This master’s thesis aims to explore the practice of becoming a researcher and the learning process embedded in this activity by looking at the communicative practices of PhD students, within the context of academic publishing. It is likely that the way in which these soon-to-be researchers reason about the task of communication is related to their way of approaching their field of research as well as the lived world, which makes it relevant to explore further. The study was performed based two sets of data, first open-ended semi-structured interviews with eleven PhD students at Stockholm University, where they talk about their current situation, their motivations and goals and about how they plan to publish their dissertation. Secondly, an analysis of data about publications focusing on work by PhD students at Stockholm University between 2013–2016, and information about how the intended audience, i.e. the readers, have interacted with the published material. These two sets of data were analysed with the use of theories about personal epistemology, sociocultural learning and the rationality of actions. The study shows that the majority of the PhD students at Stockholm University publishes their research findings as scholarly articles in English. The conclusion is also that the publishing process can be understood as a pedagogical tool, as it provides a vehicle for the PhD students to immerse themselves in their community of practice. These findings suggest that it could be useful to further emphasise the publishing activity as a learning process that may lead to a deeper understanding of the role of the researcher in society. / Den här masteruppsatsen avser att utforska hur doktorander lär sig sitt framtida yrke, och hur de socialiseras till att bli forskare via de kommunikativa praktiker som de ägnar sig åt, dvs. akademisk publicering. Dessa kommunikativa praktiker torde vara kopplade till hur en forskare relaterar till sitt forskningsfält, men också sin omvärld, och företeelsen är därför intressant att ytterligare belysa. Studien är genomförd i två delar. Den första delen består av intervjumaterial från samtal med 11 doktorander vid Stockholms universitet. Den andra delen består av en analys av statistik om elektroniska publikationer av doktorander vid Stockholms universitet under perioden 2013–2016. Publikationerna sätts sedan i relation till data om hur läsekretsen har interagerat med publikationerna via olika media och citeringar. De två dataseten analyseras med hjälp av teorier om personlig epistemologi, sociokulturellt lärande och handlingsrationalitet. Slutsatserna är att de flesta doktorander vid Stockholms universitet väljer att publicera sig i vetenskapliga tidskrifter på engelska, och att dessa kommunikativa praktiker kan förstås som ett pedagogiskt verktyg när det gäller lärande om och förståelse för doktorandernas kontext eller gemenskap. Resultatet av studien indikerar att det kan vara meningsfullt att fokusera på publicering, eller liknande kommunikativa praktiker, som en användbar lärandeprocess när det gäller att förstå mer om forskarens roll i samhället.

The intent of this study was to establish and validate criteria for use to assess the quality of a library and information sciences (LIS) Ph.D. program. The Ph.D. student-centric topology for quality Ph.D. programs was developed from a 2001 position statement by the American Association of Colleges of Nursing (AACN) regarding the quality indicators in research-focused doctoral programs in nursing. Topology components were tested using a survey instrument to establish their importance to the community of practice and their potential use to assess a Ph.D. program. Survey participants were asked to rank terms or concepts in a balanced incomplete block (BIB) design then rate, on a Likert-type scale, statements about the applicability of these terms or concepts to assessing a quality LIS Ph.D. program. Survey participants were from the Association for Library and Information Science Education (ALISE) Open Lib/Info Sci Education Forum jESSE Listserv. Of 225 survey participants affiliated with universities or schools from North America who submitted usable surveys, slightly less than two-thirds (64.4 %) were female while 35.5 % were male. Ninety-eight participants (43.6 %) were faculty, 114 (50.7 %) were Ph.D. students or candidates, and 13 (5.8 %) were in other roles. Statistical analysis of survey responses showed consistent results between the different demographic groups. The topology was validated by the results of the statistical analysis of the research data. Every component of the topology was acknowledged as very important to assess the quality of a LIS Ph.D. program. Faculty was the highest ranked item in the BIB analysis with a statistically significant difference (p < .0001) in the mean rank order from the next highest ranked item, Ph.D. students. The rank order from the BIB analysis was as follows: faculty, Ph.D. students, programs (courses) of study, teaching, learning environment, resources, and evaluation. Faculty was also the highest rated item in the Likert-type statement analysis.

<div>Multi-target tracking (MTT) is the problem to simultaneously estimate the number of targets and their states or trajectories. Numerous techniques have been developed for over 50 years, with a multitude of applications in many fields of study; however, there are two most widely used approaches to MTT: i) data association-based traditional algorithms; and ii) finite set statistics (FISST)-based data association free Bayesian multi-target filtering algorithms. Most data association-based traditional filters mainly use a statistical or simple model of the feature without explicitly considering the correlation between the target behavior</div><div>and feature characteristics. The inaccurate model of the feature can lead to divergence of the estimation error or the loss of a target in heavily cluttered and/or low signal-to-noise ratio environments. Furthermore, the FISST-based data association free Bayesian multi-target filters can lose estimates of targets frequently in harsh environments mainly</div><div>attributed to insufficient consideration of uncertainties not only measurement origin but also target's maneuvers.</div><div>To address these problems, three main approaches are proposed in this research work: i) new feature models (e.g., target dimensions) dependent on the target behavior</div><div>(i.e., distance between the sensor and the target, and aspect-angle between the longitudinal axis of the target and the axis of sensor line of sight); ii) new Gaussian mixture probability hypothesis density (GM-PHD) filter which explicitly considers the uncertainty in the measurement origin; and iii) new GM-PHD filter and tracker with jump Markov system models. The effectiveness of the analytical findings is demonstrated and validated with illustrative target tracking examples and real data collected from the surveillance radar.</div>

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Materials scientists from Ústí nad Labem and Dresden met in June of 2022 for the first joint PhD Conference on Material Science, with the special focus on biologization, nanotechnology and simulation. The conference aimed to encourage interdisciplinary exchange between Čzech and German research institutes and promote transnational cooperation on an international level along the Saxon- Čzech border. Due to the restrictions caused by the corona pandemic, several attempts were necessary before the conference, which was first planned in 2020, could finally take place for the first time in 2022. The conference could take place in presence, which was seen as a big plus by all participants, especially as it was the first meeting in this German - Čzech context for most of the participants. The attending scientists (about 60) met at the Institute of Material Science of TU Dresden in Germany for the first half of the week before the conference moved to the faculties of Science and Environment of the Jan Evangelista Purkyně University UJEP in Ústí nad Labem in Čzechia. The organized activities ranged from scientific presentations of current PhD projects and research topics, lab tours in the participating institutions, come-together events such as a guided tour at the dye collection of the TU Dresden and a hiking trip to Bohemian Switzerland. The conference was funded by INTERREG VA Saxony - Čzech Republic - a cooperation programme of the Elbe/Labe region. All participants - PhD students, scientists and staff members of the participating institutions - enjoyed this opportunity to build individual and new contacts, exchange information on current research topics and methods, find starting points for future collaborations between the different research areas and institutions and also discuss the similarities and differences between the German and Čzech research landscape. The purpose of this brochure is to present the institutions with their special topics and laboratories and to present current research topics - on the base of the presented PhD projects.:1 Introduction 2 1.1 Committees 5 2 Presentation of the participating institutes and chairs 5 2.1 Jan Evangelista Purkyně University in Ústí nad Labem 6 2.1.1 Faculty of Science 6 2.1.2 Faculty of Environment 12 2.2 Technische Universität Dresden 17 2.2.1 Institute of Material Science 17 2.3 Fraunhofer Institute for Ceramic Technologies and Systems IKTS 19 2.3.1 Department Bio- and Nanotechnology at IKTS 19 2.4 Institute for Complex Materials, Leibniz-IFW Dresden 21 2.5 TRANS³Net 22 3 Presentation of the PhD topics 23 3.1 Topic: BIOLOGIZATION 23 3.1.1 Ludovico Andrea Alberta: Exploring the effect of Cu additions on the mechanical behaviour of β-TiNb biomaterials 23 3.1.2 Franziska Alt: Formation of a microenvironment for directed differentiation of stem cells in a perfusion bioreactor 25 3.1.3 Dmitry Belyaev: Circular microfluidic systems for electro-chemical continuous monitoring of bio-chemicals in emulsion droplets 27 3.1.4 Constantin Ißleib: Dynamic osteoimmunological crosstalk in a bone replacement context 28 3.1.5 Adela Jagerová: Surface Modification by High-Energy Heavy-Ion Irradiation in Various Crystalline ZnO Facets 29 3.1.6 Nils Kaube: Bioinspired development of artificial enamel via in-situ nano-mineralization 30 3.1.7 Michaela Kocholata: Isolation and characterization of plant derived nanovesicles 30 3.1.8 Zuzana Nejedlá: Dendrimers as Drug Delivery System 31 3.1.9 Jacub Perner: Effect of cold plasma treatment of Poppy and Proso Millet seeds in plasma downer 32 3.1.10 Marina Roshchina: Development of new bacteria-killing coatings on beta-Ti-Nb alloy based on functional oxide nanotubular (ONT) layers 33 3.1.11 Muhammad Saqib: Algorithms and fluid-dynamic experimental platform for in vitro degradation studies of implant materials 34 3.1.12 Jacub Tolasz: Interaction of pollutants on nanoceria 35 3.1.13 Zuzana Žmudová: 3D spheroid culture for in vitro testing of nanoparticles 35 3.2 Topic: METROLOGY 37 3.2.1 Katrien Boonen: The potential of dendrochemistry and dendroecology in pollution research 37 3.2.2 Ivan Lopez Carasco: Development of immobilization protocols for Tro6 and Tro4 aptamers to be used in electrochemical biosensor 38 3.2.3 Jacub Hoskovec: Functionalized electrospun materials for selectvie capture of selected gases 39 3.2.4 Dominic Pilnaj: Applications of gas sensors for air-quality monitoring and identification of volatile organic compounds by GC-HRMS 39 3.2.5 Michaela Průšová: Prostat, Glioblastoma and Mammary carcinoma cells derived exosomes: Their isolation, characterization and loading with doxorubicin 40 3.2.6 Kateřina Přibylová: Preparation of nanostructured surfaces for CO2 Detection, Capture and Utilization 41 3.2.7 Michal Syrový: Chemical modification of PAN – based nanofibrous membranes prepared by electrospinning and their properties for CO2 capture potential 42 3.3 Topic: GEOLOGICAL/MATERIALS 43 3.3.1 Sabine Apelt: Using biomimicry to design anti-ice surfaces for air-water heat pumps 43 3.3.2 Jan Dočkal: Molecular dynamics of interfacial solution structure of alkali-halide electrolytes at graphens electrodes 47 3.3.3 Tereza Dušková: Metal complexes with polyfluorinated NHCs 48 3.3.4 Kristína Fiantoková: Obtaining of the active mass from the spent Li-Ion batteries 48 3.3.5 Stephanie Ihmann: Engineering of bio-based Building and Construction Materials 49 3.3.6 Sara Jalali: Degradable bone substitute materials with load-bearing properties - Fiber-strengthened silica 50 3.3.7 Pavel Kaule: Preparation of heteroborane derivatives for thin film deposition by the covalent bond formation 53 3.3.8 M. Kozakovic: The effect of primary and secondary flows on the homogenization process in a vertical bladed mixer 53 3.3.9 Pavlína Matysová: Molecular Simulation of Salt Hydrates 54 3.3.10 Viktorie Neubertová: Surface functionalization of Ti3C2T MXene for MRI contrast agent 55 3.3.11 Robert Ato Newton: Fuel characteristics of Miscanthus x giganteus biomass produced at the marginal and slightly contaminated by trace elements soils 55 3.3.12 Martin Otto: Bioresorbable Fe-based alloys processed via laser powder bed fusion 56 3.3.13 Petr Panuška: A millifluidic chip for cultivation of fish embryos and toxicity testing fabricated by 3D printing technology 59 3.3.14 David Poustka: Unlocking mass production of photocrosslinked chitosan nanofibers 60 3.3.15 Eliška Rezlerová: Adsorption and Diffusion of Short Hydrocarbons and Carbon Dioxide in Shale Organic Matter: Insights from Molecular Simulations 60 3.3.16 Stefan Weitz: Investigating the material hardness of mollusks shells in dry and wet states by microindentation 61

The U.S. shortage of qualified nursing teachers and researchers is affecting national health care outcomes. Methods such as fast-tracking Baccalaureate nurses into graduate programs and embedding leadership development early into nursing curricula have been proposed to address faculty and research shortages. Early interest in nursing research careers increases likelihood of enrollment in graduate education. One way undergraduate nursing students may develop an interest in research careers is through a mentored apprenticeship with research-active faculty. In this thesis, the author uses an autoethnography methodology to examine the benefits that a mentored research apprenticeship model brought to her undergraduate experience. Her experience incorporated a variety of roles in an adolescent intervention program with Dr. Anne Norris (PI) at the University of Central Florida College of Nursing. Several themes about the experience were defined in the results. Early research exposure that socializes a student to the nursing research world may provide a means for addressing the nursing faculty shortage. This socialization can generate interest in a research career and promote undergraduate students with the essential tools and insights needed to pursue this career pathway. However, findings from this study suggest a student-mentor relationship early in the undergraduate education experience is essential.

When an atomic nucleus undergoes fission, two fragments with different mass and kinetic energy are emitted. The highly unstable fission fragments (FFs) evaporate prompt neutrons soon after the nucleus splits. A precise measurement of both, the mass yield distribution of the FFs and the average prompt neutron emission, $\bar{\nu}$, is important not only for current nuclear technologies but also for the development of future technologies such as Generation IV nuclear power plants. Moreover, the experimental determination of the mass yield distributions, both pre- and post-neutron emission, is valuable for testing fission models. Additionally, a precise measurement of the average neutron multiplicity as a function of the FFs mass, <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?$%5Cbar%7B%5Cnu%7D(A)$" data-classname="equation" data-title="" />, is crucial in the understanding of how the excitation energy is shared between nascent FFs.  The VElocity foR DIrect particle identification spectrometer (VERDI) is designed to achieve pre- and post-fission mass distributions with resolutions between 1-2 u. VERDI is a double-energy double-velocity instrument that consists of two arms. On each arm is operated one Microchannel Plate detector (MCP) for the collection of the FFs start time and up to 32 Passive Implanted Planar Silicon (PIPS) detectors for the stop time and energy detection of the FFs. However, challenges in the experimental measurements with VERDI arise due to the high degree of ionization (plasma) in the detector material from the interaction with the FFs. The plasma causes a delay in the charge carriers' migration for the signal start, known as the plasma delay time effect (PDT). Furthermore, the recombination of charge carriers in the plasma causes a shrinking in the signal's height, known as pulse height defect (PHD). This phenomenon leads to inaccuracies in the measurement of FFs mass distributions and increased systematic uncertainties.  Previous studies on PDT and PHD have shown varying behaviors across different detector types, which motivated dedicated studies in the type of PIPS detectors used in VERDI. An experimental campaign to characterize the PDT and PHD in PIPS detectors was conducted in the LOHENGRIN recoil separator, which is part of the ILL nuclear facility in Grenoble, France. Measurements of FFs in a range of masses between 80 u and 149 u, with energies between 20 MeV to 110 MeV, were taken to fully characterize six PIPS detectors. The resulting PDT and PHD values were 1 ns to 4 ns and 2 MeV to 10 MeV respectively. The PDT and PHD exhibited consistent energy and mass dependencies across the detectors, which enables the possibility of an event-by-event correction of VERDI data. In this thesis, the basis for discussing the results of the studies of the PDT and PHD effects will be presented.

This item contains the agenda, minutes, and attachments for the Faculty Senate meeting on this date. There may be additional materials from the meeting available at the Faculty Center.

This item contains the agenda, minutes, and attachments for the Faculty Senate meeting on this date. There may be additional materials from the meeting available at the Faculty Center.

The multi-target tracking problem essentially involves the recursive joint estimation of the state of unknown and time-varying number of targets present in a tracking scene, given a series of observations. This problem becomes more challenging because the sequence of observations is noisy and can become corrupted due to miss-detections and false alarms/clutter. Additionally, the detected observations are indistinguishable from clutter. Furthermore, whether the target(s) of interest are point or extended (in terms of spatial extent) poses even more technical challenges. An approach known as random finite sets provides an elegant and rigorous framework for the handling of the multi-target tracking problem. With a random finite sets formulation, both the multi-target states and multi-target observations are modelled as finite set valued random variables, that is, random variables which are random in both the number of elements and the values of the elements themselves. Furthermore, compared to other approaches, the random finite sets approach possesses a desirable characteristic of being free of explicit data association prior to tracking. In addition, a framework is available for dealing with random finite sets and is known as finite sets statistics. In this thesis, advanced signal processing techniques are employed to provide enhancements to and develop new random finite sets based multi-target tracking algorithms for the tracking of both point and extended targets with the aim to improve tracking performance in cluttered environments. To this end, firstly, a new and efficient Kalman-gain aided sequential Monte Carlo probability hypothesis density (KG-SMC-PHD) filter and a cardinalised particle probability hypothesis density (KG-SMC-CPHD) filter are proposed. These filters employ the Kalman- gain approach during weight update to correct predicted particle states by minimising the mean square error between the estimated measurement and the actual measurement received at a given time in order to arrive at a more accurate posterior. This technique identifies and selects those particles belonging to a particular target from a given PHD for state correction during weight computation. The proposed SMC-CPHD filter provides a better estimate of the number of targets. Besides the improved tracking accuracy, fewer particles are required in the proposed approach. Simulation results confirm the improved tracking performance when evaluated with different measures. Secondly, the KG-SMC-(C)PHD filters are particle filter (PF) based and as with PFs, they require a process known as resampling to avoid the problem of degeneracy. This thesis proposes a new resampling scheme to address a problem with the systematic resampling method which causes a high tendency of resampling very low weight particles especially when a large number of resampled particles are required; which in turn affect state estimation. Thirdly, the KG-SMC-(C)PHD filters proposed in this thesis perform filtering and not tracking , that is, they provide only point estimates of target states but do not provide connected estimates of target trajectories from one time step to the next. A new post processing step using game theory as a solution to this filtering - tracking problem is proposed. This approach was named the GTDA method. This method was employed in the KG-SMC-(C)PHD filter as a post processing technique and was evaluated using both simulated and real data obtained using the NI-USRP software defined radio platform in a passive bi-static radar system. Lastly, a new technique for the joint tracking and labelling of multiple extended targets is proposed. To achieve multiple extended target tracking using this technique, models for the target measurement rate, kinematic component and target extension are defined and jointly propagated in time under the generalised labelled multi-Bernoulli (GLMB) filter framework. The GLMB filter is a random finite sets-based filter. In particular, a Poisson mixture variational Bayesian (PMVB) model is developed to simultaneously estimate the measurement rate of multiple extended targets and extended target extension was modelled using B-splines. The proposed method was evaluated with various performance metrics in order to demonstrate its effectiveness in tracking multiple extended targets.