@article{PierobonSharshenova, author = {Pierobon, Chiara and Sharshenova, Aijan}, title = {German and Russian Public Diplomacy Efforts in Kyrgyzstan: A Comparative Study of Norm Entrepreneurship}, series = {Europe-Asia Studies}, volume = {75}, journal = {Europe-Asia Studies}, number = {8}, publisher = {Taylor \& Francis}, doi = {10.1080/09668136.2023.2213871}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87380}, pages = {1384 -- 1407}, abstract = {This article explores Russian and German public diplomacy efforts in Central Asia through the example of Kyrgyzstan. Due to a difficult economic and socio-political situation, Kyrgyzstan remains open to externally funded programmes and projects, including initiatives funded by foreign governments, and thus offers a unique environment for the study of public diplomacy. The article looks at transnational public diplomacy actors such as German political foundations and Russian-sponsored organisations active in the country. Overall, the article offers interesting insights into the nature and substance of the soft power policies pursued by Germany and Russia that are relevant for Kyrgyzstan and beyond.}, language = {en} } @article{Pierobon, author = {Pierobon, Chiara}, title = {European Union, civil society and local ownership in Kyrgyzstan: analysing patterns of adaptation, reinterpretation and contestation in the prevention of violent extremism (PVE)}, series = {Central Asian Survey}, volume = {41}, journal = {Central Asian Survey}, number = {4}, publisher = {Taylor \& Francis}, doi = {10.1080/02634937.2021.1905608}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87378}, pages = {752 -- 769}, abstract = {In the last decade, a growing body of literature has investigated the promotion of good governance, rule of law, democracy and human rights in Central Asia through funding from the European Union (EU). Most of this research has taken an EU-centric approach and is concerned with the supply side of external democratization. As a result, little is known about how EU projects are implemented on the ground and what EU-funded civil society organizations consider to be their priorities. This article investigates the agency of such organizations in Kyrgyzstan by focusing on their contribution to one particular EU instrument: the Instrument contributing to Stability and Peace (IcSP), and its programme: Strengthening Resilience to Violence and Extremism (STRIVE). The findings offer new insights into the processes of adaptation, reinterpretation and contestation through which EU-funded organizations exercise ownership while engaging in the prevention of violent extremism (PVE).}, language = {en} } @article{Pierobon, author = {Pierobon, Chiara}, title = {EU's support to civil society in Kazakhstan: A pilot evaluation of the social capital generated}, series = {Evaluation}, volume = {25}, journal = {Evaluation}, number = {2}, publisher = {Sage}, doi = {10.1177/1356389018796023}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87394}, pages = {207 -- 223}, abstract = {In the last decade, several studies have been devoted to the analysis of the EU's support to civil society abroad, but only recently has scholarly attention turned to Central Asia. Most of the research in this field has adopted a macro-level perspective, concerned with the supply side of external democratization, and has examined external assistance to civil society in terms of democratization ideal types and typologies. The main contribution of this study consists of a meso-level analysis of the outcomes of the EU's support to civil society in terms of production of social capital, conceived as the raw material of civil society itself. More precisely, the article evaluates the first wave of grants awarded to civil society organizations in Kazakhstan as part of two EU funding schemes—the European Instrument for Democracy and Human Rights and the Non-State Actors and Local Authorities in Development. The article sheds new light on the use of social capital and its two dimensions-structural and cognitive-as heuristic tools for evaluating civil society support programs.}, language = {en} } @inproceedings{BartlHausladenAsgharzadeetal., author = {Bartl, Mathias and Hausladen, Matthias and Asgharzade, Ali and Buchner, Philipp and Krysztof, Michal and Kn{\´a}pek, Alexandr and Bachmann, Michael and Schreiner, Rupert}, title = {Experimental method for investigation of the emission pattern characteristics of individual field emission tips using a CMOS image sensor}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, doi = {10.1109/IVNC65669.2025.11121040}, pages = {2}, abstract = {The emission pattern characteristics of individual silicon field emission tips were investigated using a CMOS image sensor. The quality of the image was improved by spatial and temporal averaging, so that individual emission centers could be identified and their temporal changes investigated. By mapping the emission current onto the image, the distribution of the current density on the image sensor could be calculated.}, language = {en} } @inproceedings{JannsenEhrnsperger, author = {Jannsen, Kai and Ehrnsperger, Matthias}, title = {Edge-efficient convolutional neural network for real-time doppler radar gesture recognition}, series = {2025 IEEE Radar Conference (RadarConf25), 4.-9. Oktober 2025, Krakow}, booktitle = {2025 IEEE Radar Conference (RadarConf25), 4.-9. Oktober 2025, Krakow}, publisher = {IEEE}, isbn = {979-8-3315-4433-1}, doi = {10.1109/RadarConf2559087.2025.11205096}, pages = {877 -- 881}, abstract = {Embedded gesture recognition using radar sensors enables intuitive and robust human-machine interfaces, which is appealing for automotive applications such as trunk opening via foot gesture. Designing a radar-based classifier that runs ondevice (edge) under strict resource constraints poses several challenges. The system must achieve real-time inference (e.g. under 200 ms) on a microcontroller unit (MCU), while maintaining high accuracy, and minimize false detections. This paper focuses on a binary classification task, while distinguishing a valid trunkopening "kick" gesture from other motions. Firstly, we evaluate classical machine learning (cML) models (Random Forests or support vector machines (SVMs)) for baseline performance, however they face difficulties with higher false positive rates and do not meet real time criteria. We then employ Convolutional Neural Networks (CNNs) and apply neural architecture search (NAS) to discover a compact CNN tailored for a 60 GHz Doppler radar dataset of 50 subjects, each with 10 leg gestures. By constraining network depth, filter sizes, and hyperparameters, NAS yields a small but accurate "edge" CNN that fits within the limited memory of a STM32 Nucleo F446RE microcontroller. The final model achieves 95.1 \% accuracy on the binary classification task with 96.6 \% precision and 2.17 \% false positive rate (FPR), and requires only 167.5 ms to run inference on the MCU.}, language = {en} } @inproceedings{BaranowskiZychlaKrysztofetal., author = {Baranowski, Kamil and Zychla, Michał and Krysztof, Michał and Ż{\´o}łtowski, Michał and Hausladen, Matthias and Schreiner, Rupert and Kn{\´a}pek, Aleksandr}, title = {Experimenal method for studying electron beams in gaseous environments using a CMOS image sensor}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, isbn = {979-8-3315-3705-0}, doi = {10.1109/IVNC65669.2025.11120851}, pages = {2}, abstract = {Detecting and analyzing electron beams in atmospheric conditions remains a significant challenge due to scattering and absorption of electrons by gas molecules. In this work, a novel approach using a CMOS image sensor for real-time electron beam detection after its transmission through air is presented. The setup enables visualization of beam divergence, emission profiles, and dynamic behavior under atmospheric pressure. Presented results demonstrate the potential of CMOS image sensor for electron beam analysis in gaseous environment.}, language = {en} } @inproceedings{AllahamBurdaKnapeketal., author = {Allaham, Mohammad M. and Burda, Daniel and Kn{\´a}pek, Alexandr and Krysztof, Michał and Baranowski, Kamil and Hausladen, Matthias and Schreiner, Rupert}, title = {Testing the performance of tungsten-graphite cathodes as MEMS Electron microscope electron source}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, doi = {10.1109/IVNC65669.2025.11121041}, pages = {2}, abstract = {This work presents preliminary results of the performance testing of exfoliated graphene layers deposited on the nanotip of a tungsten field emission cathode. The obtained tungsten-graphite cathodes were then operated in a 3D-printed MEMS electron microscope testing model for later applications. The results were promising, where a maximum emission current of 50.2 μA was obtained with an extraction voltage of 1 kV and anode voltage of 3 kV.}, language = {en} } @article{WolfgrammAbbSampetal., author = {Wolfgramm, Alex and Abb, Valerius and Samp, Artur and Samp, Rafal and Hoffmann, Jens Christoph and M{\"u}ller, Rainer and Kammler, Martin}, title = {Structural and functional evolution of HKUST-1 nanoparticles induced by ball milling}, series = {Next Materials}, volume = {10}, journal = {Next Materials}, publisher = {Elsevier}, doi = {10.1016/j.nxmate.2025.101544}, pages = {7}, abstract = {In this study, the effect of post-synthetic ball milling on the structural and functional properties of as-synthesized nanoparticles of the copper-based metal-organic framework (MOF) HKUST-1 was investigated for the first time. Nanoparticles were synthesized using sodium formate as a capping agent. The crystalline particles were subjected to a controlled ball milling process, which induced significant structural changes. Powder X-ray diffraction (PXRD) revealed a reduction in crystallite size from 91 nm to 21 nm and the introduction of microstrain, partially disrupting the MOF's long-range crystalline order, as evidenced by peak broadening and the diminished intensity of high-angle reflections. Particle morphology pre- and post-milling was further studied with scanning electron microscopy (SEM) imaging, verifying a narrow particle size distribution of ± 22 nm after milling. Fourier-transform infrared spectroscopy (FTIR) indicated protonation of carboxylate groups in the larger pores of the framework, likely due to moisture incorporation during milling. Brunauer-Emmett-Teller (BET) surface area analysis showed a substantial decrease in specific surface area from 521 m²/g to 226 m²/g, suggesting a partial collapse of the porous framework. We discuss the applicability of ball milling as a versatile means of post-synthetic approach to reduce MOF particle sizes, a key element in the preparation of MOF-based thin films using inks or polymers.}, language = {en} } @inproceedings{AsgharzadeBartlHausladenetal., author = {Asgharzade, Ali and Bartl, Mathias and Hausladen, Matthias and Chen, Yang and Buchner, Philipp and Edler, Simon and Bachmann, Michael and She, Juncong and Schreiner, Rupert}, title = {Investigation on the influence of internal voltage drops on the emission behavior of silicon field emission arrays using CMOS image sensor}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, doi = {10.1109/IVNC65669.2025.11120937}, pages = {2}, abstract = {In this paper we report on an improved measurement and analysis method for determining the emission current distribution of field emitter arrays with CMOS sensors. It can also be used for field emission arrays where not all surfaces of the emitters are at the same electrical potential (e.g. for p-doped Si tips, where a strong current saturation occurs). To demonstrate the functionality of this method, a n-doped field emission array was measured using a variable external series resistance. Brightness variations in emission spots were analyzed to re-calculate the known series resistances for comparison. The re-calculated value is in good agreement with the actual value of the resistance. This method offers a quantitative approach to assess internal voltage drop effects on field emission using optical readout}, language = {en} } @article{BuchnerHausladenBartletal., author = {Buchner, Philipp and Hausladen, Matthias and Bartl, Mathias and Bachmann, Michael and Schreiner, Rupert}, title = {High current field emission from Si nanowires on pillar structures}, series = {Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics}, volume = {42}, journal = {Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics}, number = {2}, publisher = {AIP}, issn = {2166-2754}, doi = {10.1116/6.0003384}, abstract = {We investigate the influence of the geometry and doping level on the performance of n-type silicon nanowire field emitters on silicon pillar structures. Therefore, multiple cathodes with 50 by 50 pillar arrays (diameter: 5 μm, height: 30 μm, spacing: 50 μm) were fabricated and measured in diode configuration. In the first experiment, we compared two geometry types using the same material. Geometry 1 is black silicon, which is a highly dense surface covering a forest of tightly spaced silicon needles resulting from self-masking during a plasma etching process of single crystal silicon. Geometry 2 are silicon nanowires, which are individual spaced-out nanowires in a crownlike shape resulting from a plasma etching process of single crystal silicon. In the second experiment, we compared two different silicon doping levels [n-type (P), 1-10 and <0.005 Ω cm] for the same geometry. The best performance was achieved with lower doped silicon nanowire samples, emitting 2 mA at an extraction voltage of 1 kV. The geometry/material combination with the best performance was used to assemble an integrated electron source. These electron sources were measured in a triode configuration and reached onset voltages of about 125 V and emission currents of 2.5 mA at extraction voltages of 400 V, while achieving electron transmission rates as high as 85.0\%.}, language = {en} } @inproceedings{BarikRawatMannaetal., author = {Barik, Ranjan Kumar and Rawat, Vikram Singh and Manna, Subhrajit and Bandyopadhyay, Ayan Kumar and Hausladen, Matthias and Asgharzade, Ali and Schreiner, Rupert}, title = {On Chip Electron Gun Design Using Silicon Tip Field Emitter Array}, series = {2025 IEEE Microwaves, Antennas, and Propagation Conference (MAPCON), 14-18. Dezember 2025, Kochi, India}, booktitle = {2025 IEEE Microwaves, Antennas, and Propagation Conference (MAPCON), 14-18. Dezember 2025, Kochi, India}, publisher = {IEEE}, isbn = {979-8-3315-3722-7}, doi = {10.1109/MAPCON65020.2025.11426578}, pages = {4}, abstract = {Silicon based silicon tip array emitter has developed at OTH Regensburg, Germany. This array emitter is the basis for development of a novel electron gun. This field emitter electron sources were fabricated using laser-micromachining technique followed by MEMS technology. In this work, the design and development of electron gun using complete silicon structure is reported. The goal of this work is to develop electron gun using less effort, easy and hassle free technique.}, language = {en} } @article{TanSchreinerHausladenetal., author = {Tan, Jing Jie and Schreiner, Rupert and Hausladen, Matthias and Asgharzade, Ali and Edler, Simon and Bartsch, Julian and Bachmann, Michael and Schels, Andreas and Kwan, Ban-Hoe and Ng, Danny Wee-Kiat and Hum, Yan-Chai}, title = {SiMiC: Context-aware silicon microstructure characterization using attention-based convolutional neural networks for field-emission tip analysis}, series = {Journal of Vacuum Science \& Technology B}, volume = {43}, journal = {Journal of Vacuum Science \& Technology B}, number = {6}, publisher = {AVS}, doi = {10.1116/6.0005068}, abstract = {Accurate characterization of silicon microstructures is essential for advancing microscale fabrication, quality control, and device performance. Traditional analysis using scanning electron microscopy (SEM) often requires labor-intensive, manual evaluation of feature geometry, limiting throughput and reproducibility. In this study, we propose SiMiC: Context-aware Silicon Microstructure Characterization Using Attention-based Convolutional Neural Networks for Field-Emission Tip Analysis. By leveraging deep learning, our approach efficiently extracts morphological features—such as size, shape, and apex curvature—from SEM images, significantly reducing human intervention while improving measurement consistency. A specialized dataset of silicon-based field-emitter tips was developed, and a customized convolutional neural network architecture incorporating attention mechanisms was trained for multiclass microstructure classification and dimensional prediction. Comparative analysis with classical image processing techniques demonstrates that SiMiC achieves high accuracy while maintaining interpretability. The proposed framework establishes a foundation for data-driven microstructure analysis directly linked to field-emission performance, opening avenues for correlating emitter geometry with emission behavior and guiding the design of optimized cold-cathode and SEM electron sources. The related dataset and algorithm repository that could serve as a baseline in this area can be found at https://research.jingjietan.com/?q=SIMIC.}, language = {en} }