A searchable index of real negative results, null findings, and replication failures from the published literature — so you can learn what didn't work before repeating it.
WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record (title, authors, DOI) compiled from open scholarly databases, with the abstract shown in full only where the paper is openly licensed (e.g. Creative Commons); otherwise a short excerpt is shown for reference under fair use. WASTE classifies each work by failure type; classifications are automated and approximate.
1757 results in Negative / Null Result Report for "Mpro" · page 16 of 59
Andreas Plate, Stefania Di Gangi, Christian Garzoni et al. · 2024 · Scientific Reports
Abstract Patient information leaflets can reduce antibiotic prescription rates by improving knowledge and encouraging shared decision making (SDM) in patients with respiratory tract infections (RTI). The effect of these interventions in…
Benedict Kjaergaard, Hans O. Holdgaard, Sigridur O. Magnusdottir et al. · 2020 · Journal of Translational Medicine
Abstract Background An impedance threshold device (ITD) was developed to increase venous return to the heart and therefore increase cardiac output and organ blood flow during cardiopulmonary rescue (CPR). Basic CPR aims to maintain…
Matthias Brockmeyer, Sebastian Lott, Jonas Stroeder et al. · 2019 · Journal of Experimental Orthopaedics
Abstract Background The aim of this study was to develop two simple positioning devices for anteroposterior pelvis radiographs and to evaluate their effect on accuracy of the radiographs for assessment of the acetabular orientation…
Nicola Arrighi, Alessandro Antonelli, Tiziano Zanotelli et al. · 2011 · Urologia Journal
Objectives During the last 3 decades ultrasonographic and cross-sectional imaging techniques have been widely adopted in the pre-operative staging of renal masses with a progressive technological refinement. The aim of this study is to…
Ben Groebner, Jason D. Clark, Jeffrey D. Svedin et al. · 2024 · Agronomy Journal
Abstract Including soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn ( Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the…
Harvey C Freetly, Amanda K Lindholm-Perry, Andrew P Foote et al. · 2020 · Journal of Animal Science
Abstract Methane represents an energetic loss, and it has been proposed that its reduction may be associated with improved feed efficiency. Rumen methanogens produce most of the methane. Forty-nine crossbred heifers were individually fed a…
Andrew Fowlie · 2014 · arXiv
The absence of supersymmetry or other new physics at the Large Hadron Collider (LHC) has lead many to question naturalness arguments. With Bayesian statistics, we argue that natural models are most probable and that naturalness is not merely an aesthetic principle. We calculate a probabilistic measure of naturalness, the Bayesian evidence, for the Standard Model (SM) with and without quadratic divergences, confirming that the SM with quadratic divergences is improbable. We calculate the Bayesian evidence for the Constrained Minimal Supersymmetric Standard Model (CMSSM) with naturalness priors
Mick Harris, null null, null null et al. · 2022 · John Heinrichs Scholarly & Creative Activities Day
Treatments for mild Traumatic Brain Injuries (mTBI’s) and Persistent Post-Concussion Syndrome (PPCS) have focused on alleviating symptoms and disabilities. Researchers have seen improvements with patients who have had brain injuries due to…
Julie Flynn, null null, null null et al. · 2017 · Journal of Applied and Educational Research
Teachers and students nationwide are struggling to address the disparity in academic achievement between students in urban, socioeconomically underprivileged and racially segregated school districts, and their more affluent, white,…
Vanessa Leavitt, null null, null null et al. · 2017 · Journal of Applied and Educational Research
Achieving a high degree of mastery and success on an instrument is often a goal of band students, as well as that of their parents, band directors, and lesson teachers. The ability to practice consistently and to make lasting improvements…
Shyla Davison, null null, null null et al. · 2022 · John Heinrichs Scholarly & Creative Activities Day
Over the past five years, there has been many improvements to the Sternberg Museum of Natural History that have resulted in a renovated fossil preparation lab and a new database for specimen data storage. To find ways to improve our…
Erin Waggoner, null null, null null et al. · 2023 · John Heinrichs Scholarly & Creative Activities Day
Rapid Response Teams became a hospital standard in 2004 after a campaign by the Institute of Healthcare Improvement. The intention was to reduce hospital morbidity and mortality by bringing the resources to the bedside that match the…
Aldar C-F. Chan · 2007 · arXiv
Any secured system can be modeled as a capability-based access control system in which each user is given a set of secret keys of the resources he is granted access to. In some large systems with resource-constrained devices, such as sensor networks and RFID systems, the design is sensitive to memory or key storage cost. With a goal to minimize the maximum users' key storage, key compression based on key linking, that is, deriving one key from another without compromising security, is studied. A lower bound on key storage needed for a general access structure with key derivation is derived. Th
Calvin McCarter, Nicholas Dronen · 2022 · arXiv
Fast approximations to matrix multiplication have the potential to dramatically reduce the cost of neural network inference. Recent work on approximate matrix multiplication proposed to replace costly multiplications with table-lookups by fitting a fast hash function from training data. In this work, we propose improvements to this previous work, targeted to the deep learning inference setting, where one has access to both training data and fixed (already learned) model weight matrices. We further propose a fine-tuning procedure for accelerating entire neural networks while minimizing loss in
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
Chelsea Murray, James U. Allingham, Javier Antorán et al. · 2021 · arXiv
Farquhar et al. [2021] show that correcting for active learning bias with underparameterised models leads to improved downstream performance. For overparameterised models such as NNs, however, correction leads either to decreased or unchanged performance. They suggest that this is due to an "overfitting bias" which offsets the active learning bias. We show that depth uncertainty networks operate in a low overfitting regime, much like underparameterised models. They should therefore see an increase in performance with bias correction. Surprisingly, they do not. We propose that this negative res
Yemon Choi · 2015 · arXiv
We show that, given a compact Hausdorff space $Ω$, there is a compact group ${\mathbb G}$ and a homeomorphic embedding of $Ω$ into ${\mathbb G}$, such that the restriction map ${\rm A}({\mathbb G})\to C(Ω)$ is a complete quotient map of operator spaces. In particular, this shows that there exist compact groups which contain infinite cb-Helson subsets, answering a question raised in [Choi--Samei, Proc. AMS 2013; cf. http://arxiv.org/abs/1104.2953]. A negative result from the same paper is also improved.
Anand Ganesh, Babhrubahan Bose, Anand Rajagopalan · 2025 · arXiv
We construct four Schauder bases for the space $C[0,1]$, one using ReLU functions, another using Softplus functions, and two more using sigmoidal versions of the ReLU and Softplus functions. This establishes the existence of a basis using these functions for the first time, and improves on the universal approximation property associated with them. We also show an $O(\frac{1}{n})$ approximation bound based on our ReLU basis, and a negative result on constructing multivariate functions using finite combinations of ReLU functions.
Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares et al. · 2020 · arXiv
Natural language inference (NLI) data has proven useful in benchmarking and, especially, as pretraining data for tasks requiring language understanding. However, the crowdsourcing protocol that was used to collect this data has known issues and was not explicitly optimized for either of these purposes, so it is likely far from ideal. We propose four alternative protocols, each aimed at improving either the ease with which annotators can produce sound training examples or the quality and diversity of those examples. Using these alternatives and a fifth baseline protocol, we collect and compare
M. Gillon, B. -O. Demory, C. Lovis et al. · 2017 · arXiv
Short-period super-Earths and Neptunes are now known to be very frequent around solar-type stars. Improving our understanding of these mysterious planets requires the detection of a significant sample of objects suitable for detailed characterization. Searching for the transits of the low-mass planets detected by Doppler surveys is a straightforward way to achieve this goal. Indeed, Doppler surveys target the most nearby main-sequence stars, they regularly detect close-in low-mass planets with significant transit probability, and their radial velocity data constrain strongly the ephemeris of p
Simon Kuang, Yuezhu Xu, S. Sivaranjani et al. · 2026 · arXiv
The global Lipschitz constant of a neural network is related to robustness and generalization, yet unlike in many classical models, it is not plainly legible from the parameters. This has motivated sophisticated verification algorithms, especially semidefinite programming (SDP) based on incremental quadratic constraints on the activation functions, to improve on the fast but often loose product of layerwise Lipschitz constants (the trivial bound). We ask why Lipschitz verification is a problem in the first place. Our answer is that the difficulty is structural: estimating a network's Lipschitz
Samuel Jacob Chacko, James Hugglestone, Chashi Mahiul Islam et al. · 2026 · arXiv
Agent Skills, structured packages of procedural knowledge loaded into an LLM agent at inference time, are widely reported to improve task pass rates by an average of 16.2~percentage points across diverse domains. Yet the same benchmarks show wide variance, with 16 of 84 tasks suffering negative deltas when Skills are introduced. The community has not yet articulated a clean mechanism for \emph{when} Skills help and when they are merely redundant overhead. We re-analyze a recently published 180-run controlled study of an MCP-grounded autonomous Capture-the-Flag (CTF) agent under four documentat
Lukas Balles, Cedric Archambeau, Giovanni Zappella · 2023 · arXiv
With increasing scale in model and dataset size, the training of deep neural networks becomes a massive computational burden. One approach to speed up the training process is Selective Backprop. For this approach, we perform a forward pass to obtain a loss value for each data point in a minibatch. The backward pass is then restricted to a subset of that minibatch, prioritizing high-loss examples. We build on this approach, but seek to improve the subset selection mechanism by choosing the (weighted) subset which best matches the mean gradient over the entire minibatch. We use the gradients w.r
Kenichi Konishi · 2023 · arXiv
We comment on the so-called negative-result experiments (also known as null measurements, interaction-free measurements, and so on) in quantum mechanics (QM), in the light of the new general understanding of the quantum-measurement processes, proposed recently. All experiments of this kind (null-measurements) can be understood as improper measurements with an intentionally biased detector set up, which introduces exclusion or selection of certain events. The prediction on the state of a microscopic system under study based on a null measurement, is sometimes dramatically described as ``wave-fu
Taylor Knipe, Josue Ortega · 2025 · arXiv
The celebrated Efficiency-Adjusted Deferred Acceptance mechanism (EADA) improves the efficiency of the DA algorithm via consented priority violations. Notwithstanding its many merits, we show that EADA can improve only two students when an alternative mechanism that Pareto-dominates DA could benefit all but one student. This shortfall in the number of students improved is not exclusive of EADA but extends to all setwise minimally unstable mechanisms, i.e. those that generate a set of blocking pairs that is never a strict superset of that of another mechanism. The incompatibility between number
Fabrizio Ottati, Giovanna Turvani, Marco Vacca et al. · 2023 · arXiv
The speed of modern digital systems is severely limited by memory latency (the ``Memory Wall'' problem). Data exchange between Logic and Memory is also responsible for a large part of the system energy consumption. Logic--In--Memory (LiM) represents an attractive solution to this problem. By performing part of the computations directly inside the memory the system speed can be improved while reducing its energy consumption. LiM solutions that offer the major boost in performance are based on the modification of the memory cell. However, what is the cost of such modifications? How do these impa
Mykolas Sveistrys, Richard Kunert · 2025 · arXiv
Retrieval-Augmented Generation (RAG) has been used in question answering (QA) systems to improve performance when relevant information is in one (single-hop) or multiple (multi-hop) passages. However, many real life scenarios (e.g. dealing with financial, legal, medical reports) require checking all documents for relevant information without a clear stopping condition. We term these pluri-hop questions, and formalize them by 3 conditions - recall sensitivity, exhaustiveness, and exactness. To study this setting, we introduce PluriHopWIND, a multilingual diagnostic benchmark of 48 pluri-hop que
Asif Manzoor Hasan, Johan Larsson, Sergio Pirozzoli et al. · 2023 · arXiv
A transformation that relates a compressible wall-bounded turbulent flow with non-uniform fluid properties to an equivalent incompressible flow with uniform fluid properties is derived and validated. The transformation accounts for both variable-property and intrinsic compressibility effects, the latter being the key improvement over the current state-of-the-art. The importance of intrinsic compressibility effects contradicts the renowned Morkovin's hypothesis.
Xu Ma, Jiajie Zhang, Fujing Xie et al. · 2025 · arXiv
Global localization is essential for autonomous robotics, especially in indoor environments where the GPS signal is denied. We propose a novel WiFi-based localization framework that leverages ubiquitous wireless infrastructure and the OpenStreetMap Area Graph (osmAG) for large-scale indoor environments. Our approach integrates signal propagation modeling with osmAG's geometric and topological priors. In the offline phase, an iterative optimization algorithm localizes WiFi Access Points (APs) by modeling wall attenuation, achieving a mean localization error of 3.79 m (35.3\% improvement over tr
John Rozmarynowycz, Seungki Kim · 2023 · arXiv
We report the finding of the new upper bound on the lowest positive integer $x$ for which the Mertens conjecture \begin{equation*} \left| \sum_{1 \leq n \leq x} μ(n) \right| < \sqrt{x} \end{equation*} fails to hold: $x < \exp(1.017 \times 10^{29})$, an improvement over previously known $\exp(1.59 \times 10^{40})$ due to Kotnik and te Riele [7].