Negative / Null Result ReportOpen accessMathematics
Birgul Koc, Muhammad Mohebujjaman, Changhong Mou et al. · 2018 · arXiv
For reduced order models (ROMs) of fluid flows, we investigate theoretically and computationally whether differentiation and ROM spatial filtering commute, i.e., whether the commutation error (CE) is nonzero. We study the CE for the Laplacian and two ROM filters: the ROM projection and the ROM differential filter. Furthermore, when the CE is nonzero, we investigate whether it has any significant effect on ROMs that are constructed by using spatial filtering. As numerical tests, we use the Burgers equation with viscosities $ν=10^{-1}$ and $ν=10^{-3}$ and a 2D flow past a circular cylinder at Re
View details →Negative / Null Result ReportOpen accessMathematics
Ruiwen Fan, Zhangyin Dai, Shixiang Tian et al. · 2022 · arXiv
As an indispensable spatial direction information indicator for emergency evacuation, the spatial relationship between safety evacuation signs and evacuees will affect the response time of evacuees and the evacuation efficiency. This paper takes 2 kinds of common safety evacuation signs, hangtag-type and embedded, as the research object and designs space direction information transmission efficiency and capability simulation experiment and fire drill, the efficiency and capability of spatial direction information transmission of safety evacuation signs are studied. The results show that the sp
View details →Negative / Null Result ReportOpen accessMathematics
Oliver J. Hines, Christian L. Hines · 2026 · arXiv
Gradient boosted decision trees require a stopping rule to avoid overfitting. The standard rule monitors a validation loss and stops if the loss fails to improve for a fixed patience period. However, the patience parameter has no interpretable scale and validation losses can be noisy or implicitly defined by a user-specified gradient. We propose ScoreStop, a gradient-based early-stopping rule that casts the stopping decision at each iteration as a test of the null hypothesis that the current predictor is the population risk minimizer. We use a functional score test, computed on validation data
View details →Negative / Null Result ReportOpen accessMathematics
Rong Chen, Simone Giannerini, Greta Goracci et al. · 2025 · arXiv
We develop an estimation methodology for a factor model for high-dimensional matrix-valued time series, where common stochastic trends and common stationary factors can be present. We study, in particular, the estimation of (row and column) loading spaces, of the common stochastic trends and of the common stationary factors, and the row and column ranks thereof. In a set of (negative) preliminary results, we show that a projection-based technique fails to improve the rates of convergence compared to a "flattened" estimation technique which does not take into account the matrix nature of the da
View details →Negative / Null Result ReportOpen accessMathematics
Ange Wang, Hongzhi Guan, Yan Han et al. · 2021 · Discrete Dynamics in Nature and Society
The shared parking scheme improves the utilization rate of existing parking resources and contributes to the sustainable development of cities, but many private parking spaces that are not included in the shared parking scheme have a low utilization rate in China. In order to better promote the shared parking scheme, it is necessary to study the intention of the owners of private parking spaces to share their parking spaces. Therefore, this paper used the Unified Theory of Acceptance and Use of Technology (UTAUT) and Benefit-Risk Analysis Model (BRA) as the combined theoretical framework (C-UT
View details →Negative / Null Result ReportOpen accessMathematics
Mashhour A. Alazwari, Mohammad Reza Safaei · 2021 · Mathematics
In the present study, a novel configuration of a rotating tube bundle was simulated under non-isothermal hydrodynamic conditions using a mixture model. Eight fins were considered in this study, which targeted the hydrodynamics of the system. An aqueous copper nanofluid was used as the heat transfer fluid. Various operating factors, such as rotation speed (up to 500 rad/s), Reynolds number (10–80), and concentration of the nanofluid (0.0–4.0%) were applied, and the performance of the microchannel heat exchanger was assessed. It was found that the heat transfer coefficient of the system could be
View details →Negative / Null Result ReportOpen accessMathematics
I. Jug, D. Jug, M. Sabo et al. · 2011 · Turkish Journal of Agriculture and Forestry Sciences
Eight different soil tillage systems (TS) for winter wheat after soybean crop production were compared at the chernozem soil type in Croatian Baranya region in a 4-year period (2001/2002, 2002/2003, 2003/2004, 2004/2005). Tillage systems…
View details →Negative / Null Result ReportOpen accessMathematics
Larissa Corrêa Lopes Quadros, J. Gomes · 2020
Research is needed to subsidize foresters to manage the forest for better use of wood. To help in the research, analyzing the diameter distribution, the species can be grouped according to their characteristics concerning the diameter…
View details →Negative / Null Result ReportOpen accessMathematics
William Paul Heath, Joaquin Carrasco, Jingfan Zhang · 2021 · arXiv
We present a phase condition under which there is no suitable multiplier for a given continuous-time plant. The condition can be derived from either the duality approach or from the frequency interval approach. The condition has a simple graphical interpretation, can be tested in a numerically efficient manner and may be applied systematically. Numerical examples show significant improvement over existing results in the literature. The condition is used to demonstrate a third order system with delay that is a counterexample to the Kalman Conjecture.
View details →Negative / Null Result ReportOpen accessMathematics
Antonio Liguori, Matias Quintana, Chun Fu et al. · 2023 · arXiv
Missing data are frequently observed by practitioners and researchers in the building energy modeling community. In this regard, advanced data-driven solutions, such as Deep Learning methods, are typically required to reflect the non-linear behavior of these anomalies. As an ongoing research question related to Deep Learning, a model's applicability to limited data settings can be explored by introducing prior knowledge in the network. This same strategy can also lead to more interpretable predictions, hence facilitating the field application of the approach. For that purpose, the aim of this
View details →Negative / Null Result ReportOpen accessMathematics
Guido De Philippis, Michael Goldman, Berardo Ruffini · 2023 · arXiv
We consider a branched transport type problem which describes the magnetic flux through type-I superconductors in a regime of very weak applied fields. At the boundary of the sample, deviation of the magnetization from being uniform is penalized through a negative Sobolev norm. It was conjectured by S. Conti, F. Otto and S. Serfaty that as a result, the trace of the magnetization on the boundary should be a measure of Hausdorff dimension $8/5$. We prove that this conjecture is equivalent to the proof of local energy bounds with an optimal exponent. We then obtain local bounds which are however
View details →Negative / Null Result ReportOpen accessMathematics
Saahil Ognawala, Justin Bayer · 2014 · arXiv
Advancements in parallel processing have lead to a surge in multilayer perceptrons' (MLP) applications and deep learning in the past decades. Recurrent Neural Networks (RNNs) give additional representational power to feedforward MLPs by providing a way to treat sequential data. However, RNNs are hard to train using conventional error backpropagation methods because of the difficulty in relating inputs over many time-steps. Regularization approaches from MLP sphere, like dropout and noisy weight training, have been insufficiently applied and tested on simple RNNs. Moreover, solutions have been
View details →Negative / Null Result ReportOpen accessMathematics
Giulio Cantone, Venera Tomaselli · 2022 · arXiv
Snowball sampling is the common name for sampling designs on human populations where respondents are requested to share the questionnaire among their social ties. With some exceptions, estimates from snowball samplings are considered biased. However, the magnitude of the bias is influenced by a combination of elements of the sampling design and features of the target population. Hybrid Probabilistic-Snowball Sampling Designs (HPSSD) aims to reduce the main source of bias in the snowball sample through randomly oversampling the first stage 0 of the snowball. To check the behaviour of HPSSD for
View details →Negative / Null Result ReportOpen accessMathematics
Nicolas Banholzer, Thomas Mellan, H Juliette T Unwin et al. · 2023 · arXiv
Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative performance remain. Here, we compare short-term probabilistic forecasts of popular mechanistic models based on the renewal equation with forecasts of statistical time series models. Our empirical comparison is based on data of the daily incidence of COVID-19 across six large US states over the first pandemic year. We find that, on average, probabilistic forecast
View details →Negative / Null Result ReportOpen accessMathematics
Ben Adcock, Gregor Maier, Rahul Parhi · 2025 · arXiv
We develop a minimax theory for operator learning, where the goal is to estimate an unknown operator between separable Hilbert spaces from finitely many noisy input-output samples. For uniformly bounded Lipschitz operators, we prove information-theoretic lower bounds together with matching or near-matching upper bounds, covering both fixed and random designs under Hilbert-valued Gaussian noise and Gaussian white noise errors. The rates are controlled by the spectrum of the covariance operator of the measure that defines the error metric. Our setup is very general and allows for measures with u
View details →Negative / Null Result ReportOpen accessMathematics
Ziling Ma, Ángel López Oriona, Hernando Ombao et al. · 2026 · arXiv
We study adaptive pooling under predictive heterogeneity in high-dimensional multivariate time series forecasting, where global models improve statistical efficiency but may fail to capture heterogeneous predictive structure, while naive specialization can induce negative transfer. We formulate adaptive pooling as a statistical decision problem and propose a validation-driven framework that determines when and how specialization should be applied. Rather than grouping series based on representation similarity, we define partitions through out-of-sample predictive performance, thereby aligning
View details →Negative / Null Result ReportOpen accessMathematics
Yoav Zeevi, Sofi Astashenko, Liad Mudrik et al. · 2020 · arXiv
The field of psychological sciences has been grappling with the replicability crisis. Various issues have been identified as potential sources of this problem. We bring to light a potential source that has largely been overlooked and demonstrate its significant contribution to the problem: the practice of multiple comparisons. We analyzed 88 papers from the Reproducibility Project in Psychology and found that multiple results are commonly reported in a single paper, ranging from 4 to 730 (M=77.7), without multiple comparison adjustments. We retroactively applied such an adjustment using a hier
View details →Negative / Null Result ReportOpen accessMathematics
S. Stanley Young, Robert L. Obenchain, Christophe Lambert · 2015 · arXiv
It is well-known that claims coming from observational studies often fail to replicate when rigorously re-tested. The technical problems include multiple testing, multiple modeling and bias. Any or all of these problems can give rise to claims that will fail to replicate. There is a need for statistical methods that are easily applied, are easy to understand, and are likely to give reliable results. In particular, simple ways for reducing the influence of bias are essential. In this paper, the Local Control method developed by Robert Obenchain is explicated using a small air quality/longevity
View details →Negative / Null Result ReportOpen accessMathematics
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
View details →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
View details →Negative / Null Result ReportOpen accessMathematics
Justin Boutilier, Jonas Oddur Jonasson, Hannah Li et al. · 2024 · arXiv
We study RCTs that evaluate the impact of service interventions, for example, teachers or advisors conducting proactive outreach to at-risk students, medical providers giving medication adherence support by calling or texting, or social workers that conduct home visits. A defining feature of service interventions is that they are delivered by a capacity-constrained resource -- teachers, healthcare providers, or social workers -- whose limited availability creates causal inference complications. Because participants share a finite service capacity, adding more participants can reduce the timeli
View details →Negative / Null Result ReportOpen accessMathematics
Luca Chiantini, Łucja Farnik, Giuseppe Favacchio et al. · 2023 · arXiv
This article introduces a previously unrecognized combinatorial structure underlying configurations of skew lines in $\mathbb{P}^3$, and reveals its deep and surprising connection to the algebro-geometric concept of geproci sets. Given any field $\mathbb{K}$ and a finite set $\mathcal L$ of 3 or more skew lines in $\mathbb{P}^3_\mathbb{K}$, we associate to it a group $G_{\mathcal L}$ and a groupoid $C_{\mathcal L}$ whose action on the union $\cup_{L\in\mathcal L}L$ provides orbits which have a rich combinatorial structure. We characterize when $G_{\mathcal L}$ is abelian and give partial resul
View details →Negative / Null Result ReportOpen accessMathematics
Ilmari Kangasniemi · 2019 · arXiv
Suppose that $M$ is a closed, connected, and oriented Riemannian $n$-manifold, $f \colon \mathbb{R}^n \to M$ is a quasiregular map automorphic under a discrete group $Γ$ of Euclidean isometries, and $f$ has finite multiplicity in a fundamental cell of $Γ$. We show that if $Γ$ has a sufficiently large translation subgroup $Γ_T$, then $\dim Γ\in \{0, n-1, n\}$. If $f$ is strongly automorphic and induces a non-injective Lattès-type uniformly quasiregular map, then the same holds without the assumption on the size of $Γ_T$. Moreover, an even stronger restriction holds in the Lattès case if $M$ is
View details →Negative / Null Result ReportOpen accessMathematics
Utkarsh, Chris Elrod, Yingbo Ma et al. · 2022 · arXiv
Numerically solving ordinary differential equations (ODEs) is a naturally serial process and as a result the vast majority of ODE solver software are serial. In this manuscript we developed a set of parallelized ODE solvers using extrapolation methods which exploit "parallelism within the method" so that arbitrary user ODEs can be parallelized. We describe the specific choices made in the implementation of the explicit and implicit extrapolation methods which allow for generating low overhead static schedules to then exploit with optimized multi-threaded implementations. We demonstrate that wh
View details →Negative / Null Result ReportOpen accessMathematics
Nguyen Ngoc Hung · 2015 · arXiv
A classical theorem of John Thompson on character degrees asserts that if the degree of every ordinary irreducible character of a finite group $G$ is 1 or divisible by a prime $p$, then $G$ has a normal $p$-complement. We obtain a significant improvement of this result by considering the average of $p'$-degrees of irreducible characters. We also consider fields of character values and prove several improvements of earlier related results.
View details →Negative / Null Result ReportOpen accessMathematics
Kunyu Guo, Hansong Huang · 2013 · arXiv
In studying commutants of analytic Toeplitz operators, Thomson proved a remarkable theorem which states that under a mild condition, the commutant of an analytic Toeplitz operator is equal to that of Toeplitz operator defined by a finite Blaschke product. Cowen gave an significant improvement of Thosom's result. In this paper, we will present examples in Cowen's class which does not lie in Thomson's class.
View details →Negative / Null Result ReportOpen accessMathematics
Mark Rubin · 2024 · arXiv
One justification for preregistering research hypotheses, methods, and analyses is that it improves the transparent evaluation of the severity of hypothesis tests. In this article, I consider two cases in which preregistration does not improve this evaluation. First, I argue that, although preregistration may facilitate the transparent evaluation of severity in Mayo's error statistical philosophy of science, it does not facilitate this evaluation in Popper's theory-centric approach. To illustrate, I show that associated concerns about Type I error rate inflation are only relevant in the error
View details →Negative / Null Result ReportOpen accessMathematics
Andrea Schioppa · 2015 · arXiv
For each $β>1$ we construct a family $F_β$ of metric measure spaces which is closed under the operation of taking weak-tangents (i.e.~blow-ups), and such that each element of $F_β$ admits a $(1,P)$-Poincaré inequality if and only if $P>β$.
View details →Negative / Null Result ReportOpen accessMathematics
Mark Rubin · 2020 · arXiv
Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do and what they actually ended up doing. This historical transparency is supposed to facilitate judgments about the credibility of the research findings. The present article provides a critical review of 17 of the reasons behind this argument.
View details →Negative / Null Result ReportOpen accessMathematics
Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin et al. · 2020 · arXiv
Many instances of algorithmic bias are caused by subpopulation shifts. For example, ML models often perform worse on demographic groups that are underrepresented in the training data. In this paper, we study whether enforcing algorithmic fairness during training improves the performance of the trained model in the \emph{target domain}. On one hand, we conceive scenarios in which enforcing fairness does not improve performance in the target domain. In fact, it may even harm performance. On the other hand, we derive necessary and sufficient conditions under which enforcing algorithmic fairness l
View details →