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.
21294 results · page 336 of 710
Nakamura N · 2026 · Annals of the ICRP
Radiation risks for cancer are classified into probabilistic effects because the induction of oncogenic mutations in a single epithelial cell is thought to be causally related to the process of carcinogenesis. However, two observations…
Firzan Danang, Saugi Abduh · 2024 · Journal of Hypertension
Background: Based on reports from the World Health Organization (WHO), Coronary Heart Disease (CHD) is the number one cause of death in the world. The severity of CHD suffered by a patient can be seen from the degree of stenosis.…
Azra Nazirah Nafiah, Fitria Wijayanti, Putri Rahayu · 2024 · SIGNIFICANT : Journal Of Research And Multidisciplinary
Judul Penelitian ini adalah Pemanfaatan Kacang Hijau Sebagai Penganti Kacang Kedelai Dalam Pembuatan Tempe. Masalah yang akan di teliti dalam penelitian ini adalah Pemanfaatan Kacang Hijau Sebagai Penganti Kacang Kedelai Dalam Pembuatan…
Sooki Z · 2021 · Nursing & Healthcare International Journal
Introduction: Marital satisfaction promotes family and public health and its stability. Different factors may contribute to marital satisfaction. This study aimed to predict women’s marital satisfaction based on their happiness. Methods:…
Aleksandar Mijatović, Mikhail Urusov · 2011 · arXiv
Modelling stock prices via jump processes is common in financial markets. In practice, to hedge a contingent claim one typically uses the so-called delta-hedging strategy. This strategy stems from the Black--Merton--Scholes model where it perfectly replicates contingent claims. From the theoretical viewpoint, there is no reason for this to hold in models with jumps. However in practice the delta-hedging strategy is widely used and its potential shortcoming in models with jumps is disregarded since such models are typically incomplete and hence most contingent claims are non-attainable. In this
Mochamad Iqbal Nurmansyah, Yustiyani Yustiyani, Narila Mutia Nasir et al. · 2023 · International Journal of Public Health Science (IJPHS)
Owing to the various scientific evidence linking smoking to the increased risk of developing severe disease and death from the COVID-19 pandemic, now is a critical time for smokers to cut back or quit. This study aimed to analyze the…
C C Colling, T R Reents, M K Kottmaier et al. · 2024 · European Heart Journal
Abstract Introduction Radiofrequency (RF) current is the classic ablation technology in the EP lab. Underlying RF ablation parameters, such as RF power, impedance, duration and contact force are used to calculate expected lesion size.…
Aarón Villanueva, Peyman Najafi, Hilbert J. Kappen · 2022 · arXiv
We study quantum annealing for combinatorial optimization with Hamiltonian $H = z H_f + H_0$ where $H_f$ is diagonal, $H_0=-|φ\rangle \langle φ|$ is the equal superposition state projector and $z$ the annealing parameter. We analytically compute the minimal spectral gap as $\mathcal{O}(1/\sqrt{N})$ with $N$ the total number of states and its location $z_*$. We show that quantum speed-up requires an annealing schedule which demands a precise knowledge of $z_*$, which can be computed only if the density of states of the optimization problem is known. However, in general the density of states is
Thurai Moorthy, Chrishanthi Rajasooriyar, Anusha Ginige et al. · 2020 · Journal of Clinical Oncology
e16591 Background: Routine diagnosis of esophageal cancer varies from locally advanced to metastatic at presentation. Most of these patients are cachectic at presentation and physically not suitable for radical tri-modality treatment as…
Falco J. Bargagli-Stoffi, Omar Melikechi · 2026 · arXiv
Identifying covariates that modify treatment effects is a central problem in causal inference. Yet existing data-adaptive procedures do not provide finite-sample control over the expected number of false discoveries, risking spurious findings that fail to replicate. We introduce causal stability selection, an algorithm that combines cross-fitted estimation of conditional average treatment effects with integrated path stability selection. The method accommodates arbitrary treatment effect estimators and arbitrary base selectors, and produces a selection set with an explicit, non-asymptotic boun
Melani Firdha Maharani, Fahmi Fahmi, Retno Wulandari · 2023 · SIGNIFICANT : Journal Of Research And Multidisciplinary
Seni dapat digunakan dalam mengembangkan potensi kreatif. Potensi ini dapat dilihat dari Cara dalam berpikir kritis dan kemampuan dalam berpikir, rasa keingintahuan sangat tinggi, mampu mengekspresikan diri di muka umum, mampu mengemukakan…
DEWI ROSMALA, ANGGA KUSUMA K · 2018 · MIND Journal
Steganografi merupakan ilmu atau teknik menyembunyikan data ke dalam suatumedia dengan tujuna orang lain tidak mengetahui keberadaan pesan tersebut.Metode Most Significant Bit (MSB) dan Least Significant Bit (LSB) adalah metodeyang…
Sunao Kamimura, Teruhisa Ohno · 2016 · ECS Meeting Abstracts
Photoelectrochemical (PEC) water splitting utilizing semiconductor electrodes has attracted considerable attention as a potential means of converting solar energy into chemical energy in the form of usable hydrogen, which is a clean and…
Zichao Wang, Alexa Siu · 2026 · arXiv
Large language models (LLMs) have shown strong performance on standardized social science instruments, but their value for product discovery remains unclear. We investigate whether interview-informed generative agents can simulate user responses in concept testing scenarios. Using in-depth workflow interviews with knowledge workers, we created personalized agents and compared their evaluations of novel AI concepts against the same participants' responses. Our results show that agents are distribution-calibrated but identity-imprecise: they fail to replicate the specific individual they are gro
Shintaro Sakai, Jisun An, Migyeong Kang et al. · 2025 · arXiv
Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals report somatic ones. We test whether Large Language Models (LLMs), which are increasingly used in mental health, reproduce these cultural patterns by prompting them with Western or Eastern personas. Results show that LLMs largely fail to replicate the patterns when prompted in English, though prompting in major Eastern languages (i.e., Chinese, Japanese, and Hindi) improves alignment in several configurations. Our analysis pinpoints two key reasons
Matthew Rueben, Frank J. Bernieri, Cindy M. Grimm et al. · 2019 · arXiv
Privacy-sensitive robotics is an emerging area of HRI research. Judgments about privacy would seem to be context-dependent, but none of the promising work on contextual "frames" has focused on privacy concerns. This work studies the impact of contextual "frames" on local users' privacy judgments in a home telepresence setting. Our methodology consists of using an online questionnaire to collect responses to animated videos of a telepresence robot after framing people with an introductory paragraph. The results of four studies indicate a large effect of manipulating the robot operator's identit
*Erisa Yokozumi, Keiichiro Mukai, Shun Ogino et al. · 2025 · International Journal of Neuropsychopharmacology
Abstract Background Patients with obsessive-compulsive disorder (OCD) frequently exhibit involvement behaviors (IBs) in which they accommodate their caregivers to their OCD symptoms by 1) asking them for reassurance, 2) forcing them to…
S Soulaidopoulos, M Drakopoulou, G Oikonomou et al. · 2020 · European Heart Journal - Cardiovascular Imaging
Abstract Background The presence of concomitant mitral regurgitation (MR) is a common issue in patients with severe aortic stenosis and negatively affects patient outcome. Available data regarding MR reduction due to aortic gradient…
Guangfa Hao, Chengliang Zhang, Kang Sun et al. · 2020 · Journal of Physics: Conference Series
Abstract Aiming at the problems of short spray distance and poor atomization effect in pesticide spraying. In addition, in order to enhance the initial velocity of the droplets and the secondary atomization of the droplets, a new…
SIGRID BERGMANN, NATASHA C. BERGMANN, LÆRKE S. GASBJERG et al. · 2018 · Diabetes
Background and Aim: The mechanisms behind the second-meal effect, i.e., the capability of a small premeal to reduce plasma glucose excursions during a main meal in type 2 diabetes, remain unknown. We investigated the involvement of the…
Lawrence Clegg, John Cartlidge · 2025 · arXiv
Intransitive player dominance, where player A beats B, B beats C, but C beats A, is common in competitive tennis. Yet, there are few known attempts to incorporate it within forecasting methods. We address this problem with a graph neural network approach that explicitly models these intransitive relationships through temporal directed graphs, with players as nodes and their historical match outcomes as directed edges. Our model (65.7% accuracy, 0.214 Brier score) forecasts competitively with established rating systems such as Weighted Elo. Although it does not improve on the baseline in uncond
Arwa Arif · 2025 · arXiv
Backtranslation BT is widely used in low resource machine translation MT to generate additional synthetic training data using monolingual corpora. While this approach has shown strong improvements for many language pairs, its effectiveness in high quality, low resource settings remains unclear. In this work, we explore the effectiveness of backtranslation for English Gujarati translation using the multilingual pretrained MBART50 model. Our baseline system, trained on a high quality parallel corpus of approximately 50,000 sentence pairs, achieves a BLEU score of 43.8 on a validation set. We aug
Gabriel Huland · 2025 · Global Labour Journal
This article analyses the failure of Egypt’s democratic transition between 2011 and 2013, highlighting the often-overlooked role of the labour movement. While dominant approaches in transition studies emphasise socio-economic factors,…
Abhijit Bandyopadhyay, Sandhya Choubey, Srubabati Goswami et al. · 2003 · arXiv
A new reactor power plant Shika-2, with a power of approximately 4 GW and at a distance of about 88 km from the KamLAND detector is scheduled to start operating in March 2006. We study the impact of the $\barν_e$ flux from this reactor on the sensitivity of the KamLAND experiment to the solar neutrino oscillation parameters. We present results on prospective determination of $Δm^2_\odot$ and $\sin^2θ_\odot$ using the combined data from KamLAND and the solar neutrino experiments, including the effect of the Shika-2 contribution to the KamLAND signal and the latest data from the salt enriched ph
Wataru Masaka, Mitsuki Sakamoto, Kenshi Abe et al. · 2025 · arXiv
We investigate how perturbation does and does not improve the Follow-the-Regularized-Leader (FTRL) algorithm in solving imperfect-information extensive-form games under sampling, where payoffs are estimated from sampled trajectories. While optimistic algorithms are effective under full feedback, they often become unstable in the presence of sampling noise. Payoff perturbation offers a promising alternative for stabilizing learning and achieving \textit{last-iterate convergence}. We present a unified framework for \textit{Perturbed FTRL} algorithms and study two variants: PFTRL-KL (standard KL
Hamed R. Tavakoli, Rakshith Shetty, Ali Borji et al. · 2017 · arXiv
To bridge the gap between humans and machines in image understanding and describing, we need further insight into how people describe a perceived scene. In this paper, we study the agreement between bottom-up saliency-based visual attention and object referrals in scene description constructs. We investigate the properties of human-written descriptions and machine-generated ones. We then propose a saliency-boosted image captioning model in order to investigate benefits from low-level cues in language models. We learn that (1) humans mention more salient objects earlier than less salient ones i
Arpit Agarwal · 2021 · arXiv
Predicting the outcome of liquid droplet collisions is an extensively studied phenomenon but the current physics based models for predicting the outcomes are poor (accuracy $\approx 43\%$). The key weakness of these models is their limited complexity. They only account for 3 features while there are many more relevant features that go unaccounted for. This limitation of traditional models can be easily overcome through machine learning modeling of the problem. In an ML setting this problem directly translates to a classification problem with 4 classes. Here we compile a large labelled dataset
F. de Jong, H. Lenske · 1997 · arXiv
We present a calculation of nuclear matter which goes beyond the usual quasi-particle approximation in that it includes part of the off-shell dependence of the self-energy in the self-consistent solution of the single-particle spectrum. The spectral function is separated in contributions for energies above and below the chemical potential. For holes we approximate the spectral function for energies below the chemical potential by a $δ$-function at the quasi-particle peak and retain the standard form for energies above the chemical potential. For particles a similar procedure is followed. The a
Greta Laage, Emma Frejinger, Andrea Lodi et al. · 2021 · arXiv
Airlines and other industries have been making use of sophisticated Revenue Management Systems to maximize revenue for decades. While improving the different components of these systems has been the focus of numerous studies, estimating the impact of such improvements on the revenue has been overlooked in the literature despite its practical importance. Indeed, quantifying the benefit of a change in a system serves as support for investment decisions. This is a challenging problem as it corresponds to the difference between the generated value and the value that would have been generated keepi
Asahi Ushio, Jose Camacho-Collados · 2024 · arXiv
In machine learning, temporal shifts occur when there are differences between training and test splits in terms of time. For streaming data such as news or social media, models are commonly trained on a fixed corpus from a certain period of time, and they can become obsolete due to the dynamism and evolving nature of online content. This paper focuses on temporal shifts in social media and, in particular, Twitter. We propose a unified evaluation scheme to assess the performance of language models (LMs) under temporal shift on standard social media tasks. LMs are tested on five diverse social m