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5,477 results on '"Felix, H"'

4. Multimodal deep learning approach to predicting neurological recovery from coma after cardiac arrest

Author

Krones, Felix H., Walker, Ben, Parsons, Guy, Lyons, Terry, and Mahdi, Adam

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

This work showcases our team's (The BEEGees) contributions to the 2023 George B. Moody PhysioNet Challenge. The aim was to predict neurological recovery from coma following cardiac arrest using clinical data and time-series such as multi-channel EEG and ECG signals. Our modelling approach is multimodal, based on two-dimensional spectrogram representations derived from numerous EEG channels, alongside the integration of clinical data and features extracted directly from EEG recordings. Our submitted model achieved a Challenge score of $0.53$ on the hidden test set for predictions made $72$ hours after return of spontaneous circulation. Our study shows the efficacy and limitations of employing transfer learning in medical classification. With regard to prospective implementation, our analysis reveals that the performance of the model is strongly linked to the selection of a decision threshold and exhibits strong variability across data splits., Comment: 5 figures, 2 tables

Published
2024

8. Self-Assembly of Core-Shell Hybrid Nanoparticles by Directional Crystallization of Grafted Polymers

Author

Nabiyan, Afshin, Muttathukattil, Aswathy, Tomazic, Federico, Pretzel, David, Schubert, Ulrich S., Engel, Michael, and Schacher, Felix H.

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Physics - Chemical Physics
Abstract

Nanoparticle self-assembly is an efficient bottom-up strategy for the creation of nanostructures. In the standard approach, ligands are grafted on the surfaces of nanoparticles to keep them separated and control interparticle interactions. Ligands then remain secondary and usually are not expected to order significantly during superstructure formation. Here, we investigate how ligands can play a more primary role in the formation of inorganic-organic hybrid materials. We graft poly(2-iso-propyl-2-oxazoline) (PiPrOx) as a crystallizable shell onto SiO$_2$ nanoparticles. By varying the PiPrOx grafting density, solution stability, and nanoparticle aggregation behavior can be controlled. Upon prolonged heating, anisotropic nanostructures form in conjunction with the crystallization of the ligands. Self-assembly of hybrid PiPrOx@SiO$_2$ (shell@core) nanoparticles proceeds in two steps: First, rapid formation of amorphous aggregates via gelation, mediated by the interaction between nanoparticles through grafted polymers; second, slow radial growth of fibers via directional crystallization, governed by the incorporation of crystalline ribbons formed from unbound polymers coupling to the grafted polymer shell. Our work reveals how crystallization-driven self-assembly of ligands can create intricate hybrid nanostructures., Comment: 12 pages, 5 figures

Published
2023
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9. Converting PROMIS®-29 v2.0 profile data to SF-36 physical and mental component summary scores in patients with cardiovascular disorders

Author

Gregor Liegl, Felix H. Fischer, Carl N. Martin, Maria Rönnefarth, Annelie Blumrich, Michael Ahmadi, Leif-Hendrik Boldt, Kai-Uwe Eckardt, Matthias Endres, Frank Edelmann, Holger Gerhardt, Ulrike Grittner, Arash Haghikia, Norbert Hübner, Ulf Landmesser, David Leistner, Knut Mai, Jil Kollmus-Heege, Dominik N. Müller, Christian H. Nolte, Sophie K. Piper, Kai M. Schmidt-Ott, Tobias Pischon, Simrit Rattan, Ira Rohrpasser-Napierkowski, Katharina Schönrath, Jeanette Schulz-Menger, Oliver Schweizerhof, Joachim Spranger, Joachim E. Weber, Martin Witzenrath, Sein Schmidt, and Matthias Rose

Subjects
PROMIS-29, SF-36, Health composite scores, Cardiovascular diseases, Mapping, Patient-reported outcomes, Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Background Health-related quality of life (HRQL) has become an important outcome parameter in cardiology. The MOS 36-ltem Short-Form Health Survey (SF-36) and the PROMIS-29 are two widely used generic measures providing composite HRQL scores. The domains of the SF-36, a well-established instrument utilized for several decades, can be aggregated to physical (PCS) and mental (MCS) component summary scores. Alternative scoring algorithms for correlated component scores (PCSc and MCSc) have also been suggested. The PROMIS-29 is a newer but increasingly used HRQL measure. Analogous to the SF-36, physical and mental health summary scores can be derived from PROMIS-29 domain scores, based on a correlated factor solution. So far, scores from the PROMIS-29 are not directly comparable to SF-36 results, complicating the aggregation of research findings. Thus, our aim was to provide algorithms to convert PROMIS-29 data to well-established SF-36 component summary scores. Methods Data from n = 662 participants of the Berlin Long-term Observation of Vascular Events (BeLOVE) study were used to estimate linear regression models with either PROMIS-29 domain scores or aggregated PROMIS-29 physical/mental health summary scores as predictors and SF-36 physical/mental component summary scores as outcomes. Data from a subsequent assessment point (n = 259) were used to evaluate the agreement between empirical and predicted SF-36 scores. Results PROMIS-29 domain scores as well as PROMIS-29 health summary scores showed high predictive value for PCS, PCSc, and MCSc (R2 ≥ 70%), and moderate predictive value for MCS (R2 = 57% and R2 = 40%, respectively). After applying the regression coefficients to new data, empirical and predicted SF-36 component summary scores were highly correlated (r > 0.8) for most models. Mean differences between empirical and predicted scores were negligible (|SMD|

Published
2024
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23. Impact of the Russia-Ukraine Conflict and Global Events on Beneficiaries of Microfinance Services: A Comparative Study of Romanian Small Companies

Author

Denisa HENEGAR and Felix H. ARION

Subjects
small companies, war impact, microfinance, crises situations, Agriculture, Agriculture (General), S1-972
Abstract

Recent global events, notably the COVID-19 pandemic, and the conflict between Russia and Ukraine leaded to unprecedented challenges for companies worldwide. This study examines the impact of the Russia-Ukraine conflict on small companies in agriculture, animal breeding, and the services sector in Romania. A survey was conducted among 110 beneficiaries of a microfinance company. The respondents evaluated the impact of the Russia-Ukraine war on income, expenses, and the economic situation using a set of 8 items, evaluated on a 5 points Likert scale type. The results revealed that the analyzed companies were most affected by the increase in fuel price and electricity price. Despite a moderate impact on income decrease, there were significant differences regarding the effect of the increase of interest rates, savings reduction, and liquidity reduction among different types of companies. Limited Liability Companies (L.L.C.s) were the most affected. Most companies are seeking solutions to reduce energy costs. These findings suggest a need for targeted interventions to mitigate the impact of crises situations on small companies.

Published
2024
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24. The neurocomputational link between defensive cardiac states and approach-avoidance arbitration under threat

Author

Felix H. Klaassen, Lycia D. de Voogd, Anneloes M. Hulsman, Jill X. O’Reilly, Floris Klumpers, Bernd Figner, and Karin Roelofs

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Avoidance, a hallmark of anxiety-related psychopathology, often comes at a cost; avoiding threat may forgo the possibility of a reward. Theories predict that optimal approach-avoidance arbitration depends on threat-induced psychophysiological states, like freezing-related bradycardia. Here we used model-based fMRI analyses to investigate whether and how bradycardia states are linked to the neurocomputational underpinnings of approach-avoidance arbitration under varying reward and threat magnitudes. We show that bradycardia states are associated with increased threat-induced avoidance and more pronounced reward-threat value comparison (i.e., a stronger tendency to approach vs. avoid when expected reward outweighs threat). An amygdala-striatal-prefrontal circuit supports approach-avoidance arbitration under threat, with specific involvement of the amygdala and dorsal anterior cingulate (dACC) in integrating reward-threat value and bradycardia states. These findings highlight the role of human freezing states in value-based decision making, relevant for optimal threat coping. They point to a specific role for amygdala/dACC in state-value integration under threat.

Published
2024
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28. The CONVINCE randomized trial found positive effects on quality of life for patients with chronic kidney disease treated with hemodiafiltration

Author

Rose, Matthias, Fischer, Felix H., Liegl, Gregor, Strippoli, Giovanni F.M., Hockham, Carina, Vernooij, Robin W.M., Barth, Claudia, Canaud, Bernard, Covic, Adrian, Cromm, Krister, Cucui, Andrea M., Davenport, Andrew, Fischer, Kathrin I., Hegbrant, Jörgen, Jaha, Hanna, Schappert, Anna, Török, Marietta, Woodward, Mark, Bots, Michiel L., and Blankestijn, Peter J.

Published
2024
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31. Comparison of Patient Health Questionnaire-9, Edinburgh Postnatal Depression Scale and Hospital Anxiety and Depression – Depression subscale scores by administration mode: An individual participant data differential item functioning meta-analysis

Author

Azar, Marleine, Bhandari, Parash Mani, Chiovitti, Matthew J., He, Chen, Imran, Mahrukh, Krishnan, Ankur, Negeri, Zelalem, Neupane, Dipika, Riehm, Kira E., Yan, Xin Wei, Kloda, Lorie A., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Al-Adawi, Samir, Alvarado, Rubén, Amtmann, Dagmar, Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R., Barnes, Jacqueline, Beck, Kevin R., Beck, Cheryl Tatano, Bernstein, Charles N., Bindt, Carola, Bombardier, Charles H., Boye, Birgitte, Büel-Drabe, Natalie, Buji, Ryna Imma, Bunevicius, Adomas, Butterworth, Peter, Can, Ceyhun, Carter, Gregory, Chagas, Marcos H., Chan, Juliana C.N., Chan, Lai Fong, Chen, Chih-Ken, Chibanda, Dixon, Chorwe-Sungani, Genesis, Clover, Kerrie, Conroy, Ronán M., Conway, Aaron, Conwell, Yeates, Correa, Humberto, Couto, Thiago Castro e, Cukor, Daniel, Daray, Federico M., de Man-van Ginkel, Janneke M., De Souza, Jennifer, Downing, Marina G., Eapen, Valsamma, Fann, Jesse R., Favez, Nicolas, Felice, Ethel, Fellmeth, Gracia, Ferentinos, Panagiotis P., Fernandes, Michelle, Field, Sally, Figueiredo, Barbara, Fischer, Felix H., Fisher, Jane R.W., Flint, Alastair J., Fujimori, Maiko, Fung, Daniel S.S., Gallagher, Pamela, Gandy, Milena, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J., Goodyear-Smith, Felicity, Grassi, Luigi, Green, Eric P., Greeno, Catherine G., Hall, Brian J., Hantsoo, Liisa, Haroz, Emily E., Härter, Martin, Hegerl, Ulrich, Helle, Nadine, Hernando, Asuncion, Hides, Leanne, Hobfoll, Stevan E., Honikman, Simone, Howard, Louise M., Hyphantis, Thomas, Iglesias-González, Maria, Inagaki, Masatoshi, Jenewein, Josef, Jeon, Hong Jin, Jetté, Nathalie, Julião, Miguel, Kettunen, Pirjo A., Khamseh, Mohammad E., Kiely, Kim M., Kim, Sung-Wan, Kjærgaard, Marie, Kohlhoff, Jane, Kohrt, Brandon A., König, Hans-Helmut, Kozinszky, Zoltán, Kwan, Yunxin, Lamers, Femke, Lara, María Asunción, Leonardou, Angeliki A., Levin-Aspenson, Holly F., Liu, Shen-Ing, Löbner, Margrit, Loosman, Wim L., Lotrakul, Manote, Loureiro, Sonia R., Love, Anthony W., Löwe, Bernd, Luitel, Nagendra P., Lund, Crick, Maes, Michael, Malt, Ulrik F., Marrie, Ruth Ann, Marsh, Laura, Martínez, Pablo, Marx, Brian P., Matsuoka, Yutaka, McGuire, Anthony, Mehnert, Anja, Michopoulos, Ioannis, Sidik, Sherina Mohd, Müller-Nordhorn, Jacqueline, Muramatsu, Kumiko, Radoš, Sandra Nakić, Navarrete, Laura, Nelson, Christian J., Ng, Chong Guan, Nishi, Daisuke, O'Donnell, Meaghan L., O'Rourke, Suzanne J., Osório, Flávia L., Pabst, Alexander, Pasco, Julie A., Pawlby, Susan J., Peceliuniene, Jurate, Pence, Brian W., Persoons, Philippe, Petersen, Inge, Picardi, Angelo, Ponsford, Jennie L., Pugh, Stephanie L., Pulido, Federico, Quinn, Terence J., Quispel, Chantal, Rathod, Sujit D., Reme, Silje E., Reuter, Katrin, Riedel-Heller, Steffi G., Rooney, Alasdair G., Santos, Iná S., Saracino, Rebecca M., Schellekens, Melanie P.J., Schwarzbold, Marcelo L., Cankorur, Vesile Senturk, Shaaban, Juwita, Sharp, Deborah J., Sharpe, Louise, Shinn, Eileen H., Sidebottom, Abbey, Simard, Sébastien, Singer, Susanne, Skalkidou, Alkistis, Smith-Nielsen, Johanne, Spangenberg, Lena, Stafford, Lesley, Stein, Alan, Stewart, Robert C., Strobel, Natalie A., Su, Kuan-Pin, Sultan, Serge, Sundström-Poromaa, Inger, Sung, Sharon C., Suzuki, Keiko, Tadinac, Meri, Tan, Pei Lin Lynnette, Tandon, S. Darius, Taylor-Rowan, Martin, Teixeira, Antonio L., Tendais, Iva, Tiringer, Istvan, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Tschorn, Mira, Turner, Alyna, Væver, Mette S., van der Feltz-Cornelis, Christina M., van Heyningen, Thandi, Vega-Dienstmaier, Johann M., Wagner, Michael, Wagner, Lynne I., Wang, Liang-Jen, Wang, Jian Li, Watson, David, Weyerer, Siegfried B., White, Jennifer, Whooley, Mary A., Wiese, Birgitt, Williams, Lana J., Winkley, Kirsty, Wynter, Karen, Yamada, Mitsuhiko, Yonkers, Kimberly A., Zeng, Qing Zhi, Zhang, Yuying, Harel, Daphna, Wu, Yin, Levis, Brooke, Fan, Suiqiong, Sun, Ying, Xu, Mingyao, Rice, Danielle B., Boruff, Jill, Markham, Sarah, Ioannidis, John P.A., Takwoingi, Yemisi, Patten, Scott B., Ziegelstein, Roy C., Cuijpers, Pim, Gilbody, Simon, Vigod, Simone, Akena, Dickens, Benedetti, Andrea, and Thombs, Brett D.

Published
2024
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38. Decentralised Intelligence, Surveillance, and Reconnaissance in Unknown Environments with Heterogeneous Multi-Robot Systems

Author

Lee, Ki Myung Brian, Kong, Felix H., Cannizzaro, Ricardo, Palmer, Jennifer L., Johnson, David, Yoo, Chanyeol, and Fitch, Robert

Subjects
Computer Science - Robotics
Abstract

We present the design and implementation of a decentralised, heterogeneous multi-robot system for performing intelligence, surveillance and reconnaissance (ISR) in an unknown environment. The team consists of functionally specialised robots that gather information and others that perform a mission-specific task, and is coordinated to achieve simultaneous exploration and exploitation in the unknown environment. We present a practical implementation of such a system, including decentralised inter-robot localisation, mapping, data fusion and coordination. The system is demonstrated in an efficient distributed simulation. We also describe an UAS platform for hardware experiments, and the ongoing progress., Comment: 7 pages, 6 figures. Presented at ICRA2021 Workshop on Robot Swarms in the Real World: From Design to Deployment

Published
2021

39. An Upper Confidence Bound for Simultaneous Exploration and Exploitation in Heterogeneous Multi-Robot Systems

Author

Lee, Ki Myung Brian, Kong, Felix H., Cannizzaro, Ricardo, Palmer, Jennifer L., Johnson, David, Yoo, Chanyeol, and Fitch, Robert

Subjects
Computer Science - Robotics
Abstract

Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We define this decomposition as the scout-task robot architecture and show how it avoids the need to explicitly balance exploration and exploitation~by permitting the system to do both simultaneously. The challenge is to guide exploration in a way that improves overall performance for time-limited tasks. We derive a novel upper confidence bound for simultaneous exploration and exploitation based on mutual information and present a general solution for scout-task coordination using decentralised Monte Carlo tree search. We evaluate the performance of our algorithms in a multi-drone surveillance scenario in which scout robots are equipped with low-resolution, long-range sensors and task robots capture detailed information using short-range sensors. The results address a new class of coordination problem for heterogeneous teams that has many practical applications., Comment: 7 pages, 5 figures. To appear in IEEE ICRA 2021

Published
2021

40. 3D Ensemble-Based Online Oceanic Flow Field Estimation for Underwater Glider Path Planning

Author

Kong, Felix H., To, K. Y. Cadmus, Brassington, Gary, Anstee, Stuart, and Fitch, Robert

Subjects
Computer Science - Robotics
Abstract

Estimating ocean flow fields in 3D is a critical step in enabling the reliable operation of underwater gliders and other small, low-powered autonomous marine vehicles. Existing methods produce depth-averaged 2D layers arranged at discrete vertical intervals, but this type of estimation can lead to severe navigation errors. Based on the observation that real-world ocean currents exhibit relatively low velocity vertical components, we propose an accurate 3D estimator that extends our previous work in estimating 2D flow fields as a linear combination of basis flows. The proposed algorithm uses data from ensemble forecasting to build a set of 3D basis flows, and then iteratively updates basis coefficients using point measurements of underwater currents. We report results from experiments using actual ensemble forecasts and synthetic measurements to compare the performance of our method to the direct 3D extension of the previous work. These results show that our method produces estimates with dramatically lower error metrics, with and without measurement noise., Comment: Submitted to IROS 2021

Published
2021

41. Estimation of Spatially-Correlated Ocean Currents from Ensemble Forecasts and Online Measurements

Author

To, K. Y. Cadmus, Kong, Felix H., Lee, Ki Myung Brian, Yoo, Chanyeol, Anstee, Stuart, and Fitch, Robert

Subjects
Computer Science - Robotics
Abstract

We present a method to estimate two-dimensional, time-invariant oceanic flow fields based on data from both ensemble forecasts and online measurements. Our method produces a realistic estimate in a computationally efficient manner suitable for use in marine robotics for path planning and related applications. We use kernel methods and singular value decomposition to find a compact model of the ensemble data that is represented as a linear combination of basis flow fields and that preserves the spatial correlations present in the data. Online measurements of ocean current, taken for example by marine robots, can then be incorporated using recursive Bayesian estimation. We provide computational analysis, performance comparisons with related methods, and demonstration with real-world ensemble data to show the computational efficiency and validity of our method. Possible applications in addition to path planning include active perception for model improvement through deliberate choice of measurement locations., Comment: 7 pages, 6 figures, accepted to IEEE ICRA 2021

Published
2021

42. On the Cauchy problems associated to a ZK-KP-type family equations with a transversal fractional dispersion

Author

P., Jorge Morales and M., Félix H. Soriano

Subjects
Mathematics - Analysis of PDEs, 35Q53, 35Q35, 35A01
Abstract

In this paper we examine the well-posedness and ill-posedeness of the Cauchy problems associated to a family equations of ZK-KP-type \[ \begin{cases} u_{t}=u_{xxx}-\mathscr{H}D_{x}^{\alpha}u_{yy}+uu_{x}, \cr u(0)=\psi \in Z \end{cases} \] in anisotropic Sobolev spaces, where $1\le \alpha \le 1$, $\mathscr{H}$ is the Hilbert transform and $D_{x}^{\alpha}$ is the fractional derivative, both with respect to $x$.

Published
2021

43. Customers’ Perception of Microfinance Services as a Tool for Rural Development: A Romanian Case Study

Author

Denisa Henegar, Garofița Loredana Ilieș, Iulia C. Mureșan, Andra Ramona Poruțiu, Iulia Diana Arion, and Felix H. Arion

Subjects
intangibles dimension, empathy and trust, social value creation, Agriculture (General), S1-972
Abstract

Microfinance institutions (MFIs) play a vital role in extending financial services to marginalized and underprivileged populations worldwide. While the focus of MFIs has traditionally been on providing financial products, recent research highlights the importance of intangible factors in shaping their success and sustainability. This research examines the influence of factors such as trust, empathy, organizational culture, and reputation on MFI performance. A structured questionnaire was developed, and data were collected from 110 clients. Statistical analysis, including Cronbach alpha, composite reliability, and exploratory factor analysis, was employed to assess the reliability, validity, and dimensionality of the collected data. Three dimensions of service quality were identified: empathy and assurance, trust, and intangibles. While gender differences in perception were observed, they were not statistically significant. However, significant differences were noted across age groups, educational levels, and types of businesses. Understanding and addressing factors related to trust, intangibles, and specific aspects of service satisfaction are crucial for enhancing client engagement and long-term success. By continuously striving to improve service quality, microfinance companies can strengthen client relationships and position themselves in such a way as to achieve sustainable impact and success in the microfinance landscape.

Published
2024
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48. Failed Rotator Cuff Surgery

Author

Hawkins, Barrett J., Savoie, Felix H., III, Milano, Giuseppe, editor, Grasso, Andrea, editor, Brzóska, Roman, editor, and Kovačič, Ladislav, editor

Published
2023
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