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51. Learning Data Representations with Joint Diffusion Models

Author

Deja, Kamil, Trzcinski, Tomasz, and Tomczak, Jakub M.

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

Joint machine learning models that allow synthesizing and classifying data often offer uneven performance between those tasks or are unstable to train. In this work, we depart from a set of empirical observations that indicate the usefulness of internal representations built by contemporary deep diffusion-based generative models not only for generating but also predicting. We then propose to extend the vanilla diffusion model with a classifier that allows for stable joint end-to-end training with shared parameterization between those objectives. The resulting joint diffusion model outperforms recent state-of-the-art hybrid methods in terms of both classification and generation quality on all evaluated benchmarks. On top of our joint training approach, we present how we can directly benefit from shared generative and discriminative representations by introducing a method for visual counterfactual explanations., Comment: Code: https://github.com/KamilDeja/joint_diffusion

Published
2023

52. Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN

Author

Knigge, David M., Romero, David W., Gu, Albert, Gavves, Efstratios, Bekkers, Erik J., Tomczak, Jakub M., Hoogendoorn, Mark, and Sonke, Jan-Jakob

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Performant Convolutional Neural Network (CNN) architectures must be tailored to specific tasks in order to consider the length, resolution, and dimensionality of the input data. In this work, we tackle the need for problem-specific CNN architectures. We present the Continuous Convolutional Neural Network (CCNN): a single CNN able to process data of arbitrary resolution, dimensionality and length without any structural changes. Its key component are its continuous convolutional kernels which model long-range dependencies at every layer, and thus remove the need of current CNN architectures for task-dependent downsampling and depths. We showcase the generality of our method by using the same architecture for tasks on sequential ($1{\rm D}$), visual ($2{\rm D}$) and point-cloud ($3{\rm D}$) data. Our CCNN matches and often outperforms the current state-of-the-art across all tasks considered.

Published
2023

53. Emotional Determinants of Snack Consumption by Polish Consumers

Author

Jerzyk Ewa, Kaczmarek Mirosława, Mruk-Tomczak Dobrosława, and Gluza Natalia

Subjects
emotions, emotional eating, consumers’ behaviour, snacks, emocje, jedzenie emocjonalne, zachowania nabywców, przekąski, d91, e71, i12, p46, Social Sciences
Abstract

Emotions are the effect but also the cause of eating behaviors, including the purchase and consumption of snacks. As snacks become an increasingly prevalent segment of the food industry, their consumption has been linked to rising rates of overweight, obesity, and diet-related diseases. Understanding how emotional valence influences consumer attitudes and behaviors toward snacks is therefore crucial. This study explores the relationship between emotional eating and the propensity to consume unhealthy snacks, both sweet and salty. A survey of 707 representative participants revealed distinct emotional patterns in snack consumption, with choices significantly influenced by consumers' emotional states and personal preferences. Furthermore, individuals who frequently opted for unhealthy snacks typically exhibited poorer health and financial profiles.

Published
2024
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54. Spectral Analysis of Compass Errors Based on Fast Fourier Transform and Reduction Absolute Errors Using a Pass-Band Finite Impulse Response Filter

Author

Jaskólski Krzysztof, Czaplinski Wojciech, and Tomczak Arkadiusz

Subjects
inertial measurement unit, gyrocompass, fourier transform, finite impulse response filter, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

Compass errors can be regarded as a deviation of the vessel from the expected heading. Gyrocompass errors are randomly oscillating in nature, and it is difficult to describe the behaviour of a gyrocompass sufficiently accurately using mathematical relationships. Fibre-optic gyroscopes have no mechanical components, so the variability in their indications has a different nature; the computational processes and inertial sensors used cause certain types of errors. Thus far, compass studies have focused on presenting absolute errors in the time domain. However, compasses exhibit specific characteristics in the frequency domain that affect the amplitude of their deviation. This leads to the issue of identifying the oscillatory spectrum of errors in the operation of such compasses, and how this spectrum is impacted by the dynamic movement of the vessel. We attempt to assess this phenomenon by means of measurements taken on board the training and research vessel M/S NAWIGATOR XXI. The application of a fast Fourier transform allows for calculation of the absolute compass errors in the frequency domain, meaning that the frequency of occurrence of errors can be observed as noise against the background of the useful signal. Our results confirm the value of applying a finite impulse response filter, which is used to filter out noise in the form of absolute compass errors from the useful signal background. The convolution function proposed here considerably extends the possibilities for analysing the signal spectrum in the frequency domain when testing for the accuracy of compass device indications, and enables the elimination of random errors with a low frequency of occurrence..

Published
2024
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55. Construction and validation of a new Generational Time Perspective Questionnaire

Author

Celina Timoszyk-Tomczak and Piotr Próchniak

Subjects
Medicine, Science
Abstract

Abstract The article presents a proposal for a new diagnostic tool—the Generational Time Perspective Questionnaire. The Generational Time Perspective was defined as a cognitive-affective representation of the future in relation to the lives of a generation of people that the current generation of people will not live to see. This definition was the starting point for the construction of the Generational Time Perspective Questionnaire. The results of exploratory and confirmatory factor analyses indicate a two-factor structure of the Generational Time Perspective Questionnaire. The first factor includes items about the cognitive representation of the future in the next generations. The second factor describes negative emotions towards the problems that humanity may face in future generations. The reliability of the particular dimensions of the questionnaire is satisfactory. The Generational Time Perspective Questionnaire correlates with other constructs that diagnose different aspects of an individual’s temporality.

Published
2024
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56. Application of nitroxoline in urologic oncology – a review of evidence

Author

Wojciech Tomczak, Wojciech Krajewski, Joanna Chorbińska, Łukasz Nowak, Jan Łaszkiewicz, Katarzyna Grunwald, Szymon Pisarski, Adam Chełmoński, Bartosz Małkiewicz, and Tomasz Szydełko

Subjects
bladder cancer, prostate cancer, oncology, nitroxoline, Medicine
Abstract

The persistence of high incidence and mortality rates associated with urologic cancers underscores the urgent need for effective and safe treatments. Conventional chemotherapy regimens are often limited by their high toxicity, the cancer’s drug resistance, and the challenge of managing independently evolving multifocal spread. In this context, a repurposing strategy is particularly enticing. It allows for the introduction of a drug with a known safety profile, thus significantly reducing the costs and time necessary to introduce a new treatment. Nitroxoline (NIT), a drug with a well-established pharmacokinetic profile known for over 50 years and utilised in treating uncomplicated urinary tract infections, has recently garnered attention for its potential oncologic applications. Given the pharmacokinetic properties of NIT, our focus was specifically on urologic cancers in which its excretion profile is most advantageous. We examined all available studies, demonstrating significant effectiveness of NIT in inhibiting angiogenesis, tissue invasion, metastasis formation, and counteracting multidrug resistance. The efficacy and mechanism of action of NIT were found to vary across different cell lines. The findings to date are promising, suggesting that NIT or its derivatives could play a role in oncology, although further research is necessary to fully understand its potential and applicability in cancer treatment.

Published
2024
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57. Unconventional superconductivity without doping in infinite-layer nickelates under pressure

Author

Simone Di Cataldo, Paul Worm, Jan M. Tomczak, Liang Si, and Karsten Held

Subjects
Science
Abstract

Abstract High-temperature unconventional superconductivity quite generically emerges from doping a strongly correlated parent compound, often (close to) an antiferromagnetic insulator. The recently developed dynamical vertex approximation is a state-of-the-art technique that has quantitatively predicted the superconducting dome of nickelates. Here, we apply it to study the effect of pressure in the infinite-layer nickelate Sr x Pr1−x NiO2. We reproduce the increase of the critical temperature (T c ) under pressure found in experiment up to 12 GPa. According to our results, T c can be further increased with higher pressures. Even without Sr-doping the parent compound, PrNiO2, will become a high-temperature superconductor thanks to a strongly enhanced self-doping of the Ni $${d}_{{x}^{2}-{y}^{2}}$$ d x 2 − y 2 orbital under pressure. With a maximal T c of 100 K around 100 GPa, nickelate superconductors can reach that of the best cuprates.

Published
2024
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58. Validation and personality conditionings of the 3 × 2 achievement goal model in sport

Author

Maciej Tomczak, Paweł Kleka, Ewa Tomczak-Łukaszewska, Łukasz Bojkowski, and Małgorzata Walczak

Subjects
Medicine, Science
Abstract

Abstract Achievement goal models have been successfully applied in sport. In recent years, a framework that has emerged in this area is the 3 × 2 approach, being a natural evolution of years of research into the issue of achievement goals. Nevertheless, it is essential to further validate the abovementioned approach and explore its psychosocial context. Hence, the purpose of this study was to validate the latest 3 × 2 achievement goal model among high-performance and recreational athletes using the Polish version of the 3 × 2 Achievement Goal Questionnaire for Sport (3 × 2 AGQ-S), and to determine the relationship between personality traits and achievement goals of athletes. The study included 413 athletes, with M = 20.62 and SD = 2.72. The 3 × 2 AGQ-S was used to assess achievement goals, the Big Five personality traits were assessed using the IPIP-BFM-20 questionnaire. The model of the Polish version of the 3 × 2 AGQ-S achieved a satisfactory fit to the data (CFI = 0.940, TLI = 0.923, RMSEA = 0.086, SRMR = 0.061). Cronbach’s alphas for the subscales were: 0.77–0.96. High-performance athletes obtained higher achievement goals in task and self subscales than recreational athletes. Personality traits explained no more than 3% of variance of achievement goals in sport. Research involving the Polish version of the 3 × 2 AGQ-S supports the validity of the 3 × 2 model in sport among high-performance and recreational athletes. Nevertheless, the small relationships between the personality traits and achievement goals prompt searching for other psychosocial determinants of goals in sport.

Published
2024
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61. A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference

Author

van Krieken, Emile, Thanapalasingam, Thiviyan, Tomczak, Jakub M., van Harmelen, Frank, and Teije, Annette ten

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Logic in Computer Science, Statistics - Machine Learning
Abstract

We study the problem of combining neural networks with symbolic reasoning. Recently introduced frameworks for Probabilistic Neurosymbolic Learning (PNL), such as DeepProbLog, perform exponential-time exact inference, limiting the scalability of PNL solutions. We introduce Approximate Neurosymbolic Inference (A-NeSI): a new framework for PNL that uses neural networks for scalable approximate inference. A-NeSI 1) performs approximate inference in polynomial time without changing the semantics of probabilistic logics; 2) is trained using data generated by the background knowledge; 3) can generate symbolic explanations of predictions; and 4) can guarantee the satisfaction of logical constraints at test time, which is vital in safety-critical applications. Our experiments show that A-NeSI is the first end-to-end method to solve three neurosymbolic tasks with exponential combinatorial scaling. Finally, our experiments show that A-NeSI achieves explainability and safety without a penalty in performance., Comment: Accepted to NeurIPS 2023. 13 pages, 11 appendix pages, 7 figures

Published
2022

62. Artin's Conjecture for Abelian Varieties with Frobenius Condition

Author

Hess, Florian and Tomczak, Leonard

Subjects
Mathematics - Number Theory, 11R45, 11G05, 11G10
Abstract

$A$ be an abelian variety over a number field $K$ of dimension $r$, $a_1, \dots, a_g \in A(K)$ and $F/K$ a finite Galois extension. We consider the density of primes $\frak p$ of $K$ such that the quotient $\bar{A}(k({\frak p}))/\langle \bar{a}_1,\dots,\bar{a}_g\rangle$ has at most $2r-1$ cyclic components and $\frak p$ satisfies a Frobenius condition with respect to $F/K$, where $\bar{A}$ is the reduction of $A$ modulo $\frak p$, $k(\frak p)$ is the residue class field of $\frak p$ and $\langle \bar{a}_1,\dots,\bar{a}_g\rangle$ is the subgroup generated by the reductions $\bar{a}_1,\dots,\bar{a}_g$. We develop a general framework to prove the existence of the density under the Generalized Riemann Hypothesis.

Published
2022

63. HIKE, High Intensity Kaon Experiments at the CERN SPS

Author

Gil, E. Cortina, Jerhot, J., Lurkin, N., Numao, T., Velghe, B., Wong, V. W. S., Bryman, D., Bician, L., Hives, Z., Husek, T., Kampf, K., Koval, M., Akmete, A. T., Aliberti, R., Büscher, V., Di Lella, L., Doble, N., Peruzzo, L., Schott, M., Wahl, H., Wanke, R., Döbrich, B., Montalto, L., Rinaldi, D., Dettori, F., Cardini, A., Lai, A., Bomben, L., Carsi, S., Prest, M., Selmi, A., Lezzani, G., Monti-Guarnieri, P., Perna, L., Dalpiaz, P., Guidi, V., Mazzolari, A., Neri, I., Petrucci, F., Soldani, M., Bandiera, L., Ramusino, A. Cotta, Gianoli, A., Romagnoni, M., Sytov, A., Lenti, M., Panichi, I., Ruggiero, G., Bizzeti, A., Bucci, F., Antonelli, A., Di Meco, E., Lanfranchi, G., Martellotti, S., Martini, M., Moulson, M., Paesani, D., Sarra, I., Spadaro, T., Tinti, G., Vallazza, E., Ambrosino, F., Giordano, R., Massarotti, P., Napolitano, M., Saracino, G., Di Donato, C., D'Ambrosio, G., D'Errico, M., Mirra, M., Neshatpour, S., Fiorenza, R., Rosa, I., De Salvador, D., Sgarbossa, F., Anzivino, G., Germani, S., Volpe, R., Cenci, P., Cutini, S., Duk, V., Lubrano, P., Pepe, M., Piccini, M., Costantini, F., Donati, S., Giorgi, M., Giudici, S., Lamanna, G., Pedreschi, E., Pinzino, J., Sozzi, M., Fantechi, R., Giusti, V., Spinella, F., Mannelli, I., Raggi, M., Biagioni, A., Cretaro, P., Frezza, O., Cicero, F. Lo, Lonardo, A., Turisini, M., Vicini, P., Ammendola, R., Bonaiuto, V., Fucci, A., Salamon, A., Sargeni, F., Arcidiacono, R., Bloch-Devaux, B., Menichetti, E., Migliore, E., Biino, C., Marchetto, F., Baigarashev, D., Kambar, Y., Kereibay, D., Mukhamejanov, Y., Sakhiyev, S., Olvera, A. Briano, Engelfried, J., Estrada-Tristan, N., Piandani, R., Santos, M. A. Reyes, Rivera, K. A. Rodriguez, Boboc, P. C., Bragadireanu, A. M., Ghinescu, S. A., Hutanu, O. E., Blazek, T., Cerny, V., Kleimenova, A., Kucerova, Z., Santos, D. Martinez, Prouve, C., Boretto, M., Brizioli, F., Ceccucci, A., Corvino, M., Danielsson, H., Duval, F., Gamberini, E., Guida, R., Holzer, E. B., Jenninger, B., Miotto, G. Lehmann, Lichard, P., Massri, K., Minucci, E., Perrin-Terrin, M., Ryjov, V., Swallow, J., Van Dijk, M., Zamkovsky, M., Marchevski, R., Gerbershagen, A., Fry, J. R., Gonnella, F., Goudzovski, E., Henshaw, J., Kenworthy, C., Lazzeroni, C., Parkinson, C., Romano, A., Sanders, J., Shaikhiev, A., Tomczak, A., Heath, H., Britton, D., Norton, A., Protopopescu, D., Dainton, J. B., Jones, R. W. L., De Santo, A., Salvatore, F., Cooper, P., Coward, D., and Rubin, P.

Subjects
High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

A timely and long-term programme of kaon decay measurements at a new level of precision is presented, leveraging the capabilities of the CERN Super Proton Synchrotron (SPS). The proposed programme is firmly anchored on the experience built up studying kaon decays at the SPS over the past four decades, and includes rare processes, CP violation, dark sectors, symmetry tests and other tests of the Standard Model. The experimental programme is based on a staged approach involving experiments with charged and neutral kaon beams, as well as operation in beam-dump mode. The various phases will rely on a common infrastructure and set of detectors., Comment: Letter of Intent submitted to CERN SPSC. Address all correspondence to hike-eb@cern.ch

Published
2022

64. Annotation of Soft Onsets in String Ensemble Recordings

Author

Tomczak, Maciej, Li, Min Susan, Bradbury, Adrian, Elliott, Mark, Stables, Ryan, Witek, Maria, Goodman, Tom, Abdlkarim, Diar, Di Luca, Massimiliano, Wing, Alan, and Hockman, Jason

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Information Retrieval, Computer Science - Sound
Abstract

Onset detection is the process of identifying the start points of musical note events within an audio recording. While the detection of percussive onsets is often considered a solved problem, soft onsets-as found in string instrument recordings-still pose a significant challenge for state-of-the-art algorithms. The problem is further exacerbated by a paucity of data containing expert annotations and research related to best practices for curating soft onset annotations for string instruments. To this end, we investigate inter-annotator agreement between 24 participants, extend an algorithm for determining the most consistent annotator, and compare the performance of human annotators and state-of-the-art onset detection algorithms. Experimental results reveal a positive trend between musical experience and both inter-annotator agreement and performance in comparison with automated systems. Additionally, onsets produced by changes in fingering as well as those from the cello were found to be particularly challenging for both human annotators and automatic approaches. To promote research in best practices for annotation of soft onsets, we have made all experimental data associated with this study publicly available. In addition, we publish the ARME Virtuoso Strings dataset, consisting of over 144 recordings of professional performances of an excerpt from Haydn's string quartet Op. 74 No. 1 Finale, each with corresponding individual instrumental onset annotations.

Published
2022

65. What can we learn about a generated image corrupting its latent representation?

Author

Tomczak, Agnieszka, Gupta, Aarushi, Ilic, Slobodan, Navab, Nassir, and Albarqouni, Shadi

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Generative adversarial networks (GANs) offer an effective solution to the image-to-image translation problem, thereby allowing for new possibilities in medical imaging. They can translate images from one imaging modality to another at a low cost. For unpaired datasets, they rely mostly on cycle loss. Despite its effectiveness in learning the underlying data distribution, it can lead to a discrepancy between input and output data. The purpose of this work is to investigate the hypothesis that we can predict image quality based on its latent representation in the GANs bottleneck. We achieve this by corrupting the latent representation with noise and generating multiple outputs. The degree of differences between them is interpreted as the strength of the representation: the more robust the latent representation, the fewer changes in the output image the corruption causes. Our results demonstrate that our proposed method has the ability to i) predict uncertain parts of synthesized images, and ii) identify samples that may not be reliable for downstream tasks, e.g., liver segmentation task.

Published
2022

66. Revealing a hidden conducting state by manipulating the intracellular domains in KV10.1 exposes the coupling between two gating mechanisms

Author

Reham Abdelaziz, Adam P Tomczak, Andreas Neef, and Luis A Pardo

Subjects
potassium channels, voltage-dependent gating, KCNH1, Kv10.1, Medicine, Science, Biology (General), QH301-705.5
Abstract

The KCNH family of potassium channels serves relevant physiological functions in both excitable and non-excitable cells, reflected in the massive consequences of mutations or pharmacological manipulation of their function. This group of channels shares structural homology with other voltage-gated K+ channels, but the mechanisms of gating in this family show significant differences with respect to the canonical electromechanical coupling in these molecules. In particular, the large intracellular domains of KCNH channels play a crucial role in gating that is still only partly understood. Using KCNH1(KV10.1) as a model, we have characterized the behavior of a series of modified channels that could not be explained by the current models. With electrophysiological and biochemical methods combined with mathematical modeling, we show that the uncovering of an open state can explain the behavior of the mutants. This open state, which is not detectable in wild-type channels, appears to lack the rapid flicker block of the conventional open state. Because it is accessed from deep closed states, it elucidates intermediate gating events well ahead of channel opening in the wild type. This allowed us to study gating steps prior to opening, which, for example, explain the mechanism of gating inhibition by Ca2+-Calmodulin and generate a model that describes the characteristic features of KCNH channels gating.

Published
2024
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67. Temperament structures and the effectiveness of individual play in football

Author

Łukasz Bojkowski and Maciej Tomczak

Subjects
offensive effectiveness, defensive effectiveness, comprehensive effectiveness, temperament, temperament structures, Psychology, BF1-990
Abstract

BackgroundRegulatory Theory of Temperament distinguishes two traits involving the time course of responses and four relating to how energy is distributed and stored. This theory enables the presentation of entire structures of temperament traits and it is relevant for assessing an individual’s ability to process stimulation and influence their performance during competitions. In our cross-sectional study, these structures are examined in relation to the offensive, defensive, and comprehensive effectiveness of an individual player’s actions.MethodsThe study included 91 football players aged between 20 and 31 years, who had approximately 10 years of training experience. The Formal Characteristics of Behavior – Temperament Inventory was utilized to assess temperamental traits, while a simulation game was employed to evaluate the effectiveness of each individual player’s actions.ResultsResearch demonstrated that football players possessing a temperament structure that is closely aligned harmonized structure with a high capacity to process stimulation showed higher levels of individual efficacy in attack, defence, and comprehensive effectiveness of performance compared to football players with a harmonized temperament structure but a low capacity to process stimulation.ConclusionThe obtained result emphasises the significance of specific temperament structures in terms of matching the individual’s stimulation levels and the their ability to process it.

Published
2024
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68. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Author

Astrid Marchal, Elizabeth T. Cirulli, Iva Neveux, Evangelos Bellos, Ryan S. Thwaites, Kelly M. Schiabor Barrett, Yu Zhang, Ivana Nemes-Bokun, Mariya Kalinova, Andrew Catchpole, Stuart G. Tangye, András N. Spaan, Justin B. Lack, Jade Ghosn, Charles Burdet, Guy Gorochov, Florence Tubach, Pierre Hausfater, Clifton L. Dalgard, Shen-Ying Zhang, Qian Zhang, Christopher Chiu, Jacques Fellay, Joseph J. Grzymski, Vanessa Sancho-Shimizu, Laurent Abel, Jean-Laurent Casanova, Aurélie Cobat, Alexandre Bolze, Alessandro Aiuti, Saleh Al-Muhsen, Fahd Al-Mulla, Ali Amara, Mark S. Anderson, Evangelos Andreakos, Andrés A. Arias, Lisa M. Arkin, Hagit Baris Feldman, Paul Bastard, Alexandre Belot, Catherine M. Biggs, Dusan Bogunovic, Anastasiia Bondarenko, Alessandro Borghesi, Ahmed A. Bousfiha, Petter Brodin, Yenan Bryceson, Manish J. Butte, Giorgio Casari, John Christodoulou, Roger Colobran, Antonio Condino-Neto, Stefan N. Constantinescu, Megan A. Cooper, Murkesh Desai, Beth A. Drolet, Xavier Duval, Jamila El Baghdadi, Philippine Eloy, Sara Espinosa-Padilla, Carlos Flores, José Luis Franco, Antoine Froidure, Peter K. Gregersen, Bodo Grimbacher, Filomeen Haerynck, David Hagin, Rabih Halwani, Lennart Hammarström, James R. Heath, Elena W.Y. Hsieh, Eystein Husebye, Kohsuke Imai, Yuval Itan, Emmanuelle Jouanguy, Elżbieta Kaja, Timokratis Karamitros, Kai Kisand, Cheng-Lung Ku, Yu-Lung Lau, Yun Ling, Carrie L. Lucas, Tom Maniatis, Davood Mansouri, László Maródi, France Mentré, Isabelle Meyts, Joshua D. Milner, Kristina Mironska, Trine H. Mogensen, Tomohiro Morio, Lisa F.P. Ng, Luigi D. Notarangelo, Antonio Novelli, Giuseppe Novelli, Cliona O'Farrelly, Satoshi Okada, Keisuke Okamoto, Tayfun Ozcelik, Qiang Pan-Hammarström, Jean W. Pape, Rebeca Perez de Diego, Jordi Perez-Tur, David S. Perlin, Graziano Pesole, Anna M. Planas, Carolina Prando, Aurora Pujol, Anne Puel, Lluis Quintana-Murci, Sathishkumar Ramaswamy, Laurent Renia, Igor Resnick, Carlos Rodríguez-Gallego, Anna Sediva, Mikko R.J. Seppänen, Mohammad Shahrooei, Anna Shcherbina, Ondrej Slaby, Andrew L. Snow, Pere Soler-Palacín, Vassili Soumelis, Ivan Tancevski, Ahmad Abou Tayoun, Şehime Gülsün Temel, Christian Thorball, Pierre Tiberghien, Sophie Trouillet-Assant, Stuart E. Turvey, K. M. Furkan Uddin, Mohammed J. Uddin, Diederik van de Beek, Donald C. Vinh, Horst von Bernuth, Joost Wauters, Mayana Zatz, Pawel Zawadzki, Serge Bureau, Yannick Vacher, Anne Gysembergh-Houal, Lauren Demerville, Abla Benleulmi-Chaachoua, Sebastien Abad, Radhiya Abassi, Abdelrafie Abdellaoui, Abdelkrim Abdelmalek, Hendy Abdoul, Helene Abergel, Fariza Abeud, Sophie Abgrall, Noemie Abisror, Marylise Adechian, Nordine Aderdour, Hakeem Farid Admane, Frederic Adnet, Sara Afritt, Helene Agostini, Claire Aguilar, Sophie Agut, Tommaso Francesco Aiello, Marc Ait Kaci, Hafid Ait Oufella, Gokula Ajeenthiravasan, Virginie Alauzy, Fanny Alby-Laurent, Lucie Allard, Marie-Alexandra Alyanakian, Blanca Amador Borrero, Sabrina Amam, Lucile Amrouche, Marc Andronikof, Dany Anglicheau, Nadia Anguel, Djillali Annane, Mohammed Aounzou, Caroline Aparicio, Gladys Aratus, Jean-Benoit Arlet, Jeremy Arzoine, Elisabeth Aslangul, Mona Assefi, Adeline Aubry, Laetitia Audiffred, Etienne Audureau, Christelle Nathalie Auger, Jean-Charles Auregan, Celine Awotar, Sonia Ayllon Milla, Delphine Azan, Laurene Azemar, Billal Azzouguen, Marwa Bachir Elrufaai, Aïda Badsi, Prissile Bakouboula, Coline Balcerowiak, Fanta Balde, Elodie Baldivia, Eliane-Flore Bangamingo, Amandine Baptiste, Fanny Baran-Marszak, Caroline Barau, Nathalie Barget, Flore Baronnet, Romain Barthelemy, Jean-Luc Baudel, Camille Baudry, Elodie Baudry, Laurent Beaugerie, Adel Belamri, Nicolas Belaube, Rhida Belilita, Pierre Bellassen, Rawan Belmokhtar, Isabel Beltran, Ruben Benainous, Mourad Benallaoua, Robert Benamouzig, Amélie Benbara, Jaouad Benhida, Anis Benkhelouf, Jihene Benlagha, Chahinez Benmostafa, Skander Benothmane, Miassa Bentifraouine, Laurence Berard, Quentin Bernier, Enora Berti, Astrid Bertier, Laure Berton, Simon Bessis, Alexandra Beurton, Celine Bianco, Clara Bianquis, Frank Bidar, Philippe Blanche, Clarisse Blayau, Alexandre Bleibtreu, Emmanuelle Blin, Coralie Bloch-Queyrat, Marie-Christophe Boissier, Diane Bollens, Marion Bolzoni, Rudy pierre Bompard, Nicolas Bonnet, Justine Bonnouvrier, Shirmonecrystal Botha, Wissam Boucenna, Fatiha Bouchama, Olivier Bouchaud, Hanane Bouchghoul, Taoueslylia Boudjebla, Noel Boudjema, Catherine Bouffard, Adrien Bougle, Meriem Bouguerra, Leila Bouras, Agnes Bourcier, Anne Bourgarit Durand, Anne Bourrier, Fabrice Bouscarat, Diane Bouvry, Nesrine Bouziri, Ons Bouzrara, Sarah Bribier, Delphine Brugier, Melanie Brunel, Eida Bui, Anne Buisson, Iryna Bukreyeva, Côme Bureau, Jacques Cadranel, Johann Cailhol, Ruxandra Calin, Clara Campos Vega, Pauline Canavaggio, Marta Cancella, Delphine Cantin, Albert Cao, Lionel Carbillon, Nicolas Carlier, Clementine Cassard, Guylaine Castor, Marion Cauchy, Olivier Cha, Benjamin Chaigne, Salima Challal, Karine Champion, Patrick Chariot, Julie Chas, Simon Chauveau, Anthony Chauvin, Clement Chauvin, Nathalie Chavarot, Kamélia Chebbout, Mustapha Cherai, Ilaria Cherubini, Amelie Chevalier, Thibault Chiarabini, Thierry Chinet, Richard Chocron, Pascaline Choinier, Juliette Chommeloux, Christophe Choquet, Laure Choupeaux, Benjamin Chousterman, Dragosmarius Ciocan, Ada Clarke, Gaëlle Clavere, Florian Clavier, Karine Clement, Sebastien Clerc, Yves Cohen, Fleur Cohen, Adrien Cohen, Audrey Coilly, Hester Colboc, Pauline Colin, Magalie Collet, Chloé Comarmond, Emeline Combacon, Alain Combes, Celine Comparon, Jean-Michel Constantin, Hugues Cordel, Anne-Gael Cordier, Adrien Costantini, Nathalie Costedoat Chalumeau, Camille Couffignal, Doriane Coupeau, Alain Creange, Yannie Cuvillier Lamarre, Charlène Da Silveira, Sandrine Dautheville Guibal El Kayani, Nathalie De Castro, Yann De Rycke, Lucie Del Pozo, Quentin Delannoy, Mathieu Delay, Robin Deleris, Juliette Delforge, Laëtitia Delphine, Noemie Demare, Sophie Demeret, Alexandre Demoule, Aurore Deniau, François Depret, Sophie Derolez, Ouda Derradji, Nawal Derridj, Vincent Descamps, Lydia Deschamps, Celine Desconclois, Cyrielle Desnos, Karine Desongins, Robin Dhote, Benjamin Diallo, Morgane Didier, Myriam Diemer, Stephane Diez, Juliette Djadi-Prat, Fatima-Zohra Djamouri Monnory, Siham Djebara, Naoual Djebra, Minette Djietcheu, Hadjer Djillali, Nouara Djouadi, Severine Donneger, Catarina Dos Santos, Nathalie Dournon, Martin Dres, Laura Droctove, Marie Drogrey, Margot Dropy, Elodie Drouet, Valérie Dubosq, Evelyne Dubreucq, Estelle Dubus, Boris Duchemann, Thibault Duchenoy, Emmanuel Dudoignon, Romain Dufau, Florence Dumas, Clara Duran, Emmanuelle Duron, Antoine Durrbach, Claudine Duvivier, Nathan Ebstein, Jihane El Khalifa, Alexandre Elabbadi, Caroline Elie, Gabriel Ernotte, Anne Esling, Martin Etienne, Xavier Eyer, Muriel Sarah Fartoukh, Takoua Fayali, Marion Fermaut, Arianna Fiorentino, Souha Fliss, Marie-Céline Fournier, Benjamin Fournier, Hélène Francois, Olivia Freynet, Yvann Frigout, Isaure Fromont, Axelle Fuentes, Thomas Furet, Joris Galand, Marc Garnier, Agnes Gaubert, Stéphane Gaudry, Samuel Gaugain, Damien Gauthier, Maxime Gautier, Sophie Georgin-Lavialle, Daniela Geromin, Mohamed Ghalayini, Bijan Ghaleh, Myriam Ghezal, Aude Gibelin, Linda Gimeno, Benoit Girard, Bénédicte Giroux Leprieur, Doryan Gomes, Elisabete Gomes-Pires, Anne Gouge, Amel Gouja, Helene Goulet, Sylvain Goupil, Jeanne Goupil De Bouille, Julien Gras, Segolene Greffe, Lamiae Grimaldi, Paul Guedeney, Bertrand Guidet, Matthias Guillo, Mariechristelle Gulczynski, Tassadit Hadjam, Didier Haguenauer, Soumeya Hammal, Nadjib Hammoudi, Olivier Hanon, Anarole Harrois, Coraline Hautem, Guillaume Hekimian, Nicholas Heming, Olivier Hermine, Sylvie Ho, Marie Houllier, Benjamin Huot, Tessa Huscenot, Wafa Ibn Saied, Ghilas Ikherbane, Meriem Imarazene, Patrick Ingiliz, Lina Iratni, Stephane Jaureguiberry, Jean-Francois Jean-Marc, Deleena Jeyarajasingham, Pauline Jouany, Veronique Jouis, Clement Jourdaine, Ouifiya Kafif, Rim Kallala, Sandrine Katsahian, Lilit Kelesyan, Vixra Keo, Flora Ketz, Warda Khamis, Enfel Khelili, Mehdi Khellaf, Christy Gaëlla Kotokpo Youkou, Ilias Kounis, Gaelle Kpalma, Jessica Krause, Vincent Labbe, Karine Lacombe, Jean-Marc Lacorte, Anne Gaelle Lafont, Emmanuel Lafont, Lynda Lagha, Lionel Lamhaut, Aymeric Lancelot, Cecilia Landman, Fanny Lanternier, Cecile Larcheveque, Caroline Lascoux Combe, Ludovic Lassel, Benjamin Laverdant, Christophe Lavergne, Jean-Rémi Lavillegrand, Pompilia Lazureanu, Loïc Le Guennec, Lamia Leberre, Claire Leblanc, Marion Leboyer, Francois Lecomte, Marine Lecorre, Romain Leenhardt, Marylou Lefebvre, Bénédicte Lefebvre, Paul Legendre, Anne Leger, Laurence Legros, Justyna Legrosse, Sébastien Lehuunghia, Julien Lemarec, Jeremie Leporrier-Ext, Manon Lesein, Hubert Lesur, Vincent Levy, Albert Levy, Edwige Lopes, Amanda Lopes, Vanessa Lopez, Julien Lopinto, Olivier Lortholary, Badr Louadah, Bénédicte Loze, Marie-Laure Lucas, Axelle Lucasamichi, Liem Binh Luong, Arouna Magazimama-Ext, David Maingret, Lakhdar Mameri, Philippe Manivet, Cylia Mansouri, Estelle Marcault, Jonathan Marey, Nathalie Marin, Clémence Marois, Olivier Martin, Lou Martineau, Cannelle Martinez-Lopez, Pierre Martyniuck, Pauline Mary De Farcy, Nessrine Marzouk, Rafik Masmoudi, Alexandre Mebazaa, Frédéric Mechai, Fabio Mecozzi, Chamseddine Mediouni, Bruno Megarbane, Mohamed Meghadecha, Élodie Mejean, Arsene Mekinian, Nour Mekki Abdelhadi, Rania Mekni, Thinhinan Sabrina Meliti, Breno Melo Lima, Paris Meng, Soraya Merbah, Fadhila Messani, Yasmine Messaoudi, Baboo-Irwinsingh Mewasing, Lydia Meziane, Carole Michelot-Burger, Françoise Mignot, Fadi Hillary Minka, Makoto Miyara, Pierre Moine, Jean-Michel Molina, Anaïs Montegnies-Boulet, Alexandra Monti, Claire Montlahuc, Anne-Lise Montout, Alexandre Moores, Caroline Morbieu, Helene Mortelette, Stéphane Mouly, Rosita Muzaffar, Cherifa Iness Nacerddine, Marine Nadal, Hajer Nadif, Kladoum Nassarmadji, Pierre Natella, Sandrine Ndingamondze, Stefan Neraal, Caroline Nguyen, Bao N'Guyen, Isabelle Nion Larmurier, Luc Nlomenyengue, Nicolas Noel, Hilario Nunes, Edris Omar, Zineb Ouazene, Elise Ouedraogo, Wassila Ouelaa, Anissa Oukhedouma, Yasmina Ould Amara, Herve Oya, Johanna Oziel, Thomas Padilla, Elena Paillaud, Solenne Paiva, Beatrice Parfait, Perrine Parize, Christophe Parizot, Antoine Parrot, Arthur Pavot, Laetitia Peaudecerf, Frédéric Pene, Marion Pepin, Julie Pernet, Claire Pernin, Mylène Petit, Olivier Peyrony, Marie-Pierre Pietri, Olivia Pietri, Marc Pineton De Chambrun, Michelle Pinson, Claire Pintado, Valentine Piquard, Christine Pires, Benjamin Planquette, Sandrine Poirier, Anne-Laure Pomel, Stéphanie Pons, Diane Ponscarme, Annegaelle Pourcelot, Valérie Pourcher, Anne Pouvaret, Florian Prever, Miresta Previlon, Margot Prevost, Marie-Julie Provoost, Cyril Quemeneur, Cédric Rafat, Agathe Rami, Brigitte Ranque, Maurice Raphael, Jean Herle Raphalen, Anna Rastoin, Mathieu Raux, Amani Rebai, Michael Reby, Alexis Regent, Asma Regrag, Matthieu Resche-Rigon, Quentin Ressaire, Christian Richard, Mariecaroline Richard, Maxence Robert, Benjamin Rohaut, Camille Rolland-Debord, Jacques Ropers, Anne-Marie Roque-Afonso, Charlotte Rosso, Mélanie Rousseaux, Nabila Rousseaux, Swasti Roux, Lorène Roux, Claire Rouzaud, Antoine Rozes, Emma Rubenstein, Jean-Marc Sabate, Sheila Sabet, Sophie-Caroline Sacleux, Nathalie Saidenberg Kermanach, Faouzi Saliba, Dominique Salmon, Laurent Savale, Guillaume Savary, Rebecca Sberro, Anne Scemla, Frederic Schlemmer, Mathieu Schwartz, Saïd Sedfi, Samia Sefir-Kribel, Philippe Seksik, Pierre Sellier, Agathe Selves, Nicole Sembach, Luca Semerano, Marie-Victoire Senat, Damien Sene, Alexandra Serris, Lucile Sese, Naima Sghiouar, Johanna Sigaux, Martin Siguier, Johanne Silvain, Noémie Simon, Tabassome Simon, Lina Innes Skandri, Miassa Slimani, Aurélie Snauwaert, Harry Sokol, Heithem Soliman, Nisrine Soltani, Benjamin Soyer, Gabriel Steg, Lydia Suarez, Tali-Anne Szwebel, Kossi Taffame, Yacine Tandjaoui-Lambiotte, Claire Tantet, Mariagrazia Tateo, Igor Theodose, Pierre clement Thiebaud, Caroline Thomas, Kelly Tiercelet, Julie Tisserand, Carole Tomczak, Krystel Torelino, Fatima Touam-Ext, Lilia Toumi, Gustave Toury, Mireille Toy-Miou, Olivia Tran Dinh Thanh Lien, Alexy Trandinh, Jean-Marc Treluyer, Baptiste Trinque, Jennifer Truchot, Sarah Tubiana, Simone Tunesi, Matthieu Turpin, Agathe Turpin, Tomas Urbina, Rafael Usubillaga Narvaez, Yurdagul Uzunhan, Prabakar Vaittinadaayar, Arnaud Valent, Maelle Valentian, Nadia Valin, Hélène Vallet, Marina Vaz, Miguel-Alejandro Vazquezibarra, Benoit Vedie, Laetitia Velly, Celine Verstuyft, Cedric Viallette, Eric Vicaut, Dorothee Vignes, Damien Vimpere, Myriam Virlouvet, Guillaume Voiriot, Lena Voisot, Emmanuel Weiss, Nicolas Weiss, Anaïs Winchenne, Youri Yordanov, Lara Zafrani, Mohamad Zaidan, Wissem Zaidi, Cathia Zak, Aida Zarhrate-Ghoul, Ouassila Zatout, Suzanne Zeino, Michel Zeitouni, Naïma Zemirli, Lorene Zerah, Ounsa Zia, Marianne Ziol, Oceane Zolario, Julien Zuber, Claire Andrejak, François Angoulvant, Delphine Bachelet, Marie Bartoli, Romain Basmaci, Sylvie Behillil, Marine Beluze, Dehbia Benkerrou, Krishna Bhavsar, Lila Bouadma, Sabelline Bouchez, Maude Bouscambert, Minerva Cervantes-Gonzalez, Anissa Chair, Catherine Chirouze, Alexandra Coelho, Sandrine Couffin-Cadiergues, Eric d’Ortenzio, Marie-Pierre Debray, Laurene Deconinck, Dominique Deplanque, Diane Descamps, Mathilde Desvallée, Alpha Diallo, Alphonsine Diouf, Céline Dorival, François Dubos, Brigitte Elharrar, Vincent Enouf, Hélène Esperou, Marina Esposito-Farese, Manuel Etienne, Eglantine Ferrand Devouge, Nathalie Gault, Alexandre Gaymard, Tristan Gigante, Morgane Gilg, Jérémie Guedj, Alexandre Hoctin, Isabelle Hoffmann, Ikram Houas, Jean-Sébastien Hulot, Salma Jaafoura, Florentia Kaguelidou, Sabrina Kali, Antoine Khalil, Coralie Khan, Cédric Laouénan, Samira Laribi, Minh Le, Quentin Le Hingrat, Soizic Le Mestre, Hervé Le Nagard, François-Xavier Lescure, Sophie Letrou, Yves Levy, Bruno Lina, Guillaume Lingas, Jean-Christophe Lucet, Denis Malvy, Marina Mambert, Amina Meziane, Hugo Mouquet, Jimmy Mullaert, Nadège Neant, Duc Nguyen, Marion Noret, Saad Nseir, Aurélie Papadopoulos, Christelle Paul, Nathan Peiffer-Smadja, Thomas Perpoint, Ventzislava Petrov-Sanchez, Gilles Peytavin, Huong Pham, Olivier Picone, Oriane Puéchal, Christian Rabaud, Manuel Rosa-Calatrava, Bénédicte Rossignol, Patrick Rossignol, Carine Roy, Marion Schneider, Richa Su, Coralie Tardivon, Marie-Capucine Tellier, François Téoulé, Olivier Terrier, Jean-François Timsit, Christelle Tual, Sylvie Van Der Werf, Noémie Vanel, Aurélie Veislinger, Benoit Visseaux, Aurélie Wiedemann, Yazdan Yazdanpanah, Loubna Alavoine, Charlotte Charpentier, Aline Dechanet, Jean-Luc Ecobichon, Wahiba Frezouls, Nadhira Houhou, Jonathan Lehacaut, Pauline Manchon, Mariama Nouroudine, Caroline Quintin, Michael Thy, Sylvie van der Werf, Valérie Vignali, Abir Chahine, Nawal Waucquier, Maria-Claire Migaud, Félix Djossou, Mayka Mergeay-Fabre, Aude Lucarelli, Magalie Demar, Léa Bruneau, Patrick Gérardin, Adrien Maillot, Christine Payet, Bruno Laviolle, Fabrice Laine, Christophe Paris, Mireille Desille-Dugast, Julie Fouchard, Thierry Pistone, Pauline Perreau, Valérie Gissot, Carole L.E. Goas, Samatha Montagne, Lucie Richard, Kévin Bouiller, Maxime Desmarets, Alexandre Meunier, Marilou Bourgeon, Benjamin Lefévre, Hélène Jeulin, Karine Legrand, Sandra Lomazzi, Bernard Tardy, Amandine Gagneux-Brunon, Frédérique Bertholon, Elisabeth Botelho-Nevers, Christelle Kouakam, Leturque Nicolas, Layidé Roufai, Karine Amat, Hélène Espérou, Samia Hendou, Giuseppe Foti, Giuseppe Citerio, Ernesto Contro, Alberto Pesci, Maria Grazia Valsecchi, Marina Cazzaniga, Giacomo Bellani, Jorge Abad, Giulia Accordino, Micol Angelini, Sergio Aguilera-Albesa, Aina Aguiló-Cucurull, Esra Akyüz Özkan, Ilad Alavi Darazam, Jonathan Antonio Roblero Albisures, Juan C. Aldave, Miquel Alfonso Ramos, Taj Ali Khan, Anna Aliberti, Seyed Alireza Nadji, Gulsum Alkan, Suzan A. AlKhater, Jerome Allardet-Servent, Luis M. Allende, Rebeca Alonso-Arias, Mohammed S. Alshahrani, Laia Alsina, Zahir Amoura, Arnau Antolí, Romain Arrestier, Mélodie Aubart, Teresa Auguet, Iryna Avramenko, Gökhan Aytekin, Axelle Azot, Seiamak Bahram, Fanny Bajolle, Fausto Baldanti, Aurélie Baldolli, Maite Ballester, Benoit Barrou, Federica Barzaghi, Sabrina Basso, Gulsum Iclal Bayhan, Liliana Bezrodnik, Agurtzane Bilbao, Geraldine Blanchard-Rohner, Ignacio Blanco, Adeline Blandinières, Daniel Blázquez-Gamero, Marketa Bloomfield, Mireia Bolivar-Prados, Raphael Borie, Elisabeth Botdhlo-Nevers, Aurore Bousquet, David Boutolleau, Claire Bouvattier, Oksana Boyarchuk, Juliette Bravais, M. Luisa Briones, Marie-Eve Brunner, Raffaele Bruno, Maria Rita P. Bueno, Huda Bukhari, Jacinta Bustamante, Juan José Cáceres Agra, Ruggero Capra, Raphael Carapito, Maria Carrabba, Carlos Casasnovas, Marion Caseris, Irene Cassaniti, Martin Castelle, Francesco Castelli, Martín Castillo de Vera, Mateus V. Castro, Emilie Catherinot, Jale Bengi Celik, Alessandro Ceschi, Martin Chalumeau, Bruno Charbit, Cécile Boulanger, Père Clavé, Bonaventura Clotet, Anna Codina, Cloé Comarmond, Patrizia Comoli, Angelo G. Corsico, Taner Coşkuner, Aleksandar Cvetkovski, Cyril Cyrus, David Dalmau, François Danion, David Ross Darley, Vincent Das, Nicolas Dauby, Stéphane Dauger, Paul De Munte, Loic de Pontual, Amin Dehban, Geoffroy Delplancq, Isabelle Desguerre, Antonio Di Sabatino, Jean-Luc Diehl, Stephanie Dobbelaere, Elena Domínguez-Garrido, Clément Dubost, Olov Ekwall, Şefika Elmas Bozdemir, Marwa H. Elnagdy, Melike Emiroglu, Akifumi Endo, Emine Hafize Erdeniz, Selma Erol Aytekin, Maria Pilar Etxart Lasa, Romain Euvrard, Giovanna Fabio, Laurence Faivre, Antonin Falck, Muriel Fartoukh, Morgane Faure, Miguel Fernandez Arquero, Ricard Ferrer, Jose Ferreres, Bruno Francois, Victoria Fumadó, Kitty S.C. Fung, Francesca Fusco, Alenka Gagro, Blanca Garcia Solis, Pierre Garçon, Pascale Gaussem, Zeynep Gayretli, Juana Gil-Herrera, Laurent Gilardin, Audrey Giraud Gatineau, Mònica Girona-Alarcón, Karen Alejandra Cifuentes Godínez, Jean-Christophe Goffard, Nacho Gonzales, Luis I. Gonzalez-Granado, Rafaela González-Montelongo, Antoine Guerder, Belgin Gülhan, Victor Daniel Gumucio, Leif Gunnar Hanitsch, Jan Gunst, Marta Gut, Jérôme Hadjadj, Selda Hancerli, Tetyana Hariyan, Nevin Hatipoglu, Deniz Heppekcan, Elisa Hernandez-Brito, Po-ki Ho, María Soledad Holanda-Peña, Juan P. Horcajada, Sami Hraiech, Linda Humbert, Ivan F.N. Hung, Alejandro D. Iglesias, Antonio Íñigo-Campos, Matthieu Jamme, María Jesús Arranz, Marie-Thérèse Jimeno, Iolanda Jordan, Saliha Kanık-Yüksek, Yalcin Kara, Aydın Karahan, Adem Karbuz, Kadriye Kart Yasar, Ozgur Kasapcopur, Kenichi Kashimada, Sevgi Keles, Yasemin Kendir Demirkol, Yasutoshi Kido, Can Kizil, Ahmet Osman Kılıç, Adam Klocperk, Antonia Koutsoukou, Zbigniew J. Król, Hatem Ksouri, Paul Kuentz, Arthur M.C. Kwan, Yat Wah M. Kwan, Janette S.Y. Kwok, Jean-Christophe Lagier, David S.Y. Lam, Vicky Lampropoulou, Fleur Le Bourgeois, Yee-Sin Leo, Rafael Leon Lopez, Daniel Leung, Michael Levin, Michael Levy, Romain Lévy, Zhi Li, Daniele Lilleri, Edson Jose Adrian Bolanos Lima, Agnes Linglart, Eduardo López-Collazo, José M. Lorenzo-Salazar, Céline Louapre, Catherine Lubetzki, Kwok-Cheung Lung, Charles-Edouard Luyt, David C. Lye, Cinthia Magnone, Enrico Marchioni, Carola Marioli, Majid Marjani, Laura Marques, Jesus Marquez Pereira, Andrea Martín-Nalda, David Martínez Pueyo, Javier Martinez-Picado, Iciar Marzana, Carmen Mata-Martínez, Alexis Mathian, Larissa R.B. Matos, Gail V. Matthews, Julien Mayaux, Raquel McLaughlin-Garcia, Philippe Meersseman, Jean-Louis Mège, Armand Mekontso-Dessap, Isabelle Melki, Federica Meloni, Jean-François Meritet, Paolo Merlani, Özge Metin Akcan, Mehdi Mezidi, Isabelle Migeotte, Maude Millereux, Matthieu Million, Tristan Mirault, Clotilde Mircher, Mehdi Mirsaeidi, Yoko Mizoguchi, Bhavi P. Modi, Francesco Mojoli, Elsa Moncomble, Abián Montesdeoca Melián, Antonio Morales Martinez, Francisco Morandeira, Pierre-Emmanuel Morange, Clémence Mordacq, Guillaume Morelle, Stéphane J. Mouly, Adrián Muñoz-Barrera, Cyril Nafati, Shintaro Nagashima, Yu Nakagama, Bénédicte Neven, João Farela Neves, Yuk-Yung Ng, Hubert Nielly, Yeray Novoa Medina, Esmeralda Nuñez Cuadros, Semsi Nur Karabela, J. Gonzalo Ocejo-Vinyals, Mehdi Oualha, Amani Ouedrani, Tayfun Özçelik, Aslinur Ozkaya-Parlakay, Michele Pagani, Maria Papadaki, Philippe Parola, Tiffany Pascreau, Stéphane Paul, Estela Paz-Artal, Sigifredo Pedraza, Nancy Carolina González Pellecer, Silvia Pellegrini, Rebeca Pérez de Diego, Xosé Luis Pérez-Fernández, Aurélien Philippe, Quentin Philippot, Adrien Picod, Marc Pineton de Chambrun, Antonio Piralla, Laura Planas-Serra, Dominique Ploin, Julien Poissy, Géraldine Poncelet, Garyphallia Poulakou, Marie S. Pouletty, Persia Pourshahnazari, Jia Li Qiu-Chen, Paul Quentric, Thomas Rambaud, Didier Raoult, Violette Raoult, Anne-Sophie Rebillat, Claire Redin, Léa Resmini, Pilar Ricart, Jean-Christophe Richard, Raúl Rigo-Bonnin, Nadia Rivet, Jacques G. Rivière, Gemma Rocamora-Blanch, Mathieu P. Rodero, Carlos Rodrigo, Luis Antonio Rodriguez, Carlos Rodriguez-Gallego, Agustí Rodriguez-Palmero, Carolina Soledad Romero, Anya Rothenbuhler, Damien Roux, Nikoletta Rovina, Flore Rozenberg, Yvon Ruch, Montse Ruiz, Maria Yolanda Ruiz del Prado, Juan Carlos Ruiz-Rodriguez, Joan Sabater-Riera, Kai Saks, Maria Salagianni, Oliver Sanchez, Adrián Sánchez-Montalvá, Silvia Sánchez-Ramón, Laire Schidlowski, Agatha Schluter, Julien Schmidt, Matthieu Schmidt, Catharina Schuetz, Cyril E. Schweitzer, Francesco Scolari, Luis Seijo, Analia Gisela Seminario, Piseth Seng, Sevtap Senoglu, Mikko Seppänen, Alex Serra Llovich, Virginie Siguret, Eleni Siouti, David M. Smadja, Nikaia Smith, Ali Sobh, Xavier Solanich, Jordi Solé-Violán, Catherine Soler, Betül Sözeri, Giulia Maria Stella, Yuriy Stepanovskiy, Annabelle Stoclin, Fabio Taccone, Jean-Luc Taupin, Simon J. Tavernier, Loreto Vidaur Tello, Benjamin Terrier, Guillaume Thiery, Karolina Thorn, Caroline Thumerelle, Imran Tipu, Martin Tolstrup, Gabriele Tomasoni, Julie Toubiana, Josep Trenado Alvarez, Vasiliki Triantafyllia, Jesús Troya, Owen T.Y. Tsang, Liina Tserel, Eugene Y.K. Tso, Alessandra Tucci, Şadiye Kübra Tüter Öz, Matilde Valeria Ursini, Takanori Utsumi, Pierre Vabres, Juan Valencia-Ramos, Ana Maria Van Den Rym, Isabelle Vandernoot, Valentina Velez-Santamaria, Silvia Patricia Zuniga Veliz, Mateus C. Vidigal, Sébastien Viel, Cédric Villain, Marie E. Vilaire-Meunier, Judit Villar-García, Audrey Vincent, Dimitri Van der Linden, Alla Volokha, Fanny Vuotto, Els Wauters, Alan K.L. Wu, Tak-Chiu Wu, Aysun Yahşi, Osman Yesilbas, Mehmet Yildiz, Barnaby E. Young, Ufuk Yükselmiş, Marco Zecca, Valentina Zuccaro, Jens Van Praet, Bart N. Lambrecht, Eva Van Braeckel, Cédric Bosteels, Levi Hoste, Eric Hoste, Fré Bauters, Jozefien De Clercq, Catherine Heijmans, Hans Slabbynck, Leslie Naesens, Benoit Florkin, Mary-Anne Young, Amanda Willis, Paloma Lapuente-Suanzes, Ana de Andrés-Martín, Matilda Berkell, Valerio Carelli, Alessia Fiorentino, Surbhi Malhotra, Alessandro Mattiaccio, Tommaso Pippucci, Marco Seri, Evelina Tacconelli, Michiel van Agtmael, Anne Geke Algera, Brent Appelman, Frank van Baarle, Diane Bax, Martijn Beudel, Harm Jan Bogaard, Marije Bomers, Peter Bonta, Lieuwe Bos, Michela Botta, Justin de Brabander, Godelieve de Bree, Sanne de Bruin, David T.P. Buis, Marianna Bugiani, Esther Bulle, Osoul Chouchane, Alex Cloherty, Mirjam Dijkstra, Dave A. Dongelmans, Romein W.G. Dujardin, Paul Elbers, Lucas Fleuren, Suzanne Geerlings, Theo Geijtenbeek, Armand Girbes, Bram Goorhuis, Martin P. Grobusch, Florianne Hafkamp, Laura Hagens, Jorg Hamann, Vanessa Harris, Robert Hemke, Sabine M. Hermans, Leo Heunks, Markus Hollmann, Janneke Horn, Joppe W. Hovius, Menno D. de Jong, Rutger Koning, Endry H.T. Lim, Niels van Mourik, Jeaninne Nellen, Esther J. Nossent, Frederique Paulus, Edgar Peters, Dan A.I. Pina-Fuentes, Tom van der Poll, Bennedikt Preckel, Jan M. Prins, Jorinde Raasveld, Tom Reijnders, Maurits C.F. J. de Rotte, Michiel Schinkel, Marcus J. Schultz, Femke A.P. Schrauwen, Alex Schuurmans, Jaap Schuurmans, Kim Sigaloff, Marleen A. Slim, Patrick Smeele, Marry Smit, Cornelis S. Stijnis, Willemke Stilma, Charlotte Teunissen, Patrick Thoral, Anissa M. Tsonas, Pieter R. Tuinman, Marc van der Valk, Denise P. Veelo, Carolien Volleman, Heder de Vries, Lonneke A. Vught, Michèle van Vugt, Dorien Wouters, A.H. Zwinderman, Matthijs C. Brouwer, W. Joost Wiersinga, Alexander P.J. Vlaar, Miranda F. Tompkins, Camille Alba, Daniel N. Hupalo, John Rosenberger, Gauthaman Sukumar, Matthew D. Wilkerson, Xijun Zhang, Justin Lack, Andrew J. Oler, Kerry Dobbs, Ottavia M. Delmonte, Jeffrey J. Danielson, Andrea Biondi, Laura Rachele Bettini, Mariella D’Angiò, Ilaria Beretta, Luisa Imberti, Alessandra Sottini, Virginia Quaresima, Eugenia Quiros-Roldan, Camillo Rossi, Riccardo Castagnoli, Daniela Montagna, Amelia Licari, and Gian Luigi Marseglia

Subjects
HLA, association, asymptomatic infection, COVID-19, population stratification, Genetics, QH426-470
Abstract

Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

Published
2024
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69. Relation between crystal structure and optical properties in the correlated blue pigment YIn$_{1-x}$Mn$_x$O$_3$

Author

Ransmayr, Valentin, Tomczak, Jan M., and Galler, Anna

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

A material's properties and functionalities are determined by its chemical constituents and the atomic arrangement in which they crystallize. For the recently discovered pigment YIn$_{1-x}$Mn$_x$O$_3$, for instance, it had been surmised that its bright blue color owes to an unusual, trigonal bipyramidal, oxygen coordination of the manganese impurities. Here, we demonstrate that, indeed, a direct correspondence between details of the local Mn environment and the pigment's blue color holds: Combining realistic many-body calculations (dynamical mean-field theory to treat the quasi-atomic Mn-multiplets at low doping x=0.08) with an effective medium description (Kubelka-Munk model to describe scattering in a milled pigment sample), we find that only a Mn-coordination polyhedra consisting of two distorted oxygen pyramids results in a diffuse reflectance commensurate with the experimental blue color. We motivate that the distortion of the bipyramid helps circumventing atomic selection rules, allowing for dipolar $d$-$d$ transitions and creating the desired two-peak absorption profile.

Published
2022
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70. Optimizing superconductivity: from cuprates via nickelates to palladates

Author

Kitatani, Motoharu, Si, Liang, Worm, Paul, Tomczak, Jan M., Arita, Ryotaro, and Held, Karsten

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

Motivated by cuprate and nickelate superconductors, we perform a comprehensive study of the superconducting instability in the single-band Hubbard model. We calculate the spectrum and superconducting transition temperature $T_{\rm c}$ as a function of filling and Coulomb interaction for a range of hopping parameters, using the dynamical vertex approximation. We find the sweet spot for high $T_{\rm c}$ to be at intermediate coupling, moderate Fermi surface warping, and low hole doping. Combining these results with first principles calculations, neither nickelates nor cuprates are close to this optimum within the single-band description. Instead, we identify some palladates, notably RbSr$_2$PdO$_3$ and $A^{\prime}_2$PdO$_2$Cl$_2$ ($A^{\prime}$=Ba$_{0.5}$La$_{0.5}$), to be virtually optimal, while others, such as NdPdO$_2$, are too weakly correlated., Comment: 8+16 pages, 5+18 figures

Published
2022
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71. Macro-Level Social Work Interventions in Schools: Poverty Simulation Programs as Professional Development Opportunities for K-12 Educators

Author

Curry, Anna Maria T. and Tomczak, Stephen Monroe

Abstract

Poverty continues to be a significant public health crisis across the United States, and its impact is particularly prevalent among school-aged youth and their families. Many K-12 educators do not fully understand the realities associated with living in poverty. Such a lack of understanding impacts teachers' ability to meet the unique educational needs of students experiencing poverty and develop positive teacher-student relationships. This article sets the stage for further discussion on the lack of quality training, education, and professional development for teachers on poverty. The authors propose a model for professional development aimed at increasing empathy and understanding among K-12 educators through experiential learning tools such as the Community Action Poverty Simulation. The article concludes with an in-depth discussion on implications for future practice and a call to action for school social workers to bring innovative solutions to their campuses that pull from their educational background in advocacy and social justice to enhance teacher training through an interdisciplinary approach.

Published
2023
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75. Employees of the Future: Expected Competences at the Higher Education Level

Author

Mruk-Tomczak Dobrosława and Jerzyk Ewa

Subjects
new competences, higher education, labor market, employers’ needs, nowe kompetencje, szkolnictwo wyższe, rynek pracy, potrzeby pracodawców, j240, m510, a230, i250, Social Sciences
Abstract

Given the changing nature of the modern economy, technological advances and increasing globalization, labor markets are presenting university graduates with new challenges in terms of the competences expected of them. The aim of this article is to evaluate and forecast the future of labor market demands in relation to the competences of future employees. A comprehensive analysis of these expectations is presented, drawing on findings from the desk research method, further supplemented with a qualitative study. The discussion focuses on identifying key competences that employers are looking for in today’s business environment and the competences that will be necessary in the long term. The paper contributes to the ongoing debate on the transformation of curricula in higher education, especially in relation to business schools, emphasizing the need to continually monitor market expectations and make necessary adjustments to curricula. The conclusions from this study are intended to serve as a source of inspiration for decision-makers responsible for educational programs at universities, especially those with a business profile, and other stakeholders aiming to bridge the gap between the academic world and the dynamically changing labor market.

Published
2024
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76. Polish and Lithuanian Students at the University of Basel from the Sixteenth to the Seventeenth Century

Author

Robert T. Tomczak

Subjects
History (General) and history of Europe
Abstract

This article examines the question of the participation of students from Poland and Lithuania in the academic life in Basel from the fifteenth to the seventeenth centuries. Because the article is a prosopographic study, the group of surveyed students is presented in the context of their ethnicity, territorial and social origins, confession and field of studies. Two figures from Poland (Jan Osmólski and Marcin Chmielecki) most distinguished for intellectual contacts with Basel are also presented.

Published
2024
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77. The Potential of Non-Native Pines for Timber Production—A Case Study from Afforested Post-Mining Sites

Author

Aleš Zeidler, Vlastimil Borůvka, Karol Tomczak, Zdeněk Vacek, Jan Cukor, Stanislav Vacek, and Arkadiusz Tomczak

Subjects
Pinus sylvestris, alternative pines species, wood density, strength, wood quality, reclamation, Plant ecology, QK900-989
Abstract

Scots pine (Pinus sylvestris L.) represents one of the most important commercial coniferous tree species, providing valuable timber. Due to climate change, it is experiencing serious problems in some areas, therefore, finding a suitable substitute for its wood is currently a challenge. In this study, we compared the wood quality of three different non-native pine species and Scots pine growing at the same site to ensure identical growing conditions. Black pine (Pinus nigra J. F. Arnold), a pine species native to Southern Europe, lodgepole pine (Pinus contorta Douglas ex Loudon), and ponderosa pine (Pinus ponderosa Douglas ex C. Lawson) native to North America were compared to Scots pine for selected quantitative (productivity) and qualitative (physical and mechanical) properties. Significant differences between pine species were found in all quantitative dendrometric parameters, except average diameter at breast height. The stand volume ranged from 157 m3 ha−1 for lodgepole pine to 356 m3 ha−1 for Scots pine. For qualitative characteristics, wood density, shrinkage, and compressive strength were used to find differences among species in choosing the best alternative. The highest wood density was obtained for Scots pine (458 kg m−3), followed by black pine with 441 kg m−3. The density of the remaining pine species was significantly lower. Scots pine also exceeded the tested species in compressive strength (44.2 MPa). Lodgepole pine achieved the second highest value (39.3 MPa) but was statistically similar to black pine (36.5 MPa). The tested pine species exhibited similar values in shrinkage, which were statistically insignificant, ranging from 14.3% for lodgepole pine to 15.1% for Scots pine. Based on applications and preferred characteristics, black pine or lodgepole pine could serve as the Scots pine substitute in some areas. And vice versa, ponderosa pine did not attain the Scots pine wood quality.

Published
2024
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78. Wood Quality of Pendulate Oak on Post-Agricultural Land: A Case Study Based on Physico-Mechanical and Anatomical Properties

Author

Karol Tomczak, Przemysław Mania, Jan Cukor, Zdeněk Vacek, Magdalena Komorowicz, and Arkadiusz Tomczak

Subjects
Quercus robur L., wood density, fiber characteristics, bending strength, modulus of elasticity, Plant ecology, QK900-989
Abstract

Oak is one of the most economically important hardwood tree species in Europe, and its prevalence will increase due to progressing global climate change, according to predictive models. With the increasing demand for timber and with the need for a balance between carbon emissions and sequestration, it is essential to address the afforestation of agricultural land. Therefore, this research aimed to investigate the physico-mechanical properties and anatomical structure of pendulate oak (Quercus robur L.) wood—specifically focusing on the trunk’s cross-section—in post-agricultural areas compared with the forest land in the western part of Poland. Wood density, bending strength, modulus of elasticity, and other parameters were analyzed from 1626 wood samples. The analysis of physico-mechanical properties reveals that, historically, agricultural land use has an almost negligible impact on wood quality. Despite significant differences in small vessel diameter and fiber length favoring trees from post-agricultural land, the physico-mechanical properties remain consistent. Large vessel measurements show comparable diameter and length in both land types. These findings suggest that post-agricultural land can serve as an effective alternative for high-quality pendulate oak wood production for industrial purposes. However, wood from post-agricultural land may exhibit a decrease in modulus of rupture by over 30% and potentially lower density above the trunk’s halfway point. This observation hints at the fact that oak trees in post-agricultural areas could be cultivated in shorter rotation periods compared to forest land.

Published
2024
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79. LinReTraCe: The Linear Response Transport Centre

Author

Pickem, Matthias, Maggio, Emanuele, and Tomczak, Jan M.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

We describe the "Linear Response Transport Centre" (LinReTraCe), a package for the simulation of transport properties of solids. LinReTraCe captures quantum (in)coherence effects beyond semi-classical Boltzmann techniques, while incurring similar numerical costs. The enabling algorithmic innovation is a semi-analytical evaluation of Kubo formulae for resistivities and the coefficients of Hall, Seebeck and Nernst. We detail the program's architecture, its interface and usage with electronic-structure packages such as WIEN2k, VASP, and Wannier90, as well as versatile tight-binding settings., Comment: 64 pages, 18 figures, submission to SciPost

Published
2022
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80. Towards a General Purpose CNN for Long Range Dependencies in $N$D

Author

Romero, David W., Knigge, David M., Gu, Albert, Bekkers, Erik J., Gavves, Efstratios, Tomczak, Jakub M., and Hoogendoorn, Mark

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

The use of Convolutional Neural Networks (CNNs) is widespread in Deep Learning due to a range of desirable model properties which result in an efficient and effective machine learning framework. However, performant CNN architectures must be tailored to specific tasks in order to incorporate considerations such as the input length, resolution, and dimentionality. In this work, we overcome the need for problem-specific CNN architectures with our Continuous Convolutional Neural Network (CCNN): a single CNN architecture equipped with continuous convolutional kernels that can be used for tasks on data of arbitrary resolution, dimensionality and length without structural changes. Continuous convolutional kernels model long range dependencies at every layer, and remove the need for downsampling layers and task-dependent depths needed in current CNN architectures. We show the generality of our approach by applying the same CCNN to a wide set of tasks on sequential (1$\mathrm{D}$) and visual data (2$\mathrm{D}$). Our CCNN performs competitively and often outperforms the current state-of-the-art across all tasks considered., Comment: First two authors contributed equally to this work

Published
2022

81. On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

Author

Deja, Kamil, Kuzina, Anna, Trzciński, Tomasz, and Tomczak, Jakub M.

Subjects
Computer Science - Machine Learning
Abstract

Diffusion-based Deep Generative Models (DDGMs) offer state-of-the-art performance in generative modeling. Their main strength comes from their unique setup in which a model (the backward diffusion process) is trained to reverse the forward diffusion process, which gradually adds noise to the input signal. Although DDGMs are well studied, it is still unclear how the small amount of noise is transformed during the backward diffusion process. Here, we focus on analyzing this problem to gain more insight into the behavior of DDGMs and their denoising and generative capabilities. We observe a fluid transition point that changes the functionality of the backward diffusion process from generating a (corrupted) image from noise to denoising the corrupted image to the final sample. Based on this observation, we postulate to divide a DDGM into two parts: a denoiser and a generator. The denoiser could be parameterized by a denoising auto-encoder, while the generator is a diffusion-based model with its own set of parameters. We experimentally validate our proposition, showing its pros and cons.

Published
2022

82. Quantum versus classical nature of a low-temperature magnetic phase transition in TbAl$_3$(BO$_3$)$_4$

Author

Zajarniuk, T., Szewczyk, A., Wisniewski, P., Gutowska, M. U., Puzniak, R., Szymczak, H., Gudim, I., Bedarev, V. A., Pashchenko, M. I., Tomczak, P., and Szuszkiewicz, W.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Other Condensed Matter
Abstract

Specific heat, $C_B$, of a TbAl$_3$(BO$_3$)$_4$ crystal was studied for 50 mK $

Published
2022
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84. Combining Inquiry-Based Activities with Virtual Simulations in Fifth Grade Science: An Action Research Study

Author

Julie Tomczak

Abstract

This action research study aimed to find ways to adjust my practice by incorporating inquiry-based, science activities and virtual simulations to improve student conceptual understanding of physical and chemical changes. A multi-lesson, curricular intervention combining inquiry-based activities and virtual simulations was developed using research-based best practices and implemented in three 5th-grade classrooms. A self-reflective journal, the Science Teacher Inquiry Rubric (STIR), and student interviews were used to study my teaching practice. Exit tickets, student interviews and surveys, and classroom artifacts were used to study changes in students' conceptual understanding of the content. Data were collected from a purposeful sample of twelve fifth-grade students and analyzed using Process, In Vivo Coding, and Pattern Coding. Integrating virtual simulations and inquiry-based learning led to a more student-driven experience. During the study, students provided feedback through exit tickets and shared that inquiry-based activities and virtual simulations positively impacted their understanding of physical and chemical changes. Students demonstrated new learning of physical and chemical changes using inquiry-based activities and virtual simulations in small groups and during individual assessments. Yet, only a small number of students reported feeling confident in explaining the scientific models they developed to others. While the results were primarily positive, there are adjustments I need to make to this curriculum. For example, I need to reconsider the timing of the virtual simulations within the instruction. I also need to consider issues related to the limited time students must use the free versions of virtual simulations since paying for full access is not an option for me. This study offers ideas for integrating inquiry-based learning and virtual simulations in an elementary science classroom and provides specific details regarding the impact these methods have on teaching and student conceptual understanding. Given that most work in this area occurs in high school or post-secondary science classrooms, this study contributes important insights and suggests that elementary science classrooms can successfully combine inquiry-based science activities and virtual simulations. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2023

85. Exploring AKAPs in visual signaling

Author

Julia Tomczak, Joanna Mackiewicz, Malwina Lisek, Aleksandra Kaluza, and Tomasz Boczek

Subjects
A-kinase anchoring proteins, visual system, retina, signaling compartmentalization, retinal ganglion cell, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The complex nature of the retina demands well-organized signaling to uphold signal accuracy and avoid interference, a critical aspect in handling a variety of visual stimuli. A-kinase anchoring proteins (AKAPs), known for binding protein kinase A (PKA), contribute to the specificity and efficiency of retinal signaling. They play multifaceted roles in various retinal cell types, influencing photoreceptor sensitivity, neurotransmitter release in bipolar cells, and the integration of visual information in ganglion cells. AKAPs like AKAP79/150 and AKAP95 exhibit distinct subcellular localizations, impacting synaptic transmission and receptor sensitivity in photoreceptors and bipolar cells. Furthermore, AKAPs are involved in neuroprotective mechanisms and axonal degeneration, particularly in retinal ganglion cells. In particular, AKAP6 coordinates stress-specific signaling and promotes neuroprotection following optic nerve injury. As our review underscores the therapeutic potential of targeting AKAP signaling complexes for retinal neuroprotection and enhancement, it acknowledges challenges in developing selective drugs that target complex protein–protein interactions. Overall, this exploration of AKAPs provides valuable insights into the intricacies of retinal signaling, offering a foundation for understanding and potentially addressing retinal disorders.

Published
2024
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86. Hope for success as a mediator between Big Five personality traits and achievement goal orientation among high performance and recreational athletes.

Author

Maciej Tomczak, Paweł Kleka, Ewa Tomczak-Łukaszewska, and Małgorzata Walczak

Subjects
Medicine, Science
Abstract

The main objective of this study was to determine whether hope for success mediates the relationship between personality and goal orientation in high performance and recreational athletes. The cross-sectional study included 289 high performance and recreational athletes of various sports (age: M = 20.34, SD = 1.86). To examine personality, we used the Big Five IPIP-BFM-20 questionnaire. To assess hope for success, we used the Hope for Success Questionnaire. The Task and Ego Orientation in Sport Questionnaire (TEOSQ) was employed to examine goal orientation. Hope for success significantly mediates the relationships between conscientiousness, extraversion, emotional stability, intellect, and task goal orientation in sport. Higher levels of these personality traits are related to athletes' higher hope for success, which, in turn, is positively related to their task orientation. Personality traits may underpin the hope for success that develops from childhood. This, in turn, appears to be an important component on which, combined with the positive interaction and support from coaches, a task goal orientation beneficial to sport can be shaped in athletes.

Published
2024
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87. Alleviating Adversarial Attacks on Variational Autoencoders with MCMC

Author

Kuzina, Anna, Welling, Max, and Tomczak, Jakub M.

Subjects
Computer Science - Machine Learning
Abstract

Variational autoencoders (VAEs) are latent variable models that can generate complex objects and provide meaningful latent representations. Moreover, they could be further used in downstream tasks such as classification. As previous work has shown, one can easily fool VAEs to produce unexpected latent representations and reconstructions for a visually slightly modified input. Here, we examine several objective functions for adversarial attack construction proposed previously and present a solution to alleviate the effect of these attacks. Our method utilizes the Markov Chain Monte Carlo (MCMC) technique in the inference step that we motivate with a theoretical analysis. Thus, we do not incorporate any extra costs during training, and the performance on non-attacked inputs is not decreased. We validate our approach on a variety of datasets (MNIST, Fashion MNIST, Color MNIST, CelebA) and VAE configurations ($\beta$-VAE, NVAE, $\beta$-TCVAE), and show that our approach consistently improves the model robustness to adversarial attacks.

Published
2022

88. Toward Functionalized Ultrathin Oxide Films: the Impact of Surface Apical Oxygen

Author

Gabel, Judith, Pickem, Matthias, Scheiderer, Philipp, Dudy, Lenart, Leikert, Berengar, Fuchs, Marius, Stübinger, Martin, Schmitt, Matthias, Küspert, Julia, Sangiovanni, Giorgio, Tomczak, Jan M., Held, Karsten, Lee, Tien-Lin, Claessen, Ralph, and Sing, Michael

Subjects
Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

Thin films of transition metal oxides open up a gateway to nanoscale electronic devices beyond silicon characterized by novel electronic functionalities. While such films are commonly prepared in an oxygen atmosphere, they are typically considered to be ideally terminated with the stoichiometric composition. Using the prototypical correlated metal SrVO$_3$ as an example, it is demonstrated that this idealized description overlooks an essential ingredient: oxygen adsorbing at the surface apical sites. The oxygen adatoms, which persist even in an ultrahigh vacuum environment, are shown to severely affect the intrinsic electronic structure of a transition metal oxide film. Their presence leads to the formation of an electronically dead surface layer but also alters the band filling and the electron correlations in the thin films. These findings highlight that it is important to take into account surface apical oxygen or -- mutatis mutandis -- the specific oxygen configuration imposed by a capping layer to predict the behavior of ultrathin films of transition metal oxides near the single unit-cell limit.

Published
2022
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89. Zoology of spin and orbital fluctuations in ultrathin oxide films

Author

Pickem, Matthias, Kaufmann, Josef, Held, Karsten, and Tomczak, Jan M.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract

Many metallic transition-metal oxides turn insulating when grown as films that are only a few unit-cells thick. The microscopic origins of these thickness induced metal-to-insulator transitions however remain under dispute. Here, we simulate the extreme case of a monolayer of an inconspicuous correlated metal -- the strontium vanadate SrVO$_3$ -- deposited on a SrTiO$_3$ substrate. Crucially, our system can have a termination to vacuum consisting of either a SrO or a VO$_2$ top layer. While we find that both lead to Mott insulating behavior at nominal stoichiometry, the phase diagram emerging upon doping -- chemically or through an applied gate voltage -- is qualitatively different. Indeed, our many-body calculations reveal a cornucopia of nonlocal fluctuations associated with (in)commensurate antiferromagnetic, ferromagnetic, as well as stripe and checkerboard orbital ordering instabilities. Identifying that the two geometries yield crystal-field splittings of opposite signs, we elucidate the ensuing phases through the lens of the orbital degrees of freedom. Quite generally, our work highlights that interface and surface reconstruction and the deformation or severing of coordination polyhedra in ultra-thin films drive rich properties that are radically different from the material's bulk physics., Comment: 10 pages, 8 figures

Published
2022
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90. Phase diagram of nickelate superconductors calculated by dynamical vertex approximation

Author

Held, Karsten, Si, Liang, Worm, Paul, Janson, Oleg, Arita, Ryotaro, Zhong, Zhicheng, Tomczak, Jan M., and Kitatani, Motoharu

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

We review the electronic structure of nickelate superconductors with and without effects of electronic correlations. As a minimal model we identify the one-band Hubbard model for the Ni 3$d_{x^2-y^2}$ orbital plus a pocket around the $A$-momentum. The latter however merely acts as a decoupled electron reservoir. This reservoir makes a careful translation from {nominal} Sr-doping to the doping of the one-band Hubbard model mandatory. Our dynamical mean-field theory calculations, in part already supported by experiment, indicate that the $\Gamma$ pocket, Nd 4$f$ orbitals, oxygen 2$p$ and {the} other Ni 3$d$ orbitals are not relevant in the superconducting doping regime. The physics is completely different if topotactic hydrogen is present or the oxygen reduction is incomplete. Then, a two-band physics hosted by the Ni 3$d_{x^2-y^2}$ and 3$d_{3z^2-r^2}$ orbitals emerges. Based on our minimal modeling we calculated the superconducting $T_c$ vs. Sr-doping $x$ phase diagram prior to experiment using the dynamical vertex approximation. For such a notoriously difficult to determine quantity as $T_c$, the agreement with experiment is astonishingly good. The prediction that $T_c$ is enhanced with pressure or compressive strain, has been confirmed experimentally as well. This supports that the one-band Hubbard model plus an electron reservoir is the appropriate minimal model., Comment: 20 pages; 9 figuress; 3 tables; to be published in Frontiers in Physics as part of a series on nickelate superconductors

Published
2022
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92. Marketing-Mix-Planung

Author

Tomczak, Torsten, Reinecke, Sven, Gollnhofer, Johanna, Tomczak, Torsten, Reinecke, Sven, and Gollnhofer, Johanna

Published
2023
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96. Marktforschung

Author

Tomczak, Torsten, Reinecke, Sven, Gollnhofer, Johanna, Tomczak, Torsten, Reinecke, Sven, and Gollnhofer, Johanna

Published
2023
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97. Einführung

Author

Tomczak, Torsten, Reinecke, Sven, Gollnhofer, Johanna, Tomczak, Torsten, Reinecke, Sven, and Gollnhofer, Johanna

Published
2023
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