530 results on '"Zander, P."'
Search Results
2. The Gestalt of Functioning in Autism Revisited: First Revision of the International Classification of Functioning, Disability and Health Core Sets
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Sven Bölte, Lovisa Alehagen, Melissa H. Black, John Hasslinger, Elina Wessman, Karl Lundin Remnélius, Peter B. Marschik, Emily D'Arcy, Susanna Crowson, Megan Freeth, Andreas Seidel, Sonya Girdler, and Eric Zander
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Functioning is a construct capturing how an individual's engagement in everyday life emerges from the interaction between the individual and their environment. The World Health Organization's International Classification of Functioning, Disability and Health (ICF) provides a biopsychosocial framework of functioning. Previously, the ICF was adapted for use in autism by developing Core Sets, a selection of ICF codes from the entire classification for specific conditions. Here, we present the first revision of the ICF of the Core sets for autism from a Delphi-like technique, based on evidence from Core Sets validation/linking studies, stakeholder feedback, and the development and piloting of the autism ICF Core Sets platform. Two ICF second-level codes were removed, and 12 were added to the comprehensive autism Core Set. The added codes reflect body functions in various sensory domains, fine hand use, and environmental factors. Changes were extensive for the age-appropriate brief Core Sets where ICF codes from the initial Core Sets were added or removed. The revisions conducted indicate a continued need for regularly updating Core Sets, based on empirical evidence and stakeholder involvement. We recommend the updated Core Sets for future use in autism research and practice in different age groups and contexts.
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- 2024
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3. Constraints on non-unitary neutrino mixing in light of atmospheric and reactor neutrino data
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Kozynets, Tetiana, Eller, Philipp, Zander, Alan, Ettengruber, Manuel, and Koskinen, D. Jason
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High Energy Physics - Phenomenology ,High Energy Physics - Experiment - Abstract
While the origin of neutrino masses remains unknown, several key neutrino mass generation models result in a non-unitary three-neutrino mixing matrix. To put such models to test, the deviations of the mixing matrix from unitarity can be measured directly through neutrino oscillation experiments. In this study, we perform a Bayesian analysis of the non-unitary mixing model using the recent public data from atmospheric and reactor neutrino experiments - namely IceCube-DeepCore, Daya Bay, and KamLAND. The novelty of our approach compared to the preceding global fits for non-unitarity is in the detailed treatment of the atmospheric neutrino data, which for the first time includes the relevant flux and detector systematic uncertainties. From the Bayesian posteriors on the individual mixing matrix elements, we derive the non-unitarity constraints in the form of normalisations and closures of the mixing matrix rows and columns. We find comparable constraints for electron and tau row normalisations as other similar studies in literature, and additionally reveal strong correlations between muon and tau row constraints induced by the atmospheric systematic uncertainties. We find that the current data is well described by both unitary and non-unitary mixing models, with a strong preference for the unitary mixing indicated by the Bayes factor. With the upcoming IceCube-Upgrade and JUNO detectors, both featuring superior energy resolution compared to the current atmospheric and reactor neutrino experiments, our constraints on the row normalisations are expected to improve by a factor of 2 (2.5) in the tau (muon) sector and by nearly 25% in the electron sector. In the future, our approach can be expanded to include solar and long-baseline neutrino experiments, with the aim to provide more stringent constraints while keeping track of the nuisance parameters that may be degenerate with non-unitarity., Comment: 46 pages, 26 figures
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- 2024
4. On the Complexity of Identification in Linear Structural Causal Models
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Dörfler, Julian, van der Zander, Benito, Bläser, Markus, and Liskiewicz, Maciej
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Computer Science - Artificial Intelligence ,Computer Science - Computational Complexity - Abstract
Learning the unknown causal parameters of a linear structural causal model is a fundamental task in causal analysis. The task, known as the problem of identification, asks to estimate the parameters of the model from a combination of assumptions on the graphical structure of the model and observational data, represented as a non-causal covariance matrix. In this paper, we give a new sound and complete algorithm for generic identification which runs in polynomial space. By standard simulation results, this algorithm has exponential running time which vastly improves the state-of-the-art double exponential time method using a Gr\"obner basis approach. The paper also presents evidence that parameter identification is computationally hard in general. In particular, we prove, that the task asking whether, for a given feasible correlation matrix, there are exactly one or two or more parameter sets explaining the observed matrix, is hard for $\forall R$, the co-class of the existential theory of the reals. In particular, this problem is $coNP$-hard. To our best knowledge, this is the first hardness result for some notion of identifiability.
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- 2024
5. Solving the Product Breakdown Structure Problem with constrained QAOA
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Zander, René, Seidel, Raphael, Inajetovic, Matteo, Steinmann, Niklas, and Petrič, Matic
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Quantum Physics - Abstract
Constrained optimization problems, where not all possible variable assignments are feasible solutions, comprise numerous practically relevant optimization problems such as the Traveling Salesman Problem (TSP), or portfolio optimization. Established methods such as quantum annealing or vanilla QAOA usually transform the problem statement into a QUBO (Quadratic Unconstrained Binary Optimization) form, where the constraints are enforced by auxiliary terms in the QUBO objective. Consequently, such approaches fail to utilize the additional structure provided by the constraints. In this paper, we present a method for solving the industry relevant Product Breakdown Structure problem. Our solution is based on constrained QAOA, which by construction never explores the part of the Hilbert space that represents solutions forbidden by the problem constraints. The size of the search space is thereby reduced significantly. We experimentally show that this approach has not only a very favorable scaling behavior, but also appears to suppress the negative effects of Barren Plateaus., Comment: 13 pages
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- 2024
6. Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers
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Seidel, Raphael, Bock, Sebastian, Zander, René, Petrič, Matic, Steinmann, Niklas, Tcholtchev, Nikolay, and Hauswirth, Manfred
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Quantum Physics ,Computer Science - Programming Languages - Abstract
While significant progress has been made on the hardware side of quantum computing, support for high-level quantum programming abstractions remains underdeveloped compared to classical programming languages. In this article, we introduce Qrisp, a framework designed to bridge several gaps between high-level programming paradigms in state-of-the-art software engineering and the physical reality of today's quantum hardware. The framework aims to provide a systematic approach to quantum algorithm development such that they can be effortlessly implemented, maintained and improved. We propose a number of programming abstractions that are inspired by classical paradigms, yet consistently focus on the particular needs of a quantum developer. Unlike many other high-level language approaches, Qrisp's standout feature is its ability to compile programs to the circuit level, making them executable on most existing physical backends. The introduced abstractions enable the Qrisp compiler to leverage algorithm structure for increased compilation efficiency. Finally, we present a set of code examples, including an implementation of Shor's factoring algorithm. For the latter, the resulting circuit shows significantly reduced quantum resource requirements, strongly supporting the claim that systematic quantum algorithm development can give quantitative benefits.
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- 2024
7. Decoding moral judgement from text: a pilot study
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Gherman, Diana E. and Zander, Thorsten O.
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Quantitative Biology - Neurons and Cognition ,Computer Science - Computation and Language ,Computer Science - Human-Computer Interaction - Abstract
Moral judgement is a complex human reaction that engages cognitive and emotional dimensions. While some of the morality neural correlates are known, it is currently unclear if we can detect moral violation at a single-trial level. In a pilot study, here we explore the feasibility of moral judgement decoding from text stimuli with passive brain-computer interfaces. For effective moral judgement elicitation, we use video-audio affective priming prior to text stimuli presentation and attribute the text to moral agents. Our results show that further efforts are necessary to achieve reliable classification between moral congruency vs. incongruency states. We obtain good accuracy results for neutral vs. morally-charged trials. With this research, we try to pave the way towards neuroadaptive human-computer interaction and more human-compatible large language models (LLMs), Comment: 7 pages, 2 figures, conference
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- 2024
8. AdjointDEIS: Efficient Gradients for Diffusion Models
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Blasingame, Zander W. and Liu, Chen
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
The optimization of the latents and parameters of diffusion models with respect to some differentiable metric defined on the output of the model is a challenging and complex problem. The sampling for diffusion models is done by solving either the probability flow ODE or diffusion SDE wherein a neural network approximates the score function or related quantity, allowing a numerical ODE/SDE solver to be used. However, na\"ive backpropagation techniques are memory intensive, requiring the storage of all intermediate states, and face additional complexity in handling the injected noise from the diffusion term of the diffusion SDE. We propose a novel method based on the stochastic adjoint sensitivity method to calculate the gradientwith respect to the initial noise, conditional information, and model parameters by solving an additional SDE whose solution is the gradient of the diffusion SDE. We exploit the unique construction of diffusion SDEs to further simplify the formulation of the adjoint diffusion SDE and use a change-of-variables to simplify the solution to an exponentially weighted integral. Using this formulation we derive a custom solver for the adjoint SDE as well as the simpler adjoint ODE. The proposed adjoint diffusion solvers can efficiently compute the gradients for both the probability flow ODE and diffusion SDE for latents and parameters of the model. Lastly, we demonstrate the effectiveness of the adjoint diffusion solvers onthe face morphing problem., Comment: Initial pre-print
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- 2024
9. Probabilistic and Causal Satisfiability: the Impact of Marginalization
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Dörfler, Julian, van der Zander, Benito, Bläser, Markus, and Liskiewicz, Maciej
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Computer Science - Artificial Intelligence ,Computer Science - Computational Complexity - Abstract
The framework of Pearl's Causal Hierarchy (PCH) formalizes three types of reasoning: observational, interventional, and counterfactual, that reflect the progressive sophistication of human thought regarding causation. We investigate the computational complexity aspects of reasoning in this framework focusing mainly on satisfiability problems expressed in probabilistic and causal languages across the PCH. That is, given a system of formulas in the standard probabilistic and causal languages, does there exist a model satisfying the formulas? The resulting complexity changes depending on the level of the hierarchy as well as the operators allowed in the formulas (addition, multiplication, or marginalization). We focus on formulas involving marginalization that are widely used in probabilistic and causal inference, but whose complexity issues are still little explored. Our main contribution are the exact computational complexity results showing that linear languages (allowing addition and marginalization) yield NP^PP-, PSPACE-, and NEXP-complete satisfiability problems, depending on the level of the PCH. Moreover, we prove that the problem for the full language (allowing additionally multiplication) is complete for the class succ$\exists$R for languages on the highest, counterfactual level, which extends previous results for the lower levels of the PCH. Finally, we consider constrained models that are restricted to a given Bayesian network, a Directed Acyclic Graph structure, or a small polynomial size. The complexity of languages on the interventional level is increased to the complexity of counterfactual languages without such a constraint, that is, linear languages become NEXP-complete. On the other hand, the complexity on the counterfactual level does not change. The constraint on the size reduces the complexity of the interventional and counterfactual languages to NEXP-complete., Comment: update adds complexity results involving a graph structure; submitted to NIPS
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- 2024
10. The Existential Theory of the Reals with Summation Operators
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Bläser, Markus, Dörfler, Julian, Liskiewicz, Maciej, and van der Zander, Benito
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Computer Science - Computational Complexity ,Computer Science - Logic in Computer Science - Abstract
To characterize the computational complexity of satisfiability problems for probabilistic and causal reasoning within the Pearl's Causal Hierarchy, arXiv:2305.09508 [cs.AI] introduce a new natural class, named succ-$\exists$R. This class can be viewed as a succinct variant of the well-studied class $\exists$R based on the Existential Theory of the Reals (ETR). Analogously to $\exists$R, succ-$\exists$R is an intermediate class between NEXP and EXPSPACE, the exponential versions of NP and PSPACE. The main contributions of this work are threefold. Firstly, we characterize the class succ-$\exists$R in terms of nondeterministic real RAM machines and develop structural complexity theoretic results for real RAMs, including translation and hierarchy theorems. Notably, we demonstrate the separation of $\exists$R and succ-$\exists$R. Secondly, we examine the complexity of model checking and satisfiability of fragments of existential second-order logic and probabilistic independence logic. We show succ-$\exists$R- completeness of several of these problems, for which the best-known complexity lower and upper bounds were previously NEXP-hardness and EXPSPACE, respectively. Thirdly, while succ-$\exists$R is characterized in terms of ordinary (non-succinct) ETR instances enriched by exponential sums and a mechanism to index exponentially many variables, in this paper, we prove that when only exponential sums are added, the corresponding class $\exists$R^{\Sigma} is contained in PSPACE. We conjecture that this inclusion is strict, as this class is equivalent to adding a VNP-oracle to a polynomial time nondeterministic real RAM. Conversely, the addition of exponential products to ETR, yields PSPACE. Additionally, we study the satisfiability problem for probabilistic reasoning, with the additional requirement of a small model and prove that this problem is complete for $\exists$R^{\Sigma}.
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- 2024
11. Does an Immigrant Teacher Help Immigrant Students Cope with Negative Stereotypes? Preservice Teachers' and School Students' Perceptions of Teacher Bias and Motivational Support, as Well as Stereotype Threat Effects on Immigrant Students' Learning
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Madita Frühauf, Johanna Hildebrandt, Theresa Mros, Lysann Zander, Nele McElvany, and Bettina Hannover
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Can immigrant school students profit from an immigrant teacher sharing their minority background? We investigate preservice teachers' (Study 1; M[subscript age] = 26.29 years; 75.2% female) and school students' (Study 2; M[subscript age] = 14.88 years; 49.9% female) perceptions of a teacher as well as immigrant school students' learning gains (Study 2) by comparing four experimental video conditions in which a female teacher with a Turkish or German name instructs school students in a task while either saying that learning gains differed (stereotype activation) or did not differ (no stereotype activation) between immigrant and non-immigrant students. Study 1 shows that preservice teachers, regardless of their own cultural background, perceived the Turkish origin teacher as less biased, even when she voiced the stereotype, and as more motivationally supportive of school students in general than the German origin teacher. Study 2 shows that in contrast, among school students, the minority teacher was not perceived as less biased than the majority teacher. Rather, immigrant school students, in particular those with Turkish roots, were more concerned than students of the German majority that the teacher--irrespective of her background--was biased. Interestingly, these differences between students from different backgrounds disappeared when the teacher said that learning gains differed between immigrant and non-immigrant students. Immigrant school students of non-Turkish backgrounds, but not Turkish origin students suffered in their learning when instructed by the Turkish origin teacher who voiced the stereotype. We discuss implications for teacher recruitment.
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- 2024
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12. The Impact of Print-Scanning in Heterogeneous Morph Evaluation Scenarios
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Neddo, Richard E., Blasingame, Zander W., and Liu, Chen
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are particularly susceptible to attacks when the morphs are subjected to print-scanning to mask the artifacts generated during the morphing process. We investigate the impact of print-scanning on morphing attack detection through a series of evaluations on heterogeneous morphing attack scenarios. Our experiments show that we can increase the Mated Morph Presentation Match Rate (MMPMR) by up to 8.48%. Furthermore, when a Single-image Morphing Attack Detection (S-MAD) algorithm is not trained to detect print-scanned morphs the Morphing Attack Classification Error Rate (MACER) can increase by up to 96.12%, indicating significant vulnerability., Comment: Accepted as a special sessions paper at IJCB 2024
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- 2024
13. Greedy-DiM: Greedy Algorithms for Unreasonably Effective Face Morphs
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Blasingame, Zander W. and Liu, Chen
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Morphing attacks are an emerging threat to state-of-the-art Face Recognition (FR) systems, which aim to create a single image that contains the biometric information of multiple identities. Diffusion Morphs (DiM) are a recently proposed morphing attack that has achieved state-of-the-art performance for representation-based morphing attacks. However, none of the existing research on DiMs have leveraged the iterative nature of DiMs and left the DiM model as a black box, treating it no differently than one would a Generative Adversarial Network (GAN) or Varational AutoEncoder (VAE). We propose a greedy strategy on the iterative sampling process of DiM models which searches for an optimal step guided by an identity-based heuristic function. We compare our proposed algorithm against ten other state-of-the-art morphing algorithms using the open-source SYN-MAD 2022 competition dataset. We find that our proposed algorithm is unreasonably effective, fooling all of the tested FR systems with an MMPMR of 100%, outperforming all other morphing algorithms compared., Comment: Accepted as a conference paper at IJCB 2024
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- 2024
14. Spatially Selective Reconfigurable Intelligent Surfaces Through Element Permutation
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Rusek, Fredrik, Flordelis, Jose, Zhao, Kun, Bengtsson, Erik, and Zander, Olof
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Electrical Engineering and Systems Science - Signal Processing - Abstract
A standard reconfigurable intelligent surface (RIS) can be configured to reflect signals from an arbitrary impinging direction to an arbitrary outgoing direction. However, if a signal impinges from any other direction, said signal is reflected, with full beamforming gain, to a specific direction, which is easily determined. The goal of this paper is to propose a RIS which \emph{only} reflects signals from the configured impinging direction. This can be accomplished by a RIS architecture that permutes the antenna elements in the sense that a signal is re-radiated from a different antenna than the one receiving the signal. We analytically prove this fact, and also discuss several variants and hardware implementations., Comment: ICC 2024, 6 pages, 4 figures
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- 2024
15. Set the Clock: Temporal Alignment of Pretrained Language Models
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Zhao, Bowen, Brumbaugh, Zander, Wang, Yizhong, Hajishirzi, Hannaneh, and Smith, Noah A.
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Computer Science - Computation and Language - Abstract
Language models (LMs) are trained on web text originating from many points in time and, in general, without any explicit temporal grounding. This work investigates the temporal chaos of pretrained LMs and explores various methods to align their internal knowledge to a target time, which we call "temporal alignment." To do this, we first automatically construct a dataset containing 20K time-sensitive questions and their answers for each year from 2000 to 2023. Based on this dataset, we empirically show that pretrained LMs (e.g., LLaMa2), despite having a recent pretraining cutoff (e.g., 2022), mostly answer questions using earlier knowledge (e.g., in 2019). We then develop several methods, from prompting to finetuning, to align LMs to use their most recent knowledge when answering questions, and investigate various factors in this alignment. Our experiments demonstrate that aligning LLaMa2 to the year 2022 can enhance its performance by up to 62% according to that year's answers. This improvement occurs even without explicitly mentioning time information, indicating the possibility of aligning models' internal sense of time after pretraining. Finally, we find that alignment to a historical time is also possible, with up to 2.8$\times$ the performance of the unaligned LM in 2010 if finetuning models to that year. These findings hint at the sophistication of LMs' internal knowledge organization and the necessity of tuning them properly., Comment: Accepted as Findings of ACL 2024. Our code and data is available at https://github.com/yizhongw/llm-temporal-alignment
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- 2024
16. Quantum Backtracking in Qrisp Applied to Sudoku Problems
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Seidel, Raphael, Zander, René, Petrič, Matic, Steinmann, Niklas, Liu, David Q., Tcholtchev, Nikolay, and Hauswirth, Manfred
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Quantum Physics ,Computer Science - Data Structures and Algorithms ,Computer Science - Programming Languages - Abstract
The quantum backtracking algorithm proposed by Ashley Montanaro raised considerable interest, as it provides a quantum speed-up for a large class of classical optimization algorithms. It does not suffer from Barren-Plateaus and transfers well into the fault-tolerant era, as it requires only a limited number of arbitrary angle gates. Despite its potential, the algorithm has seen limited implementation efforts, presumably due to its abstract formulation. In this work, we provide a detailed instruction on implementing the quantum step operator for arbitrary backtracking instances. For a single controlled diffuser of a binary backtracking tree with depth n, our implementation requires only $6n+14$ CX gates. We detail the process of constructing accept and reject oracles for Sudoku problems using our interface to quantum backtracking. The presented code is written using Qrisp, a high-level quantum programming language, making it executable on most current physical backends and simulators. Subsequently, we perform several simulator based experiments and demonstrate solving 4x4 Sudoku instances with up to 9 empty fields. This is, to the best of our knowledge, the first instance of a compilable implementation of this generality, marking a significant and exciting step forward in quantum software engineering.
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- 2024
17. Benchmarking Multipartite Entanglement Generation with Graph States
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Zander, René and Becker, Colin Kai-Uwe
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Quantum Physics - Abstract
As quantum computing technology slowly matures and the number of available qubits on a QPU gradually increases, interest in assessing the capabilities of quantum computing hardware in a scalable manner is growing. One of the key properties for quantum computing is the ability to generate multipartite entangled states. In this paper, aspects of benchmarking entanglement generation capabilities of noisy intermediate-scale quantum (NISQ) devices are discussed based on the preparation of graph states and the verification of entanglement in the prepared states. Thereby, we use entanglement witnesses that are specifically suited for a scalable experiment design. This choice of entanglement witnesses can detect A) bipartite entanglement and B) genuine multipartite entanglement for graph states with constant two measurement settings if the prepared graph state is based on a 2-colorable graph, e.g., a square grid graph or one of its subgraphs. With this, we experimentally verify that a fully bipartite entangled state can be prepared on a 127-qubit IBM Quantum superconducting QPU, and genuine multipartite entanglement can be detected for states of up to 23 qubits with quantum readout error mitigation., Comment: 13 pages
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- 2024
18. Testing the Number of Neutrino Species with a Global Fit of Neutrino Data
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Ettengruber, Manuel, Zander, Alan, and Eller, Philipp
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High Energy Physics - Phenomenology ,High Energy Physics - Experiment ,Nuclear Theory - Abstract
We present the first experimental constraints on models with many additional neutrino species in an analysis of current neutrino data. These types of models are motivated as a solution to the hierarchy problem by lowering the species scale of gravity to TeV. Additionally, they offer a natural mechanism to generate small neutrino masses and provide interesting dark matter candidates. This study analyzes data from DayaBay, KamLAND, MINOS, NOvA and KATRIN. We do not find evidence for the presence of any additional neutrino species, therefore we report lower bounds on the allowed number of neutrino species realized in nature. For the normal/inverted neutrino mass ordering, we can give a lower bound on the number of neutrino species of O(30) and O(100), respectively, over a large range of the parameter space., Comment: 8 pages, 4 figures
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- 2024
19. Primary CSF-lymphatic fistula: a previously unknown cause of spontaneous intracranial hypotension
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Lützen, Niklas, Wolf, Katharina, El Rahal, Amir, Volz, Florian, Demerath, Theo, Zander, Charlotte, Pieper, Claus Christian, Schwabenland, Marius, Urbach, Horst, and Beck, Jürgen
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- 2024
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20. Spinal dementia: Don’t miss it, it’s treatable
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Urbach, Horst, El Rahal, A, Wolf, K, Zander, C, Demerath, T, Volz, F, Beck, J, and Lützen, N
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- 2024
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21. Modeling of anticipation using instance-based learning: application to automation surprise in aviation using passive BCI and eye-tracking data
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Klaproth, Oliver W., Dietz, Emmanuelle, Pawlitzki, Juliane, Krol, Laurens R., Zander, Thorsten O., and Russwinkel, Nele
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- 2024
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22. Modelling Alternative Economic Incentive Schemes for Semi-Natural Grassland Conservation in Estonia
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Nishizawa, Takamasa, Schuler, Johannes, Bethwell, Claudia, Glemnitz, Michael, Semm, Maaria, Suškevičs, Monika, Hämäläinen, Laura, Sepp, Kalev, Värnik, Rando, Uthes, Sandra, Aurbacher, Joachim, and Zander, Peter
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- 2024
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23. Incidence and risk factors for HIV-tuberculosis coinfection in the Cologne–Bonn region: a retrospective cohort study
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Suárez, Isabelle, Rauschning, Dominic, Schüller, Cora, Hagemeier, Anna, Stecher, Melanie, Lehmann, Clara, Schommers, Philipp, Schlabe, Stefan, Vehreschild, Jörg-Janne, Koll, Carolin, Schwarze-Zander, Carolynne, Wasmuth, Jan-Christian, Klingmüller, Angela, Rockstroh, Jürgen Kurt, Fätkenheuer, Gerd, Boesecke, Christoph, and Rybniker, Jan
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- 2024
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24. Linking institutional context to the community and career embeddedness of skilled migrants: The role of destination- and origin-country identifications
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Stahl, Günter K., Akkan, Eren, Reiche, B. Sebastian, Hajro, Aida, Zellmer-Bruhn, Mary, Lazarova, Mila, Richter, Nicole Franziska, Caprar, Dan V., Zikic, Jelena, Björkman, Ingmar, Brewster, Chris, Cerdin, Jean-Luc, Clegg, Callen C., Davoine, Eric, Koveshnikov, Alexei, Mayrhofer, Wolfgang, and Zander, Lena
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- 2024
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25. Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction
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Singh, Geethen, Moncrieff, Glenn, Venter, Zander, Cawse-Nicholson, Kerry, Slingsby, Jasper, and Robinson, Tamara B
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Unreliable predictions can occur when using artificial intelligence (AI) systems with negative consequences for downstream applications, particularly when employed for decision-making. Conformal prediction provides a model-agnostic framework for uncertainty quantification that can be applied to any dataset, irrespective of its distribution, post hoc. In contrast to other pixel-level uncertainty quantification methods, conformal prediction operates without requiring access to the underlying model and training dataset, concurrently offering statistically valid and informative prediction regions, all while maintaining computational efficiency. In response to the increased need to report uncertainty alongside point predictions, we bring attention to the promise of conformal prediction within the domain of Earth Observation (EO) applications. To accomplish this, we assess the current state of uncertainty quantification in the EO domain and found that only 20% of the reviewed Google Earth Engine (GEE) datasets incorporated a degree of uncertainty information, with unreliable methods prevalent. Next, we introduce modules that seamlessly integrate into existing GEE predictive modelling workflows and demonstrate the application of these tools for datasets spanning local to global scales, including the Dynamic World and Global Ecosystem Dynamics Investigation (GEDI) datasets. These case studies encompass regression and classification tasks, featuring both traditional and deep learning-based workflows. Subsequently, we discuss the opportunities arising from the use of conformal prediction in EO. We anticipate that the increased availability of easy-to-use implementations of conformal predictors, such as those provided here, will drive wider adoption of rigorous uncertainty quantification in EO, thereby enhancing the reliability of uses such as operational monitoring and decision making.
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- 2024
26. New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms
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Abboud, Amir, Fischer, Nick, Kelley, Zander, Lovett, Shachar, and Meka, Raghu
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Computer Science - Data Structures and Algorithms - Abstract
We revisit the fundamental Boolean Matrix Multiplication (BMM) problem. With the invention of algebraic fast matrix multiplication over 50 years ago, it also became known that BMM can be solved in truly subcubic $O(n^\omega)$ time, where $\omega<3$; much work has gone into bringing $\omega$ closer to $2$. Since then, a parallel line of work has sought comparably fast combinatorial algorithms but with limited success. The naive $O(n^3)$-time algorithm was initially improved by a $\log^2{n}$ factor [Arlazarov et al.; RAS'70], then by $\log^{2.25}{n}$ [Bansal and Williams; FOCS'09], then by $\log^3{n}$ [Chan; SODA'15], and finally by $\log^4{n}$ [Yu; ICALP'15]. We design a combinatorial algorithm for BMM running in time $n^3 / 2^{\Omega(\sqrt[7]{\log n})}$ -- a speed-up over cubic time that is stronger than any poly-log factor. This comes tantalizingly close to refuting the conjecture from the 90s that truly subcubic combinatorial algorithms for BMM are impossible. This popular conjecture is the basis for dozens of fine-grained hardness results. Our main technical contribution is a new regularity decomposition theorem for Boolean matrices (or equivalently, bipartite graphs) under a notion of regularity that was recently introduced and analyzed analytically in the context of communication complexity [Kelley, Lovett, Meka; arXiv'23], and is related to a similar notion from the recent work on $3$-term arithmetic progression free sets [Kelley, Meka; FOCS'23]., Comment: To appear at STOC 2024
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- 2023
27. Partydroge Lachgas
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Ziegenfuß, Thomas and Zander, Rolf
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- 2024
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28. BiodivPortal: Enabling Semantic Services for Biodiversity within the German National Research Data Infrastructure
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Karam, Naouel, Fillies, Jan, Jonquet, Clement, Bouazzouni, Syphax, Löffler, Felicitas, Zander, Franziska, König-Ries, Birgitta, Güntsch, Anton, Diepenbroek, Michael, and Paschke, Adrian
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- 2024
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29. Does vaginal bacterial colonization contribute to preterm birth in women with asymptomatic shortened cervix?
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Steetskamp, J., Zander, M., Laufs, V., Elger, T., Hasenburg, A., and Skala, C.
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- 2024
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30. Does overweight and obesity have an impact on delivery mode and peripartum outcome in breech presentation? A FRABAT cohort study
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Jennewein, Lukas, Agel, Lena, Hoock, Samira Catharina, Hentrich, Anna Elisabeth, Louwen, Frank, and Zander, Nadja
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- 2024
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31. The influence of epidural anesthesia in pregnancies with scheduled vaginal breech delivery at term: a hospital-based retrospective analysis
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Allert, Roman, Brüggmann, Dörthe, Raimann, Florian J., Zander, Nadja, Louwen, Frank, and Jennewein, Lukas
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- 2024
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32. Using best-worst scaling to inform agroecological interventions in Western Kenya
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Zander, Kerstin K., Drucker, Adam G., Aluso, Lillian, Mengistu, Dejene K., Fadda, Carlo, Termote, Céline, and Davis, Kristin
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- 2024
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33. Aerobic and anaerobic mineralisation of sediment organic matter in the tidal River Elbe
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Gebert, J. and Zander, F.
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- 2024
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34. Vorschlag für ein Verfahren zur Teilnahme an intensiv- und notfallmedizinischen Studien bei nichteinwilligungsfähigen Patient*innen (Kölner Modell)
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Kochanek, M., Grass, G., Böll, B., Eichenauer, D. A., Shimabukuro-Vornhagen, A., Hallek, M., Zander, T., Mertens, J., and Voltz, R.
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- 2024
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35. Leveraging the potential of the German operating room benchmarking initiative for planning: A ready-to-use surgical process data set
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Korzhenevich, Grigory and Zander, Anne
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- 2024
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36. Fast-DiM: Towards Fast Diffusion Morphs
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Blasingame, Zander W. and Liu, Chen
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
Diffusion Morphs (DiM) are a recent state-of-the-art method for creating high quality face morphs; however, they require a high number of network function evaluations (NFE) to create the morphs. We propose a new DiM pipeline, Fast-DiM, which can create morphs of a similar quality but with fewer NFE. We investigate the ODE solvers used to solve the Probability Flow ODE and the impact they have on the the creation of face morphs. Additionally, we employ an alternative method for encoding images into the latent space of the Diffusion model by solving the Probability Flow ODE as time runs forwards. Our experiments show that we can reduce the NFE by upwards of 85% in the encoding process while experiencing only 1.6\% reduction in Mated Morph Presentation Match Rate (MMPMR). Likewise, we showed we could cut NFE, in the sampling process, in half with only a maximal reduction of 0.23% in MMPMR., Comment: Accepted as a paper in IEEE Security and Privacy
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- 2023
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37. A new meteor detection application robust to camera movements
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Ciocan, Clara, Kandeepan, Mathuran, Cassagne, Adrien, Vaubaillon, Jeremie, Zander, Fabian, and Lacassagne, Lionel
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
This article presents a new tool for the automatic detection of meteors. Fast Meteor Detection Toolbox (FMDT) is able to detect meteor sightings by analyzing videos acquired by cameras onboard weather balloons or within airplane with stabilization. The challenge consists in designing a processing chain composed of simple algorithms, that are robust to the high fluctuation of the videos and that satisfy the constraints on power consumption (10 W) and real-time processing (25 frames per second)., Comment: in French language, Groupe de Recherche et d'{\'E}tudes de Traitement du Signal et des Images (GRETSI), Aug 2023, Grenoble, France
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- 2023
38. Explicit separations between randomized and deterministic Number-on-Forehead communication
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Kelley, Zander, Lovett, Shachar, and Meka, Raghu
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Computer Science - Computational Complexity ,Mathematics - Combinatorics ,68Q11, 68Q17 ,F.2.2 ,F.1.3 - Abstract
We study the power of randomness in the Number-on-Forehead (NOF) model in communication complexity. We construct an explicit 3-player function $f:[N]^3 \to \{0,1\}$, such that: (i) there exist a randomized NOF protocol computing it that sends a constant number of bits; but (ii) any deterministic or nondeterministic NOF protocol computing it requires sending about $(\log N)^{1/3}$ many bits. This exponentially improves upon the previously best-known such separation. At the core of our proof is an extension of a recent result of the first and third authors on sets of integers without 3-term arithmetic progressions into a non-arithmetic setting.
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- 2023
39. How Many Dark Neutrino Sectors Does Cosmology Allow?
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Zander, Alan, Ettengruber, Manuel, and Eller, Philipp
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High Energy Physics - Phenomenology - Abstract
We present the very first constraints on the number of Standard Model (SM) copies with an additional Dirac right-handed neutrino. From cosmology, we are able to pose strong limits on large regions of the parameter space. Moreover, we show that it is possible to account for the right dark matter density in form of stable particles from the dark sectors.
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- 2023
40. The rLVS ΔcapB/iglABC vaccine provides potent protection in Fischer rats against inhalational tularemia caused by various virulent Francisella tularensis strains.
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Mlynek, Kevin, Cline, Curtis, Biryukov, Sergei, Toothman, Ronald, Bachert, Beth, Klimko, Christopher, Shoe, Jennifer, Hunter, Melissa, Hedrick, Zander, Dankmeyer, Jennifer, Mou, Sherry, Fetterer, David, Qiu, Ju, Lee, Eric, Cote, Christopher, Jia, Qingmei, Bozue, Joel, and Horwitz, Marcus
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Francisella tularensis ,LVS (Live Vaccine Strain) ,aerosol challenge ,animal model ,rat ,tularemia ,vaccines ,Rats ,Animals ,Mice ,Francisella tularensis ,Tularemia ,Rats ,Inbred F344 ,Bacterial Vaccines ,Vaccines ,Attenuated ,Mice ,Inbred BALB C ,Disease Models ,Animal - Abstract
Francisella tularensis is one of the several biothreat agents for which a licensed vaccine is needed. To ensure vaccine protection is achieved across a range of virulent F. tularensis strains, we assembled and characterized a panel of F. tularensis isolates to be utilized as challenge strains. A promising tularemia vaccine candidate is rLVS ΔcapB/iglABC (rLVS), in which the vector is the LVS strain with a deletion in the capB gene and which additionally expresses a fusion protein comprising immunodominant epitopes of proteins IglA, IglB, and IglC. Fischer rats were immunized subcutaneously 1-3 times at 3-week intervals with rLVS at various doses. The rats were exposed to a high dose of aerosolized Type A strain Schu S4 (FRAN244), a Type B strain (FRAN255), or a tick derived Type A strain (FRAN254) and monitored for survival. All rLVS vaccination regimens including a single dose of 107 CFU rLVS provided 100% protection against both Type A strains. Against the Type B strain, two doses of 107 CFU rLVS provided 100% protection, and a single dose of 107 CFU provided 87.5% protection. In contrast, all unvaccinated rats succumbed to aerosol challenge with all of the F. tularensis strains. A robust Th1-biased antibody response was induced in all vaccinated rats against all F. tularensis strains. These results demonstrate that rLVS ΔcapB/iglABC provides potent protection against inhalational challenge with either Type A or Type B F. tularensis strains and should be considered for further analysis as a future tularemia vaccine.
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- 2023
41. Phase Ib/II Study of the Efficacy and Safety of Binimetinib (MEK162) Plus Panitumumab for Mutant or Wild-Type RAS Metastatic Colorectal Cancer.
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Van Cutsem, Eric, Yaeger, Rona, Delord, Jean-Pierre, Tabernero, Josep, Siu, Lillian, Ducreux, Michel, Siena, Salvatore, Elez, Elena, Kasper, Stefan, Zander, Thomas, Steeghs, Neeltje, Murphy, Danielle, Edwards, Michelle, and Wainberg, Zev
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RAS mutation ,RAS wild type ,binimetinib ,colorectal cancer ,panitumumab ,Humans ,Panitumumab ,Colorectal Neoplasms ,Benzimidazoles ,Colonic Neoplasms ,Rectal Neoplasms ,ErbB Receptors ,Antineoplastic Combined Chemotherapy Protocols ,Proto-Oncogene Proteins p21(ras) - Abstract
INTRODUCTION: Activating RAS gene mutations occur in approximately 55% of patients with metastatic colorectal cancer (mCRC) and are associated with poorer clinical outcomes due to epidermal growth factor receptor (EGFR) blockade resistance. Combined EGFR and mitogen-activated protein kinase (MEK) inhibition may extend response to EGFR inhibition and overcome acquired resistance. This phase Ib/II dose escalation trial evaluated the safety and activity of dual inhibition with binimetinib (MEK1/2 inhibitor) and panitumumab (EGFR inhibitor [EGFRi]) in patients with RAS mutant or BRAF wild type (WT)/RAS WT mCRC. METHODS: Phase Ib dose escalation started with binimetinib 45 mg twice daily plus panitumumab 6 mg/kg administered every 2 weeks. In the phase II study, patients with measurable mCRC were enrolled into 4 groups based on previous anti-EGFR monoclonal antibody therapy and RAS mutational status. RESULTS: No patients in the phase Ib portion (n = 10) had a response; 70% of patients had stable disease. In the phase II portion (n = 43), overall response rate (ORR, confirmed) was 2.3% with one partial response in the RAS WT group, DCR was 30.2%, and median progression-free survival was 1.8 months (95%CI, 1.6-3.3). All patients experienced ≥1 adverse event, with the most common being diarrhea (71.7%), vomiting (52.8%), nausea (50.9%), fatigue (49.1%), dermatitis acneiform (43.4%), and rash (41.5%). Most patients required treatment interruption or dose reduction due to difficulties tolerating treatment. CONCLUSIONS: The combination of binimetinib and panitumumab had substantial toxicity and limited clinical activity for patients with mutant or WT RAS mCRC, independent of EGFRi treatment history (Trial registration: NCT01927341).
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- 2023
42. The association between HIV-1 Tat and Vif amino acid sequence variation, inflammation and Trp-Kyn metabolism: an exploratory investigation
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Monray E. Williams, Levanco K. Asia, Zander Lindeque, and Esmé Jansen van Vuren
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Viral proteins ,Inflammation ,Pathogenesis ,Tryptophan-Kynurenine Pathway ,Metabolomics ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Background HIV-1 has well-established mechanisms to disrupt essential pathways in people with HIV, such as inflammation and metabolism. Moreover, diversity of the amino acid sequences in fundamental HIV-1 proteins including Tat and Vif, have been linked to dysregulating these pathways, and subsequently influencing clinical outcomes in people with HIV. However, the relationship between Tat and Vif amino acid sequence variation and specific immune markers and metabolites of the tryptophan-kynurenine (Trp-Kyn) pathway remains unclear. Therefore, this study aimed to investigate the relationship between Tat/Vif amino acid sequence diversity and Trp-Kyn metabolites (quinolinic acid (QUIN), Trp, kynurenic acid (KA), Kyn and Trp/Kyn ratio), as well as specific immune markers (sCD163, suPAR, IL-6, NGAL and hsCRP) in n = 67 South African cART-naïve people with HIV. Methods Sanger sequencing was used to determine blood-derived Tat/Vif amino acid sequence diversity. To measure Trp-Kyn metabolites, a LC–MS/MS metabolomics platform was employed using a targeted approach. To measure immune markers, Enzyme-linked immunosorbent assays and the Particle-enhanced turbidimetric assay was used. Results After adjusting for covariates, sCD163 (p = 0.042) and KA (p = 0.031) were higher in participants with Tat signatures N24 and R57, respectively, and amino acid variation at position 24 (adj R2 = 0.048, β = -0.416, p = 0.042) and 57 (adj R2 = 0.166, β = 0.535, p = 0.031) of Tat were associated with sCD163 and KA, respectively. Conclusions These preliminary findings suggest that amino acid variation in Tat may have an influence on underlying pathogenic HIV-1 mechanisms and therefore, this line of work merits further investigation.
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- 2024
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43. Minimally Monophyletic Genera Present within Meso- and Macrogenera
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Richard H. Zander
- Subjects
ancestron ,evolution ,macrogenus ,mesogenus ,microgenus ,novon ,Biology (General) ,QH301-705.5 - Abstract
Past efforts to identify and characterize minimally monophyletic groups (microgenera) by deconstructing larger bryophyte genera successfully determined 10 microgenera comprising the moss family Streptotrichaceae. Thirty other microgenera have also been found in the moss family Pottiaceae. A microgenus consists of one ancestral species and, optimally, four immediate descendant species, each of which shares exactly the same ancestral traits. To determine if microgenera were common, evidence of these in larger genera was garnered from published estimates of species per genus in other groups and from molecular cladograms in the moss family Pottiaceae. Both classical mesogenera and cladistically enlarged macrogenera exhibited an internal granularity of one to five species, either as multiple species below the inflection point in the hollow curve of logarithmic graphs of species per genus or as small groups of molecular cladogram branches. Microgenera are basic units of evolution. The constancy of size and monothecy of traits in microgenera give them properties that larger taxonomic groups lack. Sequences of microgenera monophyletic are easily concatenated, adaptational changes may be directly determined, self-similarity across scale allows extended scientific inferences, and traits can be associated with survival across millions of years of environmental perturbation.
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- 2024
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44. Children's Social-Emotional Development during the COVID-19 Pandemic: Protective Effects of the Quality of Children's Home and Preschool Learning Environments
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Elisa Oppermann, Sabine Blaurock, Lysann Zander, and Yvonne Anders
- Abstract
Research Findings: The study examined the development of children's social-emotional problems between 2019 (T1) and winter 2021/22 (T2) during the COVID-19 pandemic, as well as the role of children's home and preschool learning environments. The sample included 228 German children ages 3-7 years at T1 (M[subscript Age] = 5.13, SD = 0.79, 46% female). Results showed an increase in emotional problems between T1 and T2, which was more pronounced among already disadvantaged groups of children from families with lower income and lower educational background. Peer problems increased only among children from families with lower educational backgrounds. The emotional climate of the family and the quality of children's preschool learning environment were identified as protective influences for the development of children's peer problems, but not for children's emotional problems. Practice or Policy: The policy restrictions implemented to slow the spread of the COVID-19 virus had longer-lasting consequences for (some) children's emotional functioning. Efforts should be undertaken to mitigate such detrimental effects by supporting disadvantaged groups of children. In addition, based on the findings regarding the importance of high-quality interactions to prevent the development of social problems among children, policy should establish the conditions for preschool staff to provide high-quality interactions in childcare.
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- 2024
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45. How Do Others Think about My Group? Adolescents' Meta-Stereotypes about Turkish- and German-Origin Students' Subject-Related German and General School Competence
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Jannika Haase, Elisabeth Höhne, Bettina Hannover, Nele McElvany, and Lysann Zander
- Abstract
In Germany, Turkish-origin students face negative competence-related stereotypes held by different groups in society, including teachers at school. While a large body of research has examined stereotypes (i.e., "other-stereotypes") about immigrant students, little is known about their own competence-related "meta-stereotypes," i.e., beliefs regarding the other-stereotypes that outgroup peers hold about them. The present study addresses this research gap by examining Turkish- and German-origin students' meta-stereotypes about two dimensions of competencies not yet investigated, namely Turkish- and German-origin students' subject-related German competence as well as their general school competence using a newly developed instrument combining verbal and non-verbal measures. These assessments are juxtaposed to the evaluations of a group of peers with other immigrant backgrounds (i.e., "others' meta-stereotypes"). In line with previous evidence, we found "positive" meta-stereotypes (as well as other- and others' meta-stereotypes) towards German-origin students reported by all three groups. However, our study is the first that supports the existence of "negative" meta-stereotypes (as well as other- and others' meta-stereotypes) towards Turkish-origin adolescents, again, among all participants. This pattern was particularly pronounced regarding the dimension of subject-related German competence. We discuss the findings' potential relevance for students' self-concepts and intergroup interactions in classrooms.
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- 2024
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46. Data Owner Benefit-Driven Design of People Analytics
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Zander, Patrik and Zieglmeier, Valentin
- Subjects
Computer Science - Human-Computer Interaction ,Computer Science - Software Engineering - Abstract
With increasingly digitalized workplaces, the potential for sophisticated analyses of employee data rises. This increases the relevance of people analytics (PA), which are tools for the behavioral analysis of employees. Despite this potential, the successful usage of PA is hindered by employee concerns. Especially in Europe, where the GDPR or equivalent laws apply, employee consent is required before data can be processed in PA. Therefore, PA can only provide relevant insights if employees are willing to share their data. One potential way of achieving this is the use of appeal strategies. In the design of PA, the core strategy that can be used is the inclusion of data owner benefits, such as automated feedback, that are given to employees in exchange for sharing their own data. In this paper, we examine benefits as an appeal strategy and develop four design principles for the inclusion of benefits in PA. Then, we describe an exemplary set of analyses and benefits, demonstrating how our principles may be put into practice. Based on this exemplary implementation, we describe and discuss the results of a user study ($n = 46$) among employees in the EU and UK. Our study investigates the factors that foster or hinder employees' consent to sharing their data with PA. Then, we introduce our data owner benefits and analyze whether they can positively influence this consent decision. Our introduced data owner benefits were, contrary to our expectations, not suited to motivate our participants to consent to sharing their data. We therefore analyze how participants judge the benefits. Participants generally appreciate having them, confirming the value of including data owner benefits when designing PA. Some of our introduced benefits negatively influenced participants' sharing decision, though, meaning that careful consideration of potential risks is required when conceptualizing them., Comment: Peer-reviewed version accepted for publication in Proceedings of the ACM on Human-Computer Interaction (PACMHCI), EICS issue
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- 2023
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47. The Hardness of Reasoning about Probabilities and Causality
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van der Zander, Benito, Bläser, Markus, and Liśkiewicz, Maciej
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Computational Complexity - Abstract
We study formal languages which are capable of fully expressing quantitative probabilistic reasoning and do-calculus reasoning for causal effects, from a computational complexity perspective. We focus on satisfiability problems whose instance formulas allow expressing many tasks in probabilistic and causal inference. The main contribution of this work is establishing the exact computational complexity of these satisfiability problems. We introduce a new natural complexity class, named succ$\exists$R, which can be viewed as a succinct variant of the well-studied class $\exists$R, and show that the problems we consider are complete for succ$\exists$R. Our results imply even stronger algorithmic limitations than were proven by Fagin, Halpern, and Megiddo (1990) and Moss\'{e}, Ibeling, and Icard (2022) for some variants of the standard languages used commonly in probabilistic and causal inference., Comment: accepted at IJCAI 23
- Published
- 2023
48. How do others think about my group? Adolescents’ meta-stereotypes about Turkish- and German-origin students’ subject-related German and general school competence
- Author
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Haase, Jannika, Höhne, Elisabeth, Hannover, Bettina, McElvany, Nele, and Zander, Lysann
- Published
- 2024
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49. Freiburg Neuropathology Case Conference:: 68-Year-Old Patient with Slurred Speech, Double Vision, and Increasing Gait Disturbance
- Author
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Zander, C., Diebold, M., Shah, M. J., Malzkorn, B., Prinz, M., Urbach, H., Erny, D., and Taschner, C. A.
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- 2024
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50. Managing Provenance Data in Knowledge Graph Management Platforms
- Author
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Kleinsteuber, Erik, Al Mustafa, Tarek, Zander, Franziska, König-Ries, Birgitta, and Babalou, Samira
- Published
- 2024
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