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Ultrasonic-assisted enzymatic extraction of sulfated polysaccharide from Skipjack tuna by-products
Get PDFThe effect of ultrasound pretreatment on extraction efficiency of sulfate polysaccharides (SPs) using alcalase from different by-products of Skipjack tuna including head, bone and skin was evaluated. Structural, functional, antioxidant and antibacterial properties of the recovered SPs using the ultrasound-enzyme and enzymatic method were also investigated. Ultrasound pretreatment significantly increased the extraction yield of SPs from all the three by-products compared with the conventional enzymatic method. All extracted SPs showed high antioxidant potential in terms of ABTS, DPPH and ferrous chelating activities where the ultrasound treatment enhanced antioxidant activities of the SPs. The SPs exerted strong inhibiting activity against various Gram-positive and Gram-negative bacteria. The ultrasound treatment remarkably increased antibacterial activity of the SPs against L. monocytogenes but its effect on other bacteria was dependent on the source of the SPs. Altogether, the results suggest that ultrasound pretreatment during enzymatic extraction of SPs from tuna by-products can be a promising approach to improve extraction yield but also bioactivity of the extracted polysaccharides
Ionizable lipids penetrate phospholipid bilayers with high phase transition temperatures: perspectives from free energy calculations
Get PDFThe efficacies of modern gene-therapies strongly depend on their contents. At the same time the most potent formulations might not contain the best compounds. In this work we investigated the effect of phospholipids and their saturation on the binding ability of (6Z,9Z,28Z,31Z)-heptatriacont-6,9,28,31-tetraene-19-yl 4-(dimethylamino) butanoate (DLin-MC3-DMA) to model membranes at the neutral pH. We discovered that DLin-MC3-DMA has affinity to the most saturated monocomponent lipid bilayer 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and an aversion to the unsaturated one 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC). The preference to a certain membrane was also well-correlated to the phase transition temperatures of phospholipid bilayers, and to their structural and dynamical properties. Additionally, in the case of the presence of DLin-MC3-DMA in the membrane with DOPC the ionizable lipid penetrated it, which indicates possible synergistic effects. Comparisons with other ionizable lipids were performed using a model lipid bilayer of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC). Particularly, the lipids heptadecan-9-yl 8-[2-hydroxyethyl-(6-oxo-6-undecoxyhexyl)amino]octanoate (SM-102) and [(4-hydroxybutyl) azanediyl] di(hexane-6,1-diyl) bis(2-hexyldecanoate) (ALC-0315) from modern mRNA-vaccines against COVID-19 were investigated and force fields parameters were derived for those new lipids. It was discovered that ALC-0315 binds strongest to the membrane, while DLin-MC3-DMA is not able to reside in the bilayer center. The ability to penetrate the membrane POPC by SM-102 and ALC-0315 can be related to their saturation, comparing to DLin-MC3-DMA
No Ground Truth at Sea - Developing High-Accuracy AI Decision-Support for Complex Environments
No full textAs AI decision-support systems are increasingly developed for applications outside of traditional organizational confinements, developers are confronted with new sources of complexity they need to address. However, we know little about how AI applications are developed for natural use domains with high environmental complexity, stemming from physical influences outside of the developers\u27 control. This study investigates what challenges emerge from such complexity and how developers mitigate them. Drawing upon a rich longitudinal single-case study on the development of AI decision-support for maritime navigation, findings show that achieving high output accuracy is complicated by the physical environment hindering training data creation. Further, developers chose to reduce the output accuracy and adapt the HMI design to successfully situate the AI application in an existing sociotechnical context. This study contributes to IS literature following recent calls for phenomenon-based examination of emerging challenges when extending the scope frontier of AI and provides practical recommendations for developing AI decision-support for complex environments
Optimal capacity of solar photovoltaic and battery storage for grid-tied houses based on energy sharing
Get PDFThis paper determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) for a grid-connected house based on an energy-sharing mechanism. The grid-connected house, also mentioned as house 1 where it is relevant, shares electricity with house 2 under a mutually agreed fixed energy price. The objective is to minimize the cost of electricity (COE) for house 1 while decreasing the electricity cost of house 2. Practical factors such as real data for solar insolation, electricity consumption, grid constraint, ambient temperature, electricity rate, and battery degradation are considered based on actual data. The developed methodology is examined by taking the actual load data of two houses in South Australia. Different scenarios of contract years between the houses are investigated to make it more practical in real life. Sensitivity analyses are conducted for the sharing of energy between the houses and by changing parameters like export power limitation, load of houses, and costs of PV and BES. Likewise, operational analysis is done for two days of summer and winter. It is found that when energy sharing is applied, the optimal design of the PV-BES system will achieve lower COE for both houses
Computational driver behavior models for vehicle safety applications
Get PDFThe aim of this thesis is to investigate how human driving behaviors can be formally described in mathematical models intended for online personalization of advanced driver assistance systems (ADAS) or offline virtual safety evaluations. Both longitudinal (braking) and lateral (steering) behaviors in routine driving and emergencies are addressed. Special attention is paid to driver glance behavior in critical situations and the role of peripheral vision.First, a hybrid framework based on autoregressive models with exogenous input (ARX-models) is employed to predict and classify driver control in real time. Two models are suggested, one targeting steering behavior and the other longitudinal control behavior. Although the predictive performance is unsatisfactory, both models can distinguish between different driving styles.Moreover, a basic model for drivers\u27 brake initiation and modulation in critical longitudinal situations (specifically for rear-end conflicts) is constructed. The model is based on a conceptual framework of noisy evidence accumulation and predictive processing. Several model extensions related to gaze behavior are also proposed and successfully fitted to real-world crashes and near-crashes. The influence of gaze direction is further explored in a driving simulator study, showing glance response times to be independent of the glance\u27s visual eccentricity, while brake response times increase for larger gaze angles, as does the rate of missed target detections.Finally, the potential of a set of metrics to quantify subjectively perceived risk in lane departure situations to explain drivers\u27 recovery steering maneuvers was investigated. The most influential factors were the relative yaw angle and splay angle error at steering initiation. Surprisingly, it was observed that drivers often initiated the recovery steering maneuver while looking off-road.To sum up, the proposed models in this thesis facilitate the development of personalized ADASs and contribute to trustworthy virtual evaluations of current, future, and conceptual safety systems. The insights and ideas contribute to an enhanced, human-centric system development, verification, and validation process. In the long term, this will likely lead to improved vehicle safety and a reduced number of severe injuries and fatalities in traffic
Measurements and simulations of thermoplasmonically induced Marangoni flows
Get PDFParticle transport in microfluidic environments is often dominated by slow diffusion near interfaces. However, by inducing localized fluid flow, it is possible to actively transport suspended nano-objects in confined spaces. One promising method for achieving precise and dynamic control over fluid flow on the microscale is to use photothermal effects based on the illumination of plasmonic metal nanoparticles, which exhibit very high optical absorption for light wavelengths near resonance. The particles can thus be used as nanoscale heat sources that locally increase the temperature of the surrounding fluid, resulting in processes such as thermophoresis, convection, and vapor bubble generation. This thesis focuses on the latter effect and the associated bubble nucleation and thermal Marangoni convection processes.Marangoni flows result from the surface tension gradient that establishes on a thermoplasmonically induced vapor bubble at equilibrium. However, in addition to this, strong flow transients appear as a bubble is created and expands. Both phenomena lead to similar flow profiles. Here it is shown that the direction of these flows can be controlled by manipulating the temperature gradient on the surface of the bubble. Specifically, it is demonstrated that the direction of the strong transient flows around a nanobubble can be reverted by breaking the photothermal symmetry using two unequal nearby arrays of plasmonic nanoparticles. Furthermore, we investigate the possibility of remotely controlling the flow direction by turning the incident light polarization. The results are based on vectorial flow measurements using optical force microscopy supported by extensive flow profile simulations
Gaze Based Human Intention Analysis
Get PDFThe ability to determine an upcoming action or what decision a human is about to take, can be useful in multiple areas, for example during human-robot collaboration in manufacturing, where knowing the intent of the operator could provide the robot with important information to help it navigate more safely. Another field that could benefit from a system that provides information regarding human intentions is the field of psychological testing where such a system could be used as a platform for new research or be one way to provide information in the diagnostic process. The work presented in this thesis investigates the potential use of virtual reality as a safe, measurable, and customizable environment to collect gaze and movement data, eye tracking as the non-invasive system input that gives insight into the human mind, and deep machine learning as one tool to analyze the data. The thesis defines an experimental procedure that can be used to construct a virtual reality based testing system that gathers gaze and movement data, carry out a test study to gather data from human participants, and implement artificial neural networks in order to analyze human behaviour. This is followed by two studies that gives evidence to the decisions that were made in the experimental procedure and shows the potential uses of such a system
Field, capital, and habitus: The impact of Pierre Bourdieu on bibliometrics
Get PDFThis study is a critical review aimed at assessing the reception received in bibliometric research by the theories and concepts developed by the sociologist Pierre Bourdieu. The data set consists of 182 documents, including original articles, editorial material, review articles, conference papers, monographs, and doctoral dissertations. A quantitative analysis was used to establish the authors and countries that most frequently make use of Bourdieu’s theories, as well as the most popular concepts, which were identified as “field,” followed by “symbolic capital” and “social capital.” Then, the article discusses the impact of Bourdieusian key concepts such as “field.” Among the findings, the following are noteworthy: the integration of his field theory into pre-existing bibliometric conceptualizations of research fields, especially when power relations are problematized; the use of “symbolic capital” in connection with citation analysis and altmetrics; and greater interest in Bourdieu’s theories compared to his methods, although some sources have used Bourdieu’s preferred statistical method, correspondence analysis. Moreover, Bourdieu’s theoretical impact is noticeable in research on journals, university rankings, early career researchers, and gender. The paper’s conclusions point to future research paths based on concepts less used in the bibliometric literature, such as “delegation.”
Choreographies and Cost Semantics for Reliable Communicating Systems
Get PDFCommunicating systems have become ubiquitous in today\u27s society.Unfortunately, the complexity of their interactions makesthem particularly prone to failures such as deadlocked statescaused by misbehaving components, or memory exhaustion due to a surgein message traffic (malicious or not).These vulnerabilities constitute a real risk to users, withconsequences ranging from minor inconveniences to the possibility ofloss of life and capital.This thesis presents results that aim to increase the reliability of communicating systems.First, we implement a choreography language that can, by construction, only describe deadlock-free systems.Second, we develop a cost semantics to prove programs free of out-of-memory errors.Lastly, we improve both results by using novel semantic approaches that strengthen key theorems and facilitate further proof development.All of these results are formalized in the HOL4 theorem prover and integrated with the CakeML verified stack