Cellular ROS imaging with hydro-Cy3 dye is strongly influenced by mitochondrial membrane potential

Background: Hydrocyanines are widely used as fluorogenic probes to monitor reactive oxygen species (ROS) generation in cells. Their brightness, stability to autoxidation and photobleaching, large signal change upon oxidation, pH independence and red/near infrared emission are particularly attractive for imaging ROS in live tissue. Methods: Using confocal fluorescence microscopy we have examined an interference of mitochondrial membrane potential (ΔΨm) with fluorescence intensity and localisation of a commercial hydro-Cy3 probe in respiring and non-respiring colon carcinoma HCT116 cells. Results: We found that the oxidised (fluorescent) form of hydro-Cy3 is highly homologous to the common ΔΨm-sensitive probe JC-1, which accumulates and aggregates only in ‘energised’ negatively charged mitochondrial matrix. Therefore, hydro-Cy3 oxidised by hydroxyl and superoxide radicals tends to accumulate in mitochondrial matrix, but dissipates and loses brightness as soon as ΔΨm is compromised. Experiments with mitochondrial inhibitor oligomycin and uncoupler FCCP, as well as a common ROS producer paraquat demonstrated that signals of the oxidised hydro-Cy3 probe rapidly and strongly decrease upon mitochondrial depolarisation, regardless of the rate of cellular ROS production. Conclusions: While analysing ROS-derived fluorescence of commercial hydrocyanine probes, an accurate control of ΔΨm is required. General significance: If not accounted for, non-specific effect of mitochondrial polarisation state on the behaviour of oxidised hydrocyanines can cause artefacts and data misinterpretation in ROS studies.

Using a discussion about scientific controversy to teach central concepts in experimental design

Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps rubella vaccine and autism controversy in the UK to illustrate a number of threshold concepts underlying good study design and interpretation of scientific evidence. These include the necessity of sufficient sample size, representative and random sampling, appropriate controls and inferring causation.

Hybridity in contemporary commercial organizations: implications for employee trust

This study advances the concept of organizational hybridity (OH). By doing so, it takes into account the individual level of analysis often neglected in organizational theory. More specifically, it aims to understand the implications of organizational hybridity for employees’ trust in contemporary commercial organizations. Informed and guided by current literature, this study argues that the current literature on organizational hybridity fails to adequately address the consequences of hybridity for employees' behaviour. The empirical study was conducted in 2014 using data collected via semi-structured interviews and document analysis. The study was based on a comparison of two case studies in Nigeria: Alter Securities Limited and Barak Petroleum Limited. A total of forty (40) interviews were conducted; twenty (20) from each organization. The data were analysed using thematic analysis. The main findings are that organizational hybridity in this study produced tensions that resulted in negative behavioural responses and employees’ distrust in the commercial hybrid organizations. However, employees’ identification with non-market orientated institutional logics such as family, philanthropic and religious logics is seen to facilitate their commitment, honesty, and trust in the organizations. Nevertheless, caution is required here as religious logics may also lead to an acceptance of unethical behaviour by employees. Overall, this study contributes to the literature on organizational hybridity by extending on Battilana and Lee’s (2014) framework, which highlights governance, leadership, organizational culture and intra-organizational relationships as core organizational attributes in the context of which issues may arise in commercial hybrid organizations. Furthermore, it addresses a gap in Besharov and Smith’s (2014) hybrid typology framework by providing an alternative line of argument focused on understanding how tensions manifest within commercial hybrid organizations. The key recommendations of this research underscore the need for commercial hybrid organizations to invest in mechanisms for improving employees’ trust so as to reap the benefits associated with trust. This could be achieved by involving employees in the decision-making process and clearly communicating the organizations’ values, so as to minimise the misinterpretation of the embodied institutional logics by employees.

GEOTECNOLOGIAS: POTENCIALIDADES E RISCOS GEOTECHNOLOGIES: MERITS AND RISKS

Esse artigo pretende discutir como as transformações tecnológicas vêm influenciando a ciência geográfica, especificamente com o advento das geotecnologias. Diante de inúmeras potencialidades e aplicações na análise e gestão territorial, nós devemos refletir sobre seu real significado, que certamente ultrapassa o caráter meramente técnico. É necessário compreender a vasta dimensão social, política e econômica que abrangem. Atualmente as técnicas são cada vez mais utilizadas, aceitas e menos compreendidas, o que pode implicar riscos para a sociedade em função de interpretações equivocadas e muitas vezes desprovidas de princípios éticos. Vinte anos após a “unificação” do mundo com a queda do Muro de Berlim, o cenário sociocultural e político se redefine em um paradigma de contradições. As inovações tecnológicas funcionam como um instrumento emblemático subordinado ao mercado financeiro e a globalização marca a atual fase do capitalismo, que segue seu curso encontrando as limitações inerentes à tecnologia em que se sustenta. This paper intends to discuss how the technological changes have affected the geographical science, specifically with the advent of geotechnologies. Up against with great potential and applications in analysis and land management, we must to reflect on its real meaning, which certainly goes beyond the merely technical. It’s necessary to understand the broad social, political and economic dimension wich inclued. Currently, the techniques are increasingly used, accepted and least understood, which may to implicate a risk to society due to misinterpretation and often devoid of ethical principles. Twenty years after the "unification" of the world with the fall of the Berlin Wall, the cultural and political landscape was altered in a paradigm of contradictions. Technological innovations work as a emblematic instrument subordinate to financial markets and globalization marks the current phase of capitalism, which runs its course finding the limitations inherent in the technology which supports.

Fracture Toughening and Self-Healing of Composite Laminates by Nanofibrous Mats Interleaving

Composite laminates present important advantages compared to conventional monolithic materials, mainly because for equal stiffness and strength they have a weight up to four times lower. However, due to their ply-by-ply nature, they are susceptible to delamination, whose propagation can bring the structure to a rapid catastrophic failure. In this thesis, in order to increase the service life of composite materials, two different approaches were explored: increase the intrinsic resistance of the material or confer to them the capability of self-repair. The delamination has been hindered through interleaving the composite laminates with polymeric nanofibers, which completed the hierarchical reinforcement scale of the composite. The manufacturing process for the integration of the nanofibrous mat in the laminate was optimized, resulting in an enhancement of mode I fracture toughness up to 250%. The effect of the geometrical dimensions of the nano-reinforcement on the architecture of the micro one (UD and woven laminates) was studied on mode I and II. Moreover, different polymeric materials were employed as nanofibrous reinforcement (Nylon 66 and polyvinylidene fluoride). The nano toughening mechanism was studied by micrograph analysis of the crack path and SEM analysis of the fracture surface. The fatigue behavior to the onset of the delamination and the crack growth rate for woven laminates interleaved with Nylon 66 nanofibers was investigated. Furthermore, the impact behavior of GLARE aluminum-glass epoxy laminates, toughened with Nylon 66 nanofibers was investigated. Finally, the possibility of confer to the composite material the capability of self-repair was explored. An extrinsic self-healing-system, based on core-shell nanofibers filled with a two-component epoxy system, was developed by co-electrospinning technique. The healing potential of the nano vascular system has been proved by microscope electron observation of the healing agent release as result of the vessels rupture and the crosslinking reaction was verified by thermal analysis.

Advanced electrospun nanofibrous mats for hindering delamination, improving damping and for sensing of composite laminates

Carbon Fiber Reinforced Polymers (CFRPs) display high specific mechanical properties, allowing the creation of lightweight components and products by metals replacement. To reach outstanding mechanical performances, the use of stiff thermoset matrices, like epoxy, is preferred. Laminated composites are commonly used for their ease of manipulation during object manufacturing. However, the natural anisotropic structure of laminates makes them vulnerable toward delamination. Moreover, epoxy-based CFRPs are very stiff materials, thus showing low damping capacity, which results in unwanted vibrations and structure-borne noise that may contribute to delamination triggering. Hence, searching for systems able to limit these drawbacks is of primary importance for safety reasons, as well as for economic ones. In this experimental thesis, the production and integration of innovative rubbery nanofibrous mats into CFRP laminates are presented. A smart approach, based on single-needle electrospinning of rubber-containing blends, is proposed for producing dimensionally stable rubbery nanofibers without the need for rubber crosslinking. Nano-modified laminates aim at obtaining structural composites with improved delamination resistance and enhanced damping capacity, without significantly lowering other relevant mechanical properties. The possibility of producing nanofibers nano-reinforced with graphene to be applied for reinforcing composite laminates is also investigated. Moreover, the use of piezoelectric nanofibrous mats in hybrid composite laminates for achieving self-sensing capability is presented too as a different approach to prevent the catastrophic consequences of possible structural laminate failure. Finally, an accurate, systematic, and critical study concerning tensile testing of nonwovens, using electrospun Nylon 66 random nanofibrous mats as a case study, is proposed. Nanofibers diameter and specimen geometry were investigated to thoroughly describe the nanomat tensile behaviour, also considering the polymer thermal properties, and the number of nanofibers crossings as a function of the nanofibers diameter. Stress-strain data were also analysed using a phenomenological data fitting model to interpret the tensile behaviour better.

Integrating Machine Learning Paradigms for Predictive Maintenance in the Fourth Industrial Revolution era

In the last decade, manufacturing companies have been facing two significant challenges. First, digitalization imposes adopting Industry 4.0 technologies and allows creating smart, connected, self-aware, and self-predictive factories. Second, the attention on sustainability imposes to evaluate and reduce the impact of the implemented solutions from economic and social points of view. In manufacturing companies, the maintenance of physical assets assumes a critical role. Increasing the reliability and the availability of production systems leads to the minimization of systems’ downtimes; In addition, the proper system functioning avoids production wastes and potentially catastrophic accidents. Digitalization and new ICT technologies have assumed a relevant role in maintenance strategies. They allow assessing the health condition of machinery at any point in time. Moreover, they allow predicting the future behavior of machinery so that maintenance interventions can be planned, and the useful life of components can be exploited until the time instant before their fault. This dissertation provides insights on Predictive Maintenance goals and tools in Industry 4.0 and proposes a novel data acquisition, processing, sharing, and storage framework that addresses typical issues machine producers and users encounter. The research elaborates on two research questions that narrow down the potential approaches to data acquisition, processing, and analysis for fault diagnostics in evolving environments. The research activity is developed according to a research framework, where the research questions are addressed by research levers that are explored according to research topics. Each topic requires a specific set of methods and approaches; however, the overarching methodological approach presented in this dissertation includes three fundamental aspects: the maximization of the quality level of input data, the use of Machine Learning methods for data analysis, and the use of case studies deriving from both controlled environments (laboratory) and real-world instances.

Continual learning for computer vision applications

One of the most visionary goals of Artificial Intelligence is to create a system able to mimic and eventually surpass the intelligence observed in biological systems including, ambitiously, the one observed in humans. The main distinctive strength of humans is their ability to build a deep understanding of the world by learning continuously and drawing from their experiences. This ability, which is found in various degrees in all intelligent biological beings, allows them to adapt and properly react to changes by incrementally expanding and refining their knowledge. Arguably, achieving this ability is one of the main goals of Artificial Intelligence and a cornerstone towards the creation of intelligent artificial agents. Modern Deep Learning approaches allowed researchers and industries to achieve great advancements towards the resolution of many long-standing problems in areas like Computer Vision and Natural Language Processing. However, while this current age of renewed interest in AI allowed for the creation of extremely useful applications, a concerningly limited effort is being directed towards the design of systems able to learn continuously. The biggest problem that hinders an AI system from learning incrementally is the catastrophic forgetting phenomenon. This phenomenon, which was discovered in the 90s, naturally occurs in Deep Learning architectures where classic learning paradigms are applied when learning incrementally from a stream of experiences. This dissertation revolves around the Continual Learning field, a sub-field of Machine Learning research that has recently made a comeback following the renewed interest in Deep Learning approaches. This work will focus on a comprehensive view of continual learning by considering algorithmic, benchmarking, and applicative aspects of this field. This dissertation will also touch on community aspects such as the design and creation of research tools aimed at supporting Continual Learning research, and the theoretical and practical aspects concerning public competitions in this field.

Valutazione e gestione del rischio per i Beni Culturali: strumenti e metodologie

Il patrimonio culturale sopravvissuto fino ai giorni nostri nonostante calamità naturali ed eventi catastrofici è oggi sempre più in pericolo: gli eventi naturali, accelerati e resi ancora più distruttivi dagli effetti del cambiamento climatico, lo scoppio continuo di nuovi conflitti armati e l’inconsapevolezza con cui gli uomini sfruttano il territorio comportano un aumento dei rischi e dei possibili danni ad un patrimonio che, tuttavia, è di importanza vitale per la crescita dell’umanità. Per evitare che il patrimonio culturale venga disperso o distrutto, è necessario applicare misure di prevenzione e protezione mirate, utilizzando in maniera efficiente gli strumenti disponibili; lo scopo ultimo della prevenzione e della protezione deve essere la resilienza, che va costruita attraverso la conoscenza e l’attenta pianificazione della gestione del patrimonio. Il presente lavoro di ricerca si propone dunque di analizzare i metodi e le strategie utilizzabili per la valutazione e la gestione del rischio applicati ai beni culturali, verificando a quale livello di consapevolezza si è giunti a livello sia nazionale che internazionale, passando in rassegna le tecnologie che permettono di proteggere il patrimonio agevolando il lavoro di mitigazione del rischio e applicando un prototipo di calcolo e analisi del rischio al caso studio del Museo di Nonantola, in provincia di Modena.

Numerical prediction of the lateral displacement capacity of flexural reinforced concrete shear walls

Previous earthquakes showed that shear wall damage could lead to catastrophic failures of the reinforced concrete building. The lateral load capacity of shear walls needs to be estimated to minimize associated losses during catastrophic events; hence it is necessary to develop and validate reliable and stable numerical methods able to converge to reasonable estimations with minimum computational effort. The beam-column 1-D line element with fiber-type cross-section model is a practical option that yields results in agreement with experimental data. However, shortcomings of using this model to predict the local damage response may come from the fact that the model requires fine calibration of material properties to overcome regularization and size effects. To reduce the mesh-dependency of the numerical model, a regularization method based on the concept of post-yield energy is applied in this work to both the concrete and the steel material constitutive laws to predict the nonlinear cyclic response and failure mechanism of concrete shear walls. Different categories of wall specimens known to produce a different response under in plane cyclic loading for their varied geometric and detailing characteristics are considered in this study, namely: 1) scaled wall specimens designed according to the European seismic design code and 2) unique full-scale wall specimens detailed according to the U.S. design code to develop a ductile behavior under cyclic loading. To test the boundaries of application of the proposed method, two full-scale walls with a mixed shear-flexure response and different values of applied axial load are also considered. The results of this study show that the use of regularized constitutive models considerably enhances the response predictions capabilities of the model with regards to global force-drift response and failure mode. The simulations presented in this thesis demonstrate the proposed model to be a valuable tool for researchers and engineers.