Negative / Null Result ReportOpen accessMathematics
Mirna Džamonja, Saharon Shelah · 1997 · arXiv
This note gives two results on guessing unbounded subsets of lambda^+. The first is a positive result and applies to the situation of lambda regular, while the second is a negative consistency result which applies to the situation of lambda singular. Both results are connected to an earlier result of the same authors in which they showed that a certain version of clubsuit holds at a successor of singular just in ZFC. The first result here shows that that fact can to a certain extent be extended to the successor of singular. The negative result here gives limitations to the extent to which one
Negative / Null Result ReportOpen accessMathematics
H. Beirao da Veiga, F. Crispo · 2010 · arXiv
We consider the problem of the strong convergence, as the viscosity goes to zero, of the solutions to the three-dimensional evolutionary Navier-Stokes equations under a Navier slip-type boundary condition to the solution of the Euler equations under the zero flux boundary condition. In spite of the arbitrarily strong convergence results proved in the flat boundary case, see [4], it was shown in reference [5] that the result is false in general, by constructing an explicit family of smooth initial data in the sphere, for which the result fails. Our aim here is to present a more general, simpler
Negative / Null Result ReportOpen accessComputer Science
Stefan Borgwardt, Rafael Peñaloza · 2015 · arXiv
Fuzzy Description Logics (FDLs) are logic-based formalisms used to represent and reason with vague or imprecise knowledge. It has been recently shown that reasoning in most FDLs using truth values from the interval [0,1] becomes undecidable in the presence of a negation constructor and general concept inclusion axioms. One exception to this negative result are FDLs whose semantics is based on the infinitely valued Gödel t-norm (G). In this paper, we extend previous decidability results for G-IALC to deal also with qualified number restrictions. Our novel approach is based on a combination of t
Negative / Null Result ReportOpen accessComputer Science
Kittiphon Phalakarn, Kittiphop Phalakarn, Vorapong Suppakitpaisarn · 2025 · arXiv
This paper introduces an optimal representation for a right-to-left parallel elliptic curve scalar point multiplication. The right-to-left approach is easier to parallelize than the conventional left-to-right approach. However, unlike the left-to-right approach, there is still no work considering number representations for the right-to-left parallel calculation. By simplifying the implementation by Robert, we devise a mathematical model to capture the computation time of the calculation. Then, for any arbitrary amount of doubling time and addition time, we propose algorithms to generate repres
Negative / Null Result ReportOpen accessPhysics
J. A. Gonzalez, F. S. Guzman · 2011 · arXiv
In order to explore nonlinear effects on the distribution of matter during collisions within the Bose-Einstein condensate (BEC) dark matter model driven by the Schrödinger-Poisson system of equations, we study the head-on collision of structures and focus on the interference pattern formation in the density of matter during the collision process. We explore the possibility that the collision of two structures of fluid matter modeled with an ideal gas equation of state also forms interference patterns and found a negative result. Given that a fluid is the most common flavor of dark matter model
Negative / Null Result ReportOpen accessComputer Science
Jamie Hayes · 2020 · arXiv
Randomized smoothing, a method to certify a classifier's decision on an input is invariant under adversarial noise, offers attractive advantages over other certification methods. It operates in a black-box and so certification is not constrained by the size of the classifier's architecture. Here, we extend the work of Li et al. \cite{li2018second}, studying how the choice of divergence between smoothing measures affects the final robustness guarantee, and how the choice of smoothing measure itself can lead to guarantees in differing threat models. To this end, we develop a method to certify ro
Negative / Null Result ReportOpen accessMathematics
Michel Duprez, Pierre Lissy · 2017 · arXiv
This paper is devoted to studying the null and approximate controllability of two linear coupled parabolic equations posed on a smooth domain of R^N (N>1) with coupling terms of zero and first orders and one control localized in some arbitrary nonempty open subset of the domain. We prove the null controllability under a new sufficient condition and we also provide the first example of a not approximately controllable system in the case where the support of one of the nontrivial first order coupling terms intersects the control domain.
Negative / Null Result ReportOpen accessComputer Science
Tourjana Islam Supti, Israa Abuelezz, Aya Muhanad et al. · 2025 · arXiv
This study investigates the efficacy of role-taking and literacy-based interventions in reducing the influence of appearance cues, such as gender, age, ethnicity, and clothing style, on trust and risk-taking in social engineering contexts. A-4 (Group: Control, Literacy, Persuader, Persuadee) * 2 (Time: Pre, Post) mixed factorial design was implemented over two weeks with 139 participants. The control group received no material. The literacy group attended two sessions focused on how behavior can be similar regardless of appearance cues. The persuader group completed three sessions, learning ho
Negative / Null Result ReportOpen accessComputer Science
E. V. Arbuzova · 2024 · arXiv
The search for supersymmetric partners at Large Hadron Collider revealed negative result. Though, strictly speaking, it does not exclude low energy supersymmetry, but still it leads to strong constraints of the parameter space. Therefore the search for supersymmetric particles at higher energies becomes of interest. It is shown that in $R^2$-modified cosmology heavy particles with the interaction strength typical for supersymmetry could be promising candidates for carriers of dark matter. We consider the heating of the Universe at the post-inflationary stage via particle production by oscillat
Negative / Null Result ReportOpen accessComputer Science
T. Maeno, M. Fujikawa, J. Kataoka et al. · 1995 · arXiv
We have searched for an exotic decay of orthopositronium into a single photon and a short-lived neutral boson in the hitherto unexplored mass region above 900 ${\rm keV}/{\it c}^{2}$, by noting that this decay is one of few remaining candidates which could explain the discrepancy of the orthopositronium decay-rate. A high-resolution measurement of the associated photon energy spectrum was carried out with a germanium detector to search for a sharp peak from this two-body decay. Our negative result provides the upper-limits of\mbox{ }$2.0 \times 10^{-4}$ on the branching ratio of such a decay i
Negative / Null Result ReportOpen accessMathematics
Kevin Barreto, Jiwon Kang, Sang-hyun Kim et al. · 2026 · arXiv
Answering a question of Erdős and Graham, we show that the double exponential growth condition $\limsup_{n\to\infty}a_n^{1/φ^n}=\infty$ for a strictly increasing sequence of positive integers $\{a_n\}_{n=1}^\infty$ is sufficient for the series $\sum_{n=1}^\infty 1/(a_n a_{n+1})$ to have an irrational sum; here $φ$ denotes the golden ratio. We also provide a positive generalization to $\sum_{n=1}^\infty 1/(a_n^{w_0}\cdots a_{n+d-1}^{w_{d-1}})$, and a negative result showing that some of its instances are essentially optimal. The original problem was autonomously solved by the AI agent \emph{Ale
Failed Experiment ReportOpen accessAgricultural and Biological Sciences
M. Khasin, M. I. Dykman, B. Meerson · 2009 · arXiv
We consider optimal vaccination protocol where the vaccine is in short supply. In this case, disease extinction results from a large and rare fluctuation. We show that the probability of such fluctuation can be exponentially increased by vaccination. For periodic vaccination with fixed average rate, the optimal vaccination protocol is model independent and presents a sequence of short pulses. The effect of vaccination can be resonantly enhanced if the pulse period coincides with the characteristic period of the disease dynamics or its multiples. This resonant effect is illustrated using a simp
Negative / Null Result ReportOpen accessComputer Science
Andrew Fish, Alexei Lisitsa · 2014 · arXiv
We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result (i.e. that a knot is the unknot), whilst simultaneously using a model finder to try to establish a negative result (i.e. that the knot is not the unknot). The theorem proving approach utilises equational reasoning, whilst the model finder searches for a minimal size counter-model. We present and compare experimental data using the involutary quandle of the knot,
Negative / Null Result ReportOpen accessComputer Science
A. Rubbia, P. Sala · 2002 · arXiv
The possibility to improve the CERN to Gran Sasso neutrino beam performances for theta_{13} searches is investigated. We show that by an appropriate optimization of the target and focusing optics of the present CNGS design, we can increase the flux of low energy neutrinos by about a factor 5 compared to the current tau optimized focalisation. With the ICARUS 2.35 kton detector at LNGS and in case of negative result, this would allow to improve the limit to sin^22 theta_{13} by an order of magnitude better than the current limit of CHOOZ at Delta m^2 approximately 3 times 10^{-3} eV^2 within 5
Negative / Null Result ReportOpen accessComputer Science
Rohan Jha, Reno Kriz, Benjamin Van Durme · 2026 · arXiv
The XTR (conteXtual Token Retrieval) algorithm is a modification to ColBERT retrieval that avoids the costly step of fully gathering and reranking the candidates' embeddings by imputing their missing similarity scores from the initial token retrieval step. The original work proposes a modified training objective as necessary for effective XTR retrieval, arguing that standard ColBERT token scoring is unsuitable for imputation. In this paper, we replicate both the XTR retrieval algorithm and its modified training objective, and extend the evaluation to knowledge-distillation (KD) training and ef
Negative / Null Result ReportOpen accessComputer Science
Xin Ding, Yongwei Wang, Zuheng Xu · 2023 · arXiv
Continuous Conditional Generative Adversarial Networks (CcGANs) enable generative modeling conditional on continuous scalar variables (termed regression labels). However, they can produce subpar fake images due to limited training data. Although Negative Data Augmentation (NDA) effectively enhances unconditional and class-conditional GANs by introducing anomalies into real training images, guiding the GANs away from low-quality outputs, its impact on CcGANs is limited, as it fails to replicate negative samples that may occur during the CcGAN sampling. We present a novel NDA approach called Dua
Negative / Null Result ReportOpen accessMathematics
Fintan Costello, Paul Watts · 2022 · arXiv
There is a well-known problem in Null Hypothesis Significance Testing: many statistically significant results fail to replicate in subsequent experiments. We show that this problem arises because standard `point-form null' significance tests consider only within-experiment but ignore between-experiment variation, and so systematically underestimate the degree of random variation in results. We give an extension to standard significance testing that addresses this problem by analysing both within- and between-experiment variation. This `distributional null' approach does not underestimate exper
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Damien Ackerer, Natasa Tagasovska, Thibault Vatter · 2019 · arXiv
We present a neural network (NN) approach to fit and predict implied volatility surfaces (IVSs). Atypically to standard NN applications, financial industry practitioners use such models equally to replicate market prices and to value other financial instruments. In other words, low training losses are as important as generalization capabilities. Importantly, IVS models need to generate realistic arbitrage-free option prices, meaning that no portfolio can lead to risk-free profits. We propose an approach guaranteeing the absence of arbitrage opportunities by penalizing the loss using soft const
Methods Dead-EndOpen accessComputer Science
Aytaç Sekmen, Fatih Emre Gunes, Furkan Horoz et al. · 2026 · arXiv
Monocular Depth Estimation (MDE) is crucial for autonomous lunar rover navigation using electro-optical cameras. However, deploying terrestrial MDE networks to the Moon brings a severe domain gap due to harsh shadows, textureless regolith, and zero atmospheric scattering. Existing evaluations rely on analogs that fail to replicate these conditions and lack actual metric ground truth. To address this, we present LuMon, a comprehensive benchmarking framework to evaluate MDE methods for lunar exploration. We introduce novel datasets featuring high-quality stereo ground truth depth from the real C
Negative / Null Result ReportOpen accessPhysics
Naiara Patiño, Nuria Calvet, Gladis Magris et al. · 2026 · arXiv
Magnetospheric accretion is the paradigm for accretion in Classical T-Tauri Stars (CTTS). However, the standard, one-flow magnetospheric accretion model fails to replicate important characteristics such as the observed Balmer decrements. We address this limitation by adopting a model with two axisymmetric magnetospheric accretion flows of different accretion rates and geometries. We calculate the fluxes of the hydrogen $H_α$, $H_β$, and $H_γ$ lines of each flow with the magnetospheric accretion model and use Bayesian statistics to fit the Balmer line fluxes of 139 CTTS in the Orion OB1b subass
Failed Experiment ReportOpen accessComputer Science
Tilman Plehn, Michael Spannowsky, Michihisa Takeuchi · 2011 · arXiv
In time for the first tests on LHC data we introduce a set of improvements and tests of purely kinematic top tagging algorithms. First, we show how different jet algorithms can be used for different transverse momentum regimes. Combining pruning and filtering in the reconstruction can enhance the signal over background ratio significantly, while larger jet radii only give minor improvements. Finally, bottom tagging can be added to the top tagger, but at least for the HEPTopTagger does not improve the kinematic selection algorithm.
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Valentina Macchiati, Piero Mazzarisi, Diego Garlaschelli · 2024 · arXiv
Networks of financial exposures are the key propagators of risk and distress among banks, but their empirical structure is not publicly available because of confidentiality. This limitation has triggered the development of methods of network reconstruction from partial, aggregate information. Unfortunately, even the best methods available fail in replicating the number of directed cycles, which on the other hand play a crucial role in determining graph spectra and hence the degree of network stability and systemic risk. Here we address this challenge by exploiting the hypothesis that the stati
Negative / Null Result ReportOpen accessComputer Science
Mert Albaba, Sammy Christen, Thomas Langarek et al. · 2024 · arXiv
Acquiring complex behaviors is essential for artificially intelligent agents, yet learning these behaviors in high-dimensional settings poses a significant challenge due to the vast search space. Traditional reinforcement learning (RL) requires extensive manual effort for reward function engineering. Inverse reinforcement learning (IRL) uncovers reward functions from expert demonstrations but relies on an iterative process that is often computationally expensive. Imitation learning (IL) provides a more efficient alternative by directly comparing an agent's actions to expert demonstrations; how
Negative / Null Result ReportOpen accessComputer Science
Sarah Ball, Simeon Allmendinger, Frauke Kreuter et al. · 2025 · arXiv
Generative AI (GenAI) is increasingly used in survey contexts to simulate human preferences. While many research endeavors evaluate the quality of synthetic GenAI data by comparing model-generated responses to gold-standard survey results, fundamental questions about the validity and reliability of using LLMs as substitutes for human respondents remain. Our study provides a technical analysis of how demographic attributes and prompt variations influence latent opinion mappings in large language models (LLMs) and evaluates their suitability for survey-based predictions. Using 14 different model
Negative / Null Result ReportOpen accessPhysics
Matthew S. Clement, Nathan A. Kaib, John E. Chambers · 2019 · arXiv
Of the solar system's four terrestrial planets, the origin of Mercury is perhaps the most mysterious. Modern numerical simulations designed to model the dynamics of terrestrial planet formation systematically fail to replicate Mercury; which possesses just 5% the mass of Earth and the highest orbital eccentricity and inclination among the planets. However, Mercury's large iron-rich core and low volatile inventory stand out among the inner planets, and seem to imply a violent collisional origin. Because most algorithms used for simulating terrestrial accretion do not consider the effects of col
Negative / Null Result ReportOpen accessComputer Science
Xun Liang, Huayi Lai, Hanyu Wang et al. · 2025 · arXiv
Large language models (LLMs) have gained significant traction in medical decision support systems, particularly in the context of medical question answering and role-playing simulations. A common practice, Prompt-Based Role Playing (PBRP), instructs models to adopt different clinical roles (e.g., medical students, residents, attending physicians) to simulate varied professional behaviors. However, the impact of such role prompts on model reasoning capabilities remains unclear. This study introduces the RP-Neuron-Activated Evaluation Framework(RPNA) to evaluate whether role prompts induce disti
Negative / Null Result ReportOpen accessComputer Science
Jiarui Xie, Mutahar Safdar, Andrei Mircea et al. · 2024 · arXiv
Machine learning (ML)-based cyber-physical systems (CPSs) have been extensively developed to improve the print quality of additive manufacturing (AM). However, the reproducibility of these systems, as presented in published research, has not been thoroughly investigated due to a lack of formal evaluation methods. Reproducibility, a critical component of trustworthy artificial intelligence, is achieved when an independent team can replicate the findings or artifacts of a study using a different experimental setup and achieve comparable performance. In many publications, critical information nec
Negative / Null Result ReportOpen accessComputer Science
Sungmin Cha, Kyunghyun Cho · 2024 · arXiv
Continual learning (CL) aims to train a model on a sequence of tasks (i.e., a CL scenario) while balancing the trade-off between plasticity (learning new tasks) and stability (retaining prior knowledge). The dominantly adopted conventional evaluation protocol for CL algorithms selects the best hyperparameters (e.g., learning rate, mini-batch size, regularization strengths, etc.) within a given scenario and then evaluates the algorithms using these hyperparameters in the same scenario. However, this protocol has significant shortcomings: it overestimates the CL capacity of algorithms and relies
Negative / Null Result ReportOpen accessComputer Science
Emily L. Aiken, Andre T. Nguyen, Mauricio Santillana · 2019 · arXiv
We introduce the use of a Gated Recurrent Unit (GRU) for influenza prediction at the state- and city-level in the US, and experiment with the inclusion of real-time flu-related Internet search data. We find that a GRU has lower prediction error than current state-of-the-art methods for data-driven influenza prediction at time horizons of over two weeks. In contrast with other machine learning approaches, the inclusion of real-time Internet search data does not improve GRU predictions.
Negative / Null Result ReportOpen accessEngineering
Di Wu, Yifei Jia, Siyuan Li et al. · 2025 · arXiv
Neurophysiological decoding, fundamental to advancing brain-computer interface (BCI) technologies, has significantly benefited from recent advances in deep learning. However, existing decoding approaches largely remain constrained to single-task scenarios and individual subjects, limiting their broader applicability and generalizability. Efforts towards creating large-scale neurophysiological foundation models have shown promise, but continue to struggle with significant challenges due to pervasive data heterogeneity across subjects and decoding tasks. Simply increasing model parameters and da
