Interaction techniques with novel multimodal feedback for addressing gesture-sensing systems

Users need to be able to address in-air gesture systems, which means finding where to perform gestures and how to direct them towards the intended system. This is necessary for input to be sensed correctly and without unintentionally affecting other systems. This thesis investigates novel interaction techniques which allow users to address gesture systems properly, helping them find where and how to gesture. It also investigates audio, tactile and interactive light displays for multimodal gesture feedback; these can be used by gesture systems with limited output capabilities (like mobile phones and small household controls), allowing the interaction techniques to be used by a variety of device types. It investigates tactile and interactive light displays in greater detail, as these are not as well understood as audio displays. Experiments 1 and 2 explored tactile feedback for gesture systems, comparing an ultrasound haptic display to wearable tactile displays at different body locations and investigating feedback designs. These experiments found that tactile feedback improves the user experience of gesturing by reassuring users that their movements are being sensed. Experiment 3 investigated interactive light displays for gesture systems, finding this novel display type effective for giving feedback and presenting information. It also found that interactive light feedback is enhanced by audio and tactile feedback. These feedback modalities were then used alongside audio feedback in two interaction techniques for addressing gesture systems: sensor strength feedback and rhythmic gestures. Sensor strength feedback is multimodal feedback that tells users how well they can be sensed, encouraging them to find where to gesture through active exploration. Experiment 4 found that they can do this with 51mm accuracy, with combinations of audio and interactive light feedback leading to the best performance. Rhythmic gestures are continuously repeated gesture movements which can be used to direct input. Experiment 5 investigated the usability of this technique, finding that users can match rhythmic gestures well and with ease. Finally, these interaction techniques were combined, resulting in a new single interaction for addressing gesture systems. Using this interaction, users could direct their input with rhythmic gestures while using the sensor strength feedback to find a good location for addressing the system. Experiment 6 studied the effectiveness and usability of this technique, as well as the design space for combining the two types of feedback. It found that this interaction was successful, with users matching 99.9% of rhythmic gestures, with 80mm accuracy from target points. The findings show that gesture systems could successfully use this interaction technique to allow users to address them. Novel design recommendations for using rhythmic gestures and sensor strength feedback were created, informed by the experiment findings.

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review

The purpose of this paper is to survey and assess the state-of-the-art in automatic target recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an exhaustive survey of the voluminous literature, but rather to capture in one place the various approaches for implementing the SAR-ATR system. This paper is meant to be as self-contained as possible, and it approaches the SAR-ATR problem from a holistic end-to-end perspective. A brief overview for the breadth of the SAR-ATR challenges is conducted. This is couched in terms of a single-channel SAR, and it is extendable to multi-channel SAR systems. Stages pertinent to the basic SAR-ATR system structure are defined, and the motivations of the requirements and constraints on the system constituents are addressed. For each stage in the SAR-ATR processing chain, a taxonomization methodology for surveying the numerous methods published in the open literature is proposed. Carefully selected works from the literature are presented under the taxa proposed. Novel comparisons, discussions, and comments are pinpointed throughout this paper. A two-fold benchmarking scheme for evaluating existing SAR-ATR systems and motivating new system designs is proposed. The scheme is applied to the works surveyed in this paper. Finally, a discussion is presented in which various interrelated issues, such as standard operating conditions, extended operating conditions, and target-model design, are addressed. This paper is a contribution toward fulfilling an objective of end-to-end SAR-ATR system design.

'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'

Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.

PAMP-triggered immunity against Pseudomonas syringae involves microRNA-mediated regulation of several uncharacterized R genes

Two main types of noncoding small RNA molecules have been found in plants: microRNAs (miRNAs) and small interfering RNAs (siRNAs). They differ in their biogenesis and mode of action, but share similar sizes (20-24 nt). Their precursors are processed by Dicer-Like RNase III (dcl) proteins present in Arabidopsis thaliana, and in their mature form can act as negative regulators of gene expression, being involved in a vast array of plant processes, including plant development, genomic integrity or response to stress. Small-RNA mediated regulation can occurs at transcriptional level (TGS) or at post-transcriptional level (PTGS). In recent years, the role of gene silencing in the regulation of expression of genes related to plant defence responses against bacterial pathogens is becoming clearer. Comparisons carried out in our lab between the expression profiles of different mutants affected in gene silencing, and plants challenged with Pseudomonas syringae pathovar tomato DC3000, led us to identify a set of uncharacterized R genes, belonging to the TIR-NBS-LRR gene family, differentially expressed in these conditions. Through the use of bioinformatics tools, we found a miRNA* of 22 nt putatively responsible for down-regulating expression of these R genes through the generation of siRNAs. We have also found that the corresponding pri-miRNA is down-regulated after PAMP-perception in a SA-dependent manner. We also demonstrate that plants with altered levels of miRNA* (knockdown lines or overexpression lines) exhibit altered PTI-associated phenotypes, suggesting a role for this miRNA* in this defence response against bacteria. In addition we identify one of the target genes as a negative regulator of defence response against Pseudomonas syringae.

Adaptivity and a posteriori error control for bifurcation problems II: Incompressible fluid flow in open systems with Z_2 symmetry

In this article we consider the a posteriori error estimation and adaptive mesh refinement of discontinuous Galerkin finite element approximations of the bifurcation problem associated with the steady incompressible Navier-Stokes equations. Particular attention is given to the reliable error estimation of the critical Reynolds number at which a steady pitchfork or Hopf bifurcation occurs when the underlying physical system possesses reflectional or Z_2 symmetry. Here, computable a posteriori error bounds are derived based on employing the generalization of the standard Dual-Weighted-Residual approach, originally developed for the estimation of target functionals of the solution, to bifurcation problems. Numerical experiments highlighting the practical performance of the proposed a posteriori error indicator on adaptively refined computational meshes are presented.

Development of paclitaxel-loaded liposomal systems with anti-her2 antibody for targeted therapy

Purpose: To develop liposome formulations containing monoclonal antibody anti-HER2 (MabHer2), and Paclitaxel (PTX). Methods: Seven different liposomal systems containing PTX, or MabHer2 or a combination of PTX and MabHer2 were made using lipid film hydration technique and sonication. The effects of liposome preparation conditions and extraction methods on antibody structure were investigated by polyacrylamide gel electrophoresis and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The characteristics of the liposomes were determined by a zetasizer, while drug-loading efficiency was evaluated by high-performance liquid chromatography. The cytotoxic effect of the liposome formulations was evaluated on MDA-MB-453 (HER2+) and MCF-7 (HER2-) breast cancer cell lines by MTT assay. Results: The antibody was not significantly affected by the stress conditions and the method of extraction. The particle size of liposomes was < 200 nm while the amount of incorporated PTX was 97.6 % for liposome without cationic agent and 98.2 % for those with cationic agent. Recovery of MabHer2 was 94.38 % after extraction. Combined PTX/MabHer2 liposome was more toxic on HER2 overexpressing positive MDA-MB-453 cell line than PTX-loaded liposomes and MabHer2. MabHer2 and combined PTX/MabHer2 liposomes showed no toxic effects on HER2 overexpressing negative MCF-7 cells relative to cationic PTX-loaded liposomes. Conclusions: This results obtained show that PTX can be encapsulated successfully into liposoma systems and that owing to Her2 specific antibody, these systems can be delivered directly to the target cell.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Using modeling tools for implementing feasible land use and nature conservation governance systems in small islands e The Pico Island (Azores) case-study

The present study deals with the development of systematic conservation planning as management instrument in small oceanic islands, ensuring open systems of governance, and able to integrate an informed and involved participation of the stakeholders. Marxan software was used to define management areas according a set of alternative land use scenarios considering different conservation and management paradigms. Modeled conservation zones were interpreted and compared with the existing protected areas allowing more fused information for future trade-outs and stakeholder's involvement. The results, allowing the identification of Target Management Units (TMU) based on the consideration of different development scenarios proved to be consistent with a feasible development of evaluation approaches able to support sound governance systems. Moreover, the detailed geographic identification of TMU seems to be able to support participated policies towards a more sustainable management of the entire island

Interoperability Challenges in Internet of Things Systems: a Service-Oriented Computing Approach

Internet of Things systems are pervasive systems evolved from cyber-physical to large-scale systems. Due to the number of technologies involved, software development involves several integration challenges. Among them, the ones preventing proper integration are those related to the system heterogeneity, and thus addressing interoperability issues. From a software engineering perspective, developers mostly experience the lack of interoperability in the two phases of software development: programming and deployment. On the one hand, modern software tends to be distributed in several components, each adopting its most-appropriate technology stack, pushing programmers to code in a protocol- and data-agnostic way. On the other hand, each software component should run in the most appropriate execution environment and, as a result, system architects strive to automate the deployment in distributed infrastructures. This dissertation aims to improve the development process by introducing proper tools to handle certain aspects of the system heterogeneity. Our effort focuses on three of these aspects and, for each one of those, we propose a tool addressing the underlying challenge. The first tool aims to handle heterogeneity at the transport and application protocol level, the second to manage different data formats, while the third to obtain optimal deployment. To realize the tools, we adopted a linguistic approach, i.e.\ we provided specific linguistic abstractions that help developers to increase the expressive power of the programming language they use, writing better solutions in more straightforward ways. To validate the approach, we implemented use cases to show that the tools can be used in practice and that they help to achieve the expected level of interoperability. In conclusion, to move a step towards the realization of an integrated Internet of Things ecosystem, we target programmers and architects and propose them to use the presented tools to ease the software development process.

Identificazione di un nuovo meccanismo microRNA-dipendente di resistenza all'inibizione della via di segnale PI3K/AKT nel carcinoma della prostata

Benché le alterazioni della via PI3K/AKT siano molto sudiate a causa del loro ruolo nella tumorigenesi, e rappresentino pertanto un importante bersaglio terapeutico, i risultati di numerosi studi clinici con inibitori di PI3K o AKT sono finora deludenti, in parte a causa dell’insorgenza di resistenza provocata dall'interruzione dei circuiti di feedback negativo. In questo studio, abbiamo scoperto che l’inattivazione farmacologica di AKT in cellule di carcinoma prostatico PC3 porta alla down-regolazione di un microRNA con funzione di oncosoppressore, il miR-145-5p, e ad un drammatico aumento di espressione di uno dei suoi geni target, cioè N/KRas. E’ interessante sottolineare che questo microRNA è considerato un marker di progressione metastatica nel carcinoma prostatico, il cui livello di espressione aiuta a discriminare tra pazienti con iperplasia prostatica benigna e cancro alla prostata. Inoltre, la bassa espressione di miR-145 aumenta il rischio di progressione della malattia da localizzata a metastatica. La conferma che l’aumento di Ras, osservato sia in termini di mRNA che di proteina, è dipendente dalla caduta del miR-145-5p, è stata poi ottenuta tramite un modello di PC3 ingegnerizzate per ottenere il silenziamento inducibile del miR-145-5p. Tramite un array di fosfoproteine siamo poi stati in grado di verificare che l’aumento di Ras provoca la riattivazione della cascata di PI3K/AKT e di ERK. Dal punto di vista meccanicistico, quindi, lo studio ha portato all’identificazione di un nuovo meccanismo di resistenza adattativa, in cui l’inattivazione di AKT provoca una caduta del miR-145-5p che, a sua volta, aumenta l’espressione di Ras e riattiva il signaling di PI3K, rendendo inefficace il trattamento farmacologico. Questi risultati sono particolarmente rilevanti alla luce di recenti studi (NCT04493853; NCT03072238; NCT02525068) e di trial clinici in corso (NCT04737109; NCT03673787), basati sulla somministrazione combinata di inibitori della sintesi degli androgeni con gli inibitori di AKT capitasertib o ipatasertib.

Appropriate technologies and natural systems for wastewater treatment in low- and middle-income countries

Wastewater management is an environmental and social burden that primarily affects populations in Low- and Middle-Income Countries and the global environment. Wastewater collection, treatment, and reuse have become urgent, especially considering that 80% of the world's wastewater is untreated or improperly treated and discharged directly into water bodies. In recent years, the role of wastewater treatment plants in a sustainable water cycle has become even more critical, as they are the final destination of the collected wastewater. Indeed, the management of wastewater treatment plants should play an essential role in achieving SDG target 6.3 of the United Nations 2030 Agenda for SD. In this context, water reuse, especially wastewater reuse, plays a key role. This research focuses on investigating the valorization of wastewater resources applying Appropriate Technologies and Natural Systems for wastewater treatment in two different Low- and Middle-Income Countries, the Palestinian Territories and Sub-Saharan Africa. The research objectives are: (1) Determine the characteristics and quality of wastewater in the two case studies analysed. (2) Identify Appropriate Technology to be used in the Palestinian Territories to treat wastewater for reuse in agriculture. (3) Assess the environmental, economic, and social impacts of this project. (4) Assess the feasibility of using natural wetlands for household wastewater treatment in Sub-Saharan region. The first study, conducted in Rafah, Gaza Strip, showed that implementing existing primary treatment plant with a natural secondary treatment plant properly optimized the wastewater quality for reuse in agriculture and was suitable for the study area. The second case study was conducted in Cape Coast, Ghana. It shows that the natural wetland studied is currently overly polluted and threatened by various anthropogenic factors that cannot remove pollutants from the incoming domestic wastewater. Therefore, some recommendations were made in order to improve the efficiency of this natural wetland.

Design and evaluation of aerosol and liquid separation systems

Conventional chromatographic columns are packed with porous beads by the universally employed slurry-packing method. The lack of precise control of the particle size distribution, shape and position inside the column have dramatic effects on the separation efficiency. In the first part the thesis an ordered, three-dimensional, pillar-array structure was designed by a CAD software. Several columns, characterized by different fluid distributors and bed length, were produced by a stereolithographic 3D printer and compared in terms of pressure drop and height equivalent to a theroretical plate (HETP). To prevent the release of unwanted substances and to provide a surface for immobilizing a ligand, pillars were coated with one or more of the following materials: titanium dioxide, nanofibrillated cellulose (NFC) and polystyrene. The external NFC layer was functionalized with Cibacron Blue and the dynamic binding capacity of the column was measured by performing three chromatographic cycles, using bovine serum albumin (BSA) as target molecule. The second part of the thesis deals with Covid-19 pandemic related research activities. In early 2020, due to the pandemic outbreak, surgical face masks became an essential non-pharmaceutical intervention to limit the spread. To address the consequent shortage and to support the reconversion of the Italian industry, in late March 2020 a multidisciplinary group of the University of Bologna created the first Italian laboratory able to perform all the tests required for the evaluation and certification of surgical masks. More than 1200 tests were performed on about 350 prototypes, according to the standard EN 14683:2019. The results were analyzed to define the best material properties and masks composition for the production of masks with excellent efficiency. To optimize the usage of surgical masks and to reduce their environmental burden, the variation of their performance over time of usage were investigated as to determine the maximum lifetime.

Development of sexing systems functional to mass production of Aedes albopictus sterile males

Aedes albopictus is a vector able to transmit several arboviruses. Due to its high impact on human health, it is important to develop an efficient control strategy for this pest. Nowadays, control based on chemical insecticides is limited by the number of available active principles and the occurrence of resistance. A valuable alternative to the conventional control strategies is the sterile insect technique (SIT) which relies on releasing sterile males of the target insect. Mating between wild females and sterile males results in no viable offspring. A crucial aspect of SIT is the production of a large number of sterile males with a low presence of females that can bite and transmit viruses. The present thesis aimed to find, implement and study the most reliable mechanical sex sorter and protocol to implement male productivity and reduce female contamination. In addition, I evaluated different variables and sorting protocols to enable female recovery for breeding purposes. Furthermore, I studied the creation of a hyper-protandric strain potentially able to produce only males. I also assessed the integration of artificial intelligence with an optical unit to identify sexes at the adult stage. All these applications helped to realise a mass production model in Italy with a potential weekly production of 1 million males. Moreover, I studied and applied for aerial sterile male release in an urban environment. This technology could allow the release of males in a wide area, overcoming environmental and urban obstacles. However, the development and application of drone technologies in a metropolitan area close to airports, such as in Bologna area, must fit specific requirements. Lastly, at Réunion Island, during a Short Term Scientific Mission France (AIM-COST Action), Indian Ocean, I studied the Boosted SIT application. Coating sterile males with Pyriproxyfen may help spread the insecticide into the larval breeding sites.