Negative / Null Result ReportOpen accessComputer Science
Mandhapati P. Raju, Siddhartha Khaitan · 2009 · arXiv
The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers. Parallel sparse direct solvers are not found to exhibit good scalability. Hence, the parallelization of sparse direct solvers is done using domain decomposition techniques. A highly efficient sparse direct solver PARDISO is used in this study. The scalability of both Newton and modified Newton algorithms are tested.
View details →Negative / Null Result ReportOpen accessEngineering
Kushal Mehta, Arshita Jain, Jayalakshmi Mangalagiri et al. · 2020 · arXiv
We present a hybrid algorithm to estimate lung nodule malignancy that combines imaging biomarkers from Radiologist's annotation with image classification of CT scans. Our algorithm employs a 3D Convolutional Neural Network (CNN) as well as a Random Forest in order to combine CT imagery with biomarker annotation and volumetric radiomic features. We analyze and compare the performance of the algorithm using only imagery, only biomarkers, combined imagery + biomarkers, combined imagery + volumetric radiomic features and finally the combination of imagery + biomarkers + volumetric features in orde
View details →Negative / Null Result ReportOpen accessComputer Science
Gi-Chol Cho, Kaoru Hagiwara · 1999 · arXiv
We study constraints on the supersymmetric standard model from the updated electroweak precision measurements --- the Z-pole experiments and the $W$-boson mass measurements. The supersymmetric-particle contributions to the universal gauge-boson-propagator corrections are parametrized by the three oblique parameters Sz, Tz and mw. The oblique corrections, the Zqq and Zll vertex corrections, and the vertex and box corrections to the μ-decay width are separately studied in detail. We first study individual contribution from the four sectors of the model, the squarks, the sleptons, the supersymmet
View details →Negative / Null Result ReportOpen accessComputer Science
Hao-jie Xu · 2023 · arXiv
In these proceedings, we present the three proposed observables to probe the neutron skin and symmetry energy with relativistic isobar collisions, namely, the isobar ratios of the produced hadron multiplicities ($N_{\rm ch}$), the mean transverse momenta ($\langle p_{\perp} \rangle$), and the net charge multiplicities ($ΔQ$). Our findings suggest potentially significant improvement to neutron skin and symmetry energy determination over traditional low energy methods.
View details →Negative / Null Result ReportOpen accessPhysics
Krzysztof Pachucki · 2006 · arXiv
Corrections of order $α^4$Ry are calculated for the singlet states $1^1S_0$ and $2^1S_0$ of the helium atom. The result for $1^1S_0$ state is in slight disagreement with that of Korobov and Yelkhovsky in [Phys. Rev. Lett. {\bf 87}, 193003 (2001)]. The results obtained lead to a significant improvement of transition frequencies between low lying levels of the helium atom. In particular theoretical predictions for the $2^1S_0 - 1^1S_0$ transition are found to be in disagreement with experimental values.
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 accessComputer Science
S. Schneider, J. Haidenbauer, C. Hanhart et al. · 2002 · arXiv
We study pion absorption on 3He employing trinucleon wave functions calculated from modern realistic NN interactions (Paris, CD Bonn). Even though the use of the new wave functions leads to a significant improvement over older calculations with regard to both cross section and polarization data, there are hints that polarization data with quasifree kinematics cannot be described by just two-nucleon absorption mechanisms.
View details →Negative / Null Result ReportOpen accessPhysics
Ingvild Dalehaug, Kirsten Nygaard Bolstad, Daniel Aadnevik et al. · 2017 · arXiv
Purpose: Siemens has developed several iterative reconstruction (IR) algorithms on their CT scanners. SAFIRE is available on most of their CT scanners. The latest algorithm, ADMIRE, is available on their newest high-end CT scanners. The aim of our study was to compare the noise reduction properties of the two IR algorithms using objective methods. Methods and Materials: The homogeneous module of the Catphan phantom was scanned on a Siemens AS+ and a Siemens Flash CT scanner using an axial abdomen protocol with fixed tube current at two dose levels. The images were reconstructed with an abdomen
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 accessComputer Science
O. Behrend, R. Harris, P. Warren · 1993 · arXiv
We present a numerical analysis of the validity of classical and generalized hydrodynamics for Lattice Boltzmann Equation (LBE) and Lattice BGK methods in two and three dimensions, as a function of the collision parameters of these models. Our analysis is based on the wave-number dependence of the evolution operator. Good ranges of validity are found for BGK models as long as the relaxation time is chosen smaller than or equal to unity. The additional freedom in the choice of collision parameters for LBE models does not seem to give significant improvement.
View details →Negative / Null Result ReportOpen accessPhysics
Motonari Tonegawa, Tomonori Totani, Masayuki Akiyama et al. · 2013 · arXiv
The efficient selection of high-redshift emission galaxies is important for future large galaxy redshift surveys for cosmology. Here we describe the target selection methods for the FastSound project, a redshift survey for H alpha emitting galaxies at z=1.2-1.5 using Subaru/FMOS to measure the linear growth rate fσ8 via Redshift Space Distortion (RSD) and constrain the theory of gravity. To select ~400 target galaxies in the 0.2 deg^2 FMOS field-of-view from photometric data of CFHTLS-Wide (u*g'r'i'z'), we test several different methods based on color-color diagrams or photometric redshift est
View details →Negative / Null Result ReportOpen accessComputer Science
V. S. Raghu Parupudi · 2025 · arXiv
Vector comparison in high dimensions is a fundamental task in NLP, yet it is dominated by two baselines: the raw dot product, which is unbounded and sensitive to vector norms, and the cosine similarity, which discards magnitude information entirely. This paper challenges both standards by proposing and rigorously evaluating a new class of parameter-free, magnitude-aware similarity metrics. I introduce two such functions, Overlap Similarity (OS) and Hyperbolic Tangent Similarity (HTS), designed to integrate vector magnitude and alignment in a more principled manner. To ensure that my findings a
View details →Negative / Null Result ReportOpen accessPhysics
A. D. Kulkarni, R. M. Shannon, D. J. Reardon et al. · 2024 · arXiv
Pulse-to-pulse profile shape variations introduce correlations in pulsar times of arrival (TOAs) across radio frequency measured at the same observational epoch. This leads to a broadband noise in excess of radiometer noise, which is termed pulse jitter noise. The presence of jitter noise limits the achievable timing precision and decreases the sensitivity of pulsar-timing data sets to signals of interest such as nanohertz-frequency gravitational waves. Current white noise models used in pulsar timing analyses attempt to account for this, assuming complete correlation of uncertainties through
View details →Negative / Null Result ReportOpen accessComputer Science
Sungjin Park, Seungwoo Ryu, Edward Choi · 2022 · arXiv
Recent success of pre-trained language models (PLMs) has stimulated interest in their ability to understand and work with numbers. Yet, the numerical reasoning over measurements has not been formally studied despite their importance. In this study, we show that PLMs lack the capability required for reasoning over measurements. Furthermore, we find that a language model trained on a measurement-rich corpus shows better performance on understanding measurements. We propose a simple embedding strategy to better distinguish between numbers and units, which leads to a significant improvement in the
View details →Negative / Null Result ReportOpen accessComputer Science
Ramnath Kumar, Tristan Deleu, Yoshua Bengio · 2022 · arXiv
Recent studies show that task distribution plays a vital role in the meta-learner's performance. Conventional wisdom is that task diversity should improve the performance of meta-learning. In this work, we find evidence to the contrary; (i) our experiments draw into question the efficacy of our learned models: similar manifolds can be learned with a subset of the data (lower task diversity). This finding questions the advantage of providing more data to the model, and (ii) adding diversity to the task distribution (higher task diversity) sometimes hinders the model and does not lead to a signi
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Dominic M. Bowman, Daniel L. Holdsworth · 2019 · arXiv
Context. Modern space telescopes are currently providing high-precision light curves for a large fraction of the sky, such that many new variable stars are being discovered. However, some stars have periodic variability with periods of order minutes and require high-cadence photometry to probe the physical mechanisms responsible. A cadence of less than a minute is often required to remove Nyquist ambiguities and confirm rapid variability which forces observers to obtain high-cadence ground-based photometry. Aims. We aim to provide a modern software package to reduce ground-based photometric ti
View details →Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Francisco Rodríguez · 2022 · arXiv
We revisit the results of a recent paper by Equipo Anova, who claim to find evidence of an improvement in Venezuelan imports of food and medicines associated with the adoption of U.S. financial sanctions towards Venezuela in 2017. We show that their results are consequence of data coding errors and questionable methodological choices, including the use an unreasonable functional form that implies a counterfactual of negative imports in the absence of sanctions, the omission of data accounting for four-fifths of the country's food imports at the time of sanctions and incorrect application of re
View details →Negative / Null Result ReportOpen accessPhysics
Sarbani Basu, H. M. Antia · 1999 · arXiv
Ring diagram analysis can be used to study large scale velocity fields in the outer part of the solar convection zone. All previous works assume that the peak profiles in the solar oscillation power spectrum are symmetric. However, it has now been demonstrated that the peaks are not symmetric. In this work we study how the explicit use of asymmetric peak profiles in ring-diagram analysis influences the estimated velocity fields. We find that the use of asymmetric profiles leads to significant improvement in the fits, but the estimated velocity fields are not substantially different from those
View details →Negative / Null Result ReportOpen accessPhysics
Xian-Yu Wang, Yong-Hao Wang, Songhu Wang et al. · 2021 · arXiv
We present 127 new transit light curves for 39 hot Jupiter systems, obtained over the span of five years by two ground-based telescopes. A homogeneous analysis of these newly collected light curves together with archived spectroscopic, photometric, and Doppler velocimetric data using EXOFASTv2 leads to a significant improvement in the physical and orbital parameters of each system. All of our stellar radii are constrained to accuracies of better than 3\%. The planetary radii for 37 of our 39 targets are determined to accuracies of better than $5\%$. Compared to our results, the literature ecce
View details →Negative / Null Result ReportOpen accessComputer Science
Andreas Hocker · 2001 · arXiv
The recent precise measurement of the muon magnetic anomaly (g-2)_{mu} at BNL opens a window into possible new physics, provided the contribution from hadronic vacuum polarization is well understood. This talk summarizes the development in the evaluation of the leading order hadronic contributions. Significant improvement has been achieved in a series of analyses which is presented historically in three steps: (1), use of tau spectral functions in addition to e+e- cross sections, (2), extended use of perturbative QCD and (3), application of QCD sum rule techniques. The uncertainties, in partic
View details →Negative / Null Result ReportOpen accessComputer Science
Wojciech Zaremba, Evgenia Nitishinskaya, Boaz Barak et al. · 2025 · arXiv
We conduct experiments on the impact of increasing inference-time compute in reasoning models (specifically OpenAI o1-preview and o1-mini) on their robustness to adversarial attacks. We find that across a variety of attacks, increased inference-time compute leads to improved robustness. In many cases (with important exceptions), the fraction of model samples where the attack succeeds tends to zero as the amount of test-time compute grows. We perform no adversarial training for the tasks we study, and we increase inference-time compute by simply allowing the models to spend more compute on reas
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 accessEconomics, Econometrics and Finance
Yuda Bi, Vince D Calhoun · 2026 · arXiv
We address the attribution problem for apparent slow collective dynamics: is the observed persistence intrinsic, or inherited from a persistent driver? For the leading eigenvalue fraction $ψ_1=λ_{\max}/N$ of S\&P 500 60-day rolling correlation matrices ($237$ stocks, 2004--2023), a VIX-coupled Ornstein--Uhlenbeck model reduces the effective relaxation time from $298$ to $61$ trading days and improves the fit over bare mean reversion by $Δ$BIC$=109$. On the decomposition sample, an informational residual of $\log(\mathrm{VIX})$ alone retains most of that gain ($Δ$BIC$=78.6$), whereas a mechanic
View details →Negative / Null Result ReportOpen accessComputer Science
Hongxu Zhou · 2026 · arXiv
Intrinsic self-correction in Large Language Models (LLMs) frequently fails in open-ended reasoning tasks due to ``hallucination snowballing,'' a phenomenon in which models recursively justify early errors during free-text reflection. While structured feedback can mitigate this issue, existing approaches often rely on externally trained critics or symbolic tools, reducing agent autonomy. This study investigates whether enforcing structured reflection purely through Outlines-based constrained decoding can disrupt error propagation without additional training. Evaluating an 8-billion-parameter mo
View details →Negative / Null Result ReportOpen accessPhysics
Md Mamun Al-Rashid, Jayasimha Atulasimha, Supriyo Bandyopadhyay · 2014 · arXiv
Strain-clocked dipole-coupled nanomagnetic logic is an energy-efficient Boolean logic paradigm whose progress has been stymied by its propensity for high error rates. In an effort to mitigate this problem, we have studied the effect of nanomagnet geometry on error rates, focusing on elliptical and cylindrical geometries. We had previously reported that the out-of-plane excursion of the magnetization vector during switching creates a precessional torque that is responsible for high switching error probability in elliptical nanomagnet geometries. The absence of this torque in cylindrical magnets
View details →Negative / Null Result ReportOpen accessComputer Science
Linas Vepstas · 2013 · arXiv
This report describes the suicidality prediction models created under the DARPA DCAPS program in association with the Durkheim Project [http://durkheimproject.org/]. The models were built primarily from unstructured text (free-format clinician notes) for several hundred patient records obtained from the Veterans Health Administration (VHA). The models were constructed using a genetic programming algorithm applied to bag-of-words and bag-of-phrases datasets. The influence of additional structured data was explored but was found to be minor. Given the small dataset size, classification between c
View details →Negative / Null Result ReportOpen accessComputer Science
Shreya Chandrasekhar, Chieh-Yang Huang, Ting-Hao 'Kenneth' Huang · 2023 · arXiv
The rapid growth of scientific publications, particularly during the COVID-19 pandemic, emphasizes the need for tools to help researchers efficiently comprehend the latest advancements. One essential part of understanding scientific literature is research aspect classification, which categorizes sentences in abstracts to Background, Purpose, Method, and Finding. In this study, we investigate the impact of different datasets on model performance for the crowd-annotated CODA-19 research aspect classification task. Specifically, we explore the potential benefits of using the large, automatically
View details →Negative / Null Result ReportOpen accessComputer Science
Egor Shevchenko, Elena Bruches · 2026 · arXiv
Data quality is a critical factor in the effectiveness of machine learning models. Label errors, present even in widely used benchmarks, introduce noise into training data and reduce model generalization. In this work, we conduct a comparative analysis of two automatic label error detection methods - Confident Learning and Dataset Cartography - on three Russian text classification corpora of varying size, number of classes, and domain: ru_emotion_e-culture (49,123 examples, emotion classification), RuCoLA (8,524 examples, linguistic acceptability), and TERRa (2,337 examples, textual entailment
View details →Negative / Null Result ReportOpen accessPhysics
Mohamed M. Fadlallah, Ulrich Eckern · 2017 · arXiv
The structural, electronic, and optical properties of metal (Si, Ge, Sn, and Pb) mono- and co-doped anatase TiO$_{2}$ nanotubes are investigated, in order to elucidate their potential for photocatalytic applications. It is found that Si doped TiO$_{2}$ nanotubes are more stable than those doped with Ge, Sn, or Pb. All dopants lower the band gap, except the (Ge, Sn) co-doped structure, the decrease depending on the concentration and the type of dopant. Correspondingly, a redshift in the optical properties for all kinds of dopings is obtained. Even though a Pb mono- and co-doped TiO$_{2}$ nanotu
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