processes, a flat glass-surface of dye-loaded Zeolite L-crystal nanoparticles was coated with bioactive α4β1-peptidomimetics to detect specific integrin-expressing cells as biomarkers of inflammatory diseases. Targeted drug delivery has been considered a promising alternative to overcome the pharmacokinetic limitations of conventional anticancer drugs. Thus, a novel Small-Molecule Drug Conjugate was synthesized by connecting the highly cytotoxic Cryptophycin to the tumor-targeting RGDfK-peptide through a protease-cleavable linker. Finally, in view to making the peptide synthesis more sustainable and greener, we developed an alternative method for peptide bonds formation employing solvent-free mechanochemistry and ultra-mild minimal solvent-grinding conditions in common, inexpensive laboratory equipment. To this purpose, standard amino acids, coupling agents and organic-green solvents were used in the presence of nanocrystalline hydroxyapatite as a reusable, bio-compatible inorganic basic catalyst.

Synthesis, characterization, and application of PHB-based gels for cultural heritage conservation

The aim of my master thesis is developing novel, greener approaches for the cleaning of artworks: such treatment consists in the removal of old varnish layers which tend to discolor or darken with time, thus allowing replacement with a new protecting coat. While protocols presently applied can be effective in the cleaning of the artworks, none of them take into account conservators’ health safety and environmental issues. Thus, using biomass-derived components, which are non-toxic and reusable and/or compostable might bring into the heritage conservation an additional awareness about safety and environmental claiming. The laboratory work for the thesis is a collaborative work between different groups. The biggest part of the work was at the Polymer group where gels were synthesized using Polyhydroxybutyrate (PHB) from sustainable resources and green solvents. The use of the gels might help to reduce the volatilization of solvents and contributes to the localization of the cleaning action. After the preparation of the gels, different characterization methods were used in order to estimate their properties and shelf-life. Finally, the work was completed on the application of the gels on sculpture, coated with undesired layers to be removed. Here, pre-mapping of the areas of interest was realized with different optical techniques, followed by the application of the gels for the cleaning and analyzing the effectiveness of cleaning.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics.

Cyber threat intelligence: identifying hardcoded secrets in GitHub

The usage of version control systems and the capabilities of storing the source code in public platforms such as GitHub increased the number of passwords, API Keys and tokens that can be found and used causing a massive security issue for people and companies. In this project, SAP's secret scanner Credential Digger is presented. How it can scan repositories to detect hardcoded secrets and how it manages to filter out the false positives between them. Moreover, how I have implemented the Credential Digger's pre-commit hook. A performance comparison between three different implementations of the hook based on how it interacts with the Machine Learning model is presented. This project also includes how it is possible to use already detected credentials to decrease the number false positive by leveraging the similarity between leaks by using the Bucket System.