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.
21328 results · page 474 of 711
A. Janae Sholtz · 2025 · Philosophy Today
Deleuze and Guattari provide a sophisticated account of ontological relationality, many facets of which have been annexed into new materialist theory. It is worth asking how this happens and with what degree of accuracy. Deleuze’s…
Е.Н. Малова · 2019 · Бизнес. Образование. Право
Актуальность определена существенными изменениями социокультурной, экономической, образовательной ситуации в стране и потребностями общества в развитии социально активной молодежи. Волонтерство добровольная безвозмездная социально значимая…
Rio Diansyah P, Lusiana, Elvira · 2025 · Menara: Jurnal Teknik Sipil
Estimasi biaya selalu menjadi salah satu elemen yang krusial dalam suatu manajemen proyek secara keseluruhan. Dengan melakukan perhitungan estimasi, maka dapat diketahui biaya yang dibutuhkan dalam suatu proyek. Cost Significant Model…
Mahadevappa Hanchinamani · 2022 · International Journal of Research Publication and Reviews
It has been widely debated that while scholars like Nitin Nohria Dean Harvard Business School from Indian origin are leading the world’s top B-Schools; BSchools in India are struggling to find a place among the Top 100 Global Institutions.…
Adam Liebendorfer · 2023 · Scilight
High-fidelity simulations driven by atomic force microscopy help demonstrate the potential for spintronics in neuromorphic computing.
Stephen Antonoplis, Serena Chen · 2022 · Meta-Psychology
As economic inequality increases in the United States and around the world, psychologists have begun to study how the psychological experience of scarcity impacts people's decision making. Recent work in psychology suggests that…
· 2022 · Cancer Discovery
Abstract Tumor antigen recognition is limited to a small percentage of CD8+ T cells in ovarian cancer.
Elliott Jane · 2011 · BMJ Supportive & Palliative Care
Introduction Two bereavement audit tools have been written to enable Hospices to collect crucial data to evidence high quality service provision based on national standards. Aims To enable hospices to evidence the standard of their…
�������, Andrey Chiganov, �������� et al. · 2015 · Standards and Monitoring in Education
The paper shares the experience of interacting with Mathematics teachers and 5th�6th grade schoolchildren in order to obtain and demonstrate new
 learning outcomes in mastering Mathematics by means of such a non-conventional…
John C. Licciardone · 2014 · Journal of Osteopathic Medicine
Abstract The Journal of the American Osteopathic Association ( JAOA ) encourages osteopathic physicians, faculty members and students at colleges of osteopathic medicine, and others within the health care professions to submit comments…
Timothy Daniel Allerton, Stefany D. Primeaux · 2013 · The FASEB Journal
The propensity for some individuals to develop obesity has been linked to intake of a high fat diet (HFD) and physical inactivity. However, some individuals resist obesity through improved energy sensing and other compensatory measures to…
P. J. McKnight, R. Manwaring, L. Felton · 2026 · Frontiers in Psychology
This study represents the first investigation of psychological skills in Formula 1 (F1) and Formula 2 (F2) drivers, addressing a critical gap in motorsport psychology research. Ten professional drivers (5 F1, 5 F2; all male; age = 24 ± 4…
Lauren Willis, Sara R. Fagerlie · 2018 · Blood
Abstract Background: The objective of this study was to assess current clinical practices of hematologist/oncologist (hem/onc) specialists related to FLT3 mutations and FLT3 inhibitors used in acute myeloid leukemia (AML), in order to…
Catherine Doyle, Diego Combita, Matthew J. Dunlop et al. · 2025 · Polymers
Microbial contamination is a global concern with impacts on a variety of industries ranging from marine to biomedical applications. Recent research on hydrophilic polymer-based coatings is focused on combining antifouling polymers with…
Sthithpragya Gupta, Durgesh Haribhau Salunkhe, Aude Billard · 2026 · Science Robotics
Teaching robots new skills should be as natural as showing rather than programming. Learning from demonstration (LfD) moves toward this goal by allowing users to guide a robot or sketch a desired motion, enabling learning without writing a…
Najib George Awad · 2021 · Interreligious Studies and Intercultural Theology
Can people of different faiths worship the same God and pray inter-religiously? Can this worship demonstrate that the religions believe in the same God? Does the participation in interreligious prayer verify that the participants believe…
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].
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
Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang · 2024 · arXiv
This study addresses the critical challenge of error accumulation in spatio-temporal auto-regressive (AR) predictions within scientific machine learning models by exploring temporal integration schemes and adaptive multi-step rollout strategies. We introduce the first implementation of the two-step Adams-Bashforth method specifically tailored for data-driven AR prediction, leveraging historical derivative information to enhance numerical stability without additional computational overhead. To validate our approach, we systematically evaluate time integration schemes across canonical 2D PDEs be
Frank Meier, Hans Walliser · 1996 · arXiv
We present a procedure to calculate 1-loop graphs in the soliton sector of chiral Lagrangians and use it to calculate quantum corrections to certain baryon observables in Skyrme-type models. Results generally show an improvement over the values obtained in tree approximation except for the case of the axial coupling g_A.
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.
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
Ramin Babaee, Shahab Oveis Gharan, Martin Bouchard · 2025 · arXiv
We propose a novel digital-to-analog converter (DAC) weighting architecture that statistically minimizes the distortion caused by random timing mismatches among current sources. To decode the DAC input codewords into corresponding DAC switches, we present three algorithms with varying computational complexities. We perform high-level Matlab simulations to illustrate the dynamic performance improvement over the segmented structure.
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
Yoonjeon Kim, Yuhta Takida, Chieh-Hsin Lai et al. · 2026 · arXiv
RL-based post-training has been widely adopted to enable interleaved visual and textual reasoning in unified multimodal models capable of both text and image generation. However, most existing approaches are built upon autoregressive (AR) unified models, which require full image regeneration during visual reasoning. In this work, we demonstrate that multimodal discrete diffusion models are effective alternatives to AR models for reinforcement learning in interleaved reasoning, owing to their ability to perform efficient visual rollouts via localized visual editing rather than full image-token
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
S. A. Gurvitz · 2003 · arXiv
We investigate measurement of electron transport in quantum dot systems by using single-electron transistor as a noninvasive detector. It is demonstrated that such a detector can operate in the ``negative-result measurement'' regime. In this case the measured current is not distorted, providing that it is a non-coherent one. For a coherent transport, however, the possibility of observing a particular state out of coherent superposition leads to distortion of a measured current even in the ``negative-result measurement'' regime. The corresponding decoherence rate is obtained in the framework of
Hari Sadasivan · 2026 · arXiv
We set out to train behavioral dispositions (self-verification, uncertainty acknowledgment, feedback integration) into small language models (0.6B to 2.3B effective parameters) through a four-stage all-MIT distillation pipeline, with follow-on experiments on inference-time attention-head interventions and a frozen-base confidence-gated sidecar. An internal draft reported +33.9-point MCAS and +15.3-point HumanEval gains on a Qwen3-0.6B student; a second-pass sanity check falsified both numbers before publication. The HumanEval delta was a truncation artifact (n_predict=512) that inverted to -8.
J. M. Almira, P. E. Lopez-de-Teruel, D. J. Romero-Lopez et al. · 2018 · arXiv
We prove a negative result for the approximation of functions defined on compact subsets of $\mathbb{R}^d$ (where $d \geq 2$) using feedforward neural networks with one hidden layer and arbitrary continuous activation function. In a nutshell, this result claims the existence of target functions that are as difficult to approximate using these neural networks as one may want. We also demonstrate an analogous result (for general $d \in \mathbb{N}$) for neural networks with an \emph{arbitrary} number of hidden layers, for activation functions that are either rational functions or continuous splin
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