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21,290 real negative results, null findings, and replication failures. Search the index →

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.

Negative / Null Result ReportOpen accessComputer Science

A Personalized Data-Driven Generative Model of Human Repetitive Motion

Angelo Di Porzio, Marco Coraggio · 2025 · arXiv

The deployment of autonomous virtual avatars (in extended reality) and robots in human group activities -- such as rehabilitation therapy, sports, and manufacturing -- is expected to increase as these technologies become more pervasive. Designing cognitive architectures and control strategies to drive these agents requires realistic models of human motion. Furthermore, recent research has shown that each person exhibits a unique velocity signature, highlighting how individual motor behaviors are both rich in variability and internally consistent. However, existing models only provide simplifie

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Negative / Null Result Report

The Significant Effect of Intravenous Methylprednisolone on Visual Recovery in a Case of Acute Central Retinal Artery Occlusion: A Case Report

Indranil Saha, Raveesh Bindal · 2024 · Nigerian Journal of Ophthalmology

A 62-year-old man presented with a 1-day history of sudden vision loss in the right eye, while the left eye remained unaffected. Upon examination, the best corrected visual acuity (BCVA) was finger counting in the right eye and 20/20 (0.00…

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Negative / Null Result ReportOpen accessComputer Science

The Devil is in Fine-tuning and Long-tailed Problems:A New Benchmark for Scene Text Detection

Tianjiao Cao, Jiahao Lyu, Weichao Zeng et al. · 2025 · arXiv

Scene text detection has seen the emergence of high-performing methods that excel on academic benchmarks. However, these detectors often fail to replicate such success in real-world scenarios. We uncover two key factors contributing to this discrepancy through extensive experiments. First, a \textit{Fine-tuning Gap}, where models leverage \textit{Dataset-Specific Optimization} (DSO) paradigm for one domain at the cost of reduced effectiveness in others, leads to inflated performances on academic benchmarks. Second, the suboptimal performance in practical settings is primarily attributed to the

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Negative / Null Result ReportOpen accessComputer Science

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation

Christopher Brady, Xu Wu · 2025 · arXiv

The Organization for Economic Cooperation and Development (OECD) Working Party on Nuclear Criticality Safety (WPNCS) proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian Inverse Uncertainty Quantification (IUQ) as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of Generalized Linear Least Squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed

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Negative / Null Result ReportOpen accessComputer Science

Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion

Meimingwei Li, Yuanhao Ding, Esteban Garces Arias et al. · 2026 · arXiv

Recent work has identified a counterintuitive phenomenon termed "Hyperfitting", where fine-tuning Large Language Models (LLMs) to near-zero training loss on small datasets surprisingly enhances open-ended generation quality and mitigates repetition in greedy decoding. While effective, the underlying mechanism remains poorly understood, with the extremely low-entropy output distributions suggesting a potential equivalence to simple temperature scaling. In this work, we demonstrate that this phenomenon is fundamentally distinct from distribution sharpening; entropy-matched control experiments re

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Negative / Null Result Report

The Effect of Significant Exercise Modalities, Gender and Age on 9 Markers (Indicators) in NHISS Registered ACL Patients for Designing Exercise Intervention Program

Hyunseok JEE, Sae Yong LEE · 2020 · Iranian Journal of Public Health

Background: Knee disease is prevalent in the post middle-aged and associated with lower quality of life. Knee disease (i.e., anterior cruciate ligament, ACL) related injury preventive program should be supported. We examined the…

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Negative / Null Result Report

Effect of Latitude As a Significant Element on the Results of Direct UTM Coordinates Transformation Method

Mohammed Anwer Jassim, Darin Mohammed Tofiq Mohammed · 2023 · Photogrammetric Engineering & Remote Sensing

The transformation of global navigation satellite systems coordi- nates between any two datums represents a vital procedure. Although the geocentric coordinates (X, Y, Z) of two datums can be trans- formed using the 7-parameters method,…

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Negative / Null Result Report

Effect of significant ventricular septal defect on the left atrial function and strain using three-dimensional speckle tracking echocardiography

H Nossier, E Ali, H Attia et al. · 2026 · European Heart Journal - Cardiovascular Imaging

Abstract Introduction Among the various types of congenital heart diseases (CHDs), significant left-to-right shunts such as ventricular septal defects (VSDs) alter normal cardiac physiology and hemodynamics, leading to increased volume…

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Negative / Null Result ReportOpen accessComputer Science

Beyond Geometry: Artistic Disparity Synthesis for Immersive 2D-to-3D

Ping Chen, Zezhou Chen, Xingpeng Zhang et al. · 2026 · arXiv

Current 2D-to-3D conversion methods achieve geometric accuracy but are artistically deficient, failing to replicate the immersive and emotionally resonant experience of professional 3D cinema. This is because geometric reconstruction paradigms mistake deliberate artistic intent, such as strategic zero-plane shifts for pop-out effects and local depth sculpting, for data noise or ambiguity. This paper argues for a new paradigm: Artistic Disparity Synthesis, shifting the goal from physically accurate disparity estimation to artistically coherent disparity synthesis. We propose Art3D, a preliminar

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Negative / Null Result ReportOpen accessAgricultural and Biological Sciences

Emergence of Human-Like Attention in Self-Supervised Vision Transformers: an eye-tracking study

Takuto Yamamoto, Hirosato Akahoshi, Shigeru Kitazawa · 2024 · arXiv

Many models of visual attention have been proposed so far. Traditional bottom-up models, like saliency models, fail to replicate human gaze patterns, and deep gaze prediction models lack biological plausibility due to their reliance on supervised learning. Vision Transformers (ViTs), with their self-attention mechanisms, offer a new approach but often produce dispersed attention patterns if trained with supervised learning. This study explores whether self-supervised DINO (self-DIstillation with NO labels) training enables ViTs to develop attention mechanisms resembling human visual attention.

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Negative / Null Result ReportOpen accessComputer Science

PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation

Chenglong Ma, Ziqi Xu, Yongli Ren et al. · 2025 · arXiv

Traditional offline evaluation methods for recommender systems struggle to capture the complexity of modern platforms due to sparse behavioural signals, noisy data, and limited modelling of user personality traits. While simulation frameworks can generate synthetic data to address these gaps, existing methods fail to replicate behavioural diversity, limiting their effectiveness. To overcome these challenges, we propose the Personality-driven User Behaviour Simulator (PUB), an LLM-based simulation framework that integrates the Big Five personality traits to model personalised user behaviour. PU

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Negative / Null Result Report

Abstract 11211: Kawasaki Disease Like Vasculitis Facilitate Atherosclerosis and Statin Shows Significant Antiatherosclerosis and Antiinflammatory Effect in Kawasaki Disease Model Mouse

Yusuke Motoji, Ryuji Fukazawa, Miyagi Yasuo et al. · 2022 · Circulation

Introduction: Kawasaki disease (KD) is an acute form of systemic vasculitis that may promote atherosclerosis in adulthood. We reported last year that CAWS vasculitis, a KD-like vasculitis, induces atherosclerosis in ApoE -/- mice and that…

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Negative / Null Result ReportOpen accessComputer Science

Disturbance-Injected Robust Imitation Learning with Task Achievement

Hirotaka Tahara, Hikaru Sasaki, Hanbit Oh et al. · 2022 · arXiv

Robust imitation learning using disturbance injections overcomes issues of limited variation in demonstrations. However, these methods assume demonstrations are optimal, and that policy stabilization can be learned via simple augmentations. In real-world scenarios, demonstrations are often of diverse-quality, and disturbance injection instead learns sub-optimal policies that fail to replicate desired behavior. To address this issue, this paper proposes a novel imitation learning framework that combines both policy robustification and optimal demonstration learning. Specifically, this combinato

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Negative / Null Result ReportOpen accessPhysics

Herd Behaviour in Public Goods Games

María Pereda · 2024 · arXiv

The problem of free-riding arises when individuals benefit from a shared resource, service, or public good without contributing proportionately to its provision. This conduct often leads to a collective action problem, as individuals pursue personal gains while relying on the contributions of others. In this study, we present a Bayesian inference model to elucidate the behaviour of participants in a Public Goods Game, a conceptual framework that captures the essence of the free-riding problem. Here, individuals possess information on the distribution of group donations to the public good. Our

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Negative / Null Result ReportOpen accessComputer Science

Neutral evolution and turnover over centuries of English word popularity

Damian Ruck, R. Alexander Bentley, Alberto Acerbi et al. · 2017 · arXiv

Here we test Neutral models against the evolution of English word frequency and vocabulary at the population scale, as recorded in annual word frequencies from three centuries of English language books. Against these data, we test both static and dynamic predictions of two neutral models, including the relation between corpus size and vocabulary size, frequency distributions, and turnover within those frequency distributions. Although a commonly used Neutral model fails to replicate all these emergent properties at once, we find that modified two-stage Neutral model does replicate the static a

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Negative / Null Result Report

PEMANFAATAN KACANG HIJAU SEBAGAI PENGANTI KACANG KEDELAI DALAM PEMBUATAN TEMPE

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…

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