cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
Creators: name: Osika, Zuzanna
name: Zatarain-Salazar, Jazmin
name: Oliehoek, Frans A.
name: Murukannaiah, Pradeep K.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Multi-objective reinforcement learning (MORL) is used to solve problems involving multiple objectives. An MORL agent must make decisions based on the diverse signals provided by distinct reward functions. Training an MORL agent yields a set of solutions (policies), each presenting distinct trade-offs among the objectives (expected returns). MORL enhances explainability by enabling fine-grained comparisons of policies in the solution set based on their trade-offs as opposed to having a single policy. However, the solution set is typically large and multi-dimensional, where each policy (e.g., a neural network) is represented by its objective values.
 We propose an approach for clustering the solution set generated by MORL. By considering both policy behavior and objective values, our clustering method can reveal the relationship between policy behaviors and regions in the objective space. This approach can enable decision makers (DMs) to identify overarching trends and insights in the solution set rather than examining each policy individually. We tested our method in four multi-objective environments and found it outperformed traditional k-medoids clustering. Additionally, we include a case study that demonstrates its real-world application.
Protein Discovery with Discrete Walk-Jump Sampling
Creators: name: Frey, Nathan C.
name: Berenberg, Daniel
name: Zadorozhny, Karina
name: Kleinhenz, Joseph
name: Lafrance-Vanasse, Julien
name: Hotzel, Isidro
name: Wu, Yan
name: Ra, Stephen
name: Bonneau, Richard
name: Cho, Kyunghyun
name: Loukas, Andreas
name: Gligorijevic, Vladimir
name: Saremi, Saeed
Publisher: name: arXiv
Year: 2023
Subjects: subject: Biomolecules (q-bio.BM)
subject: Machine Learning (cs.LG)
subject: FOS: Biological sciences
subject: FOS: Computer and information sciences

description: We resolve difficulties in training and sampling from a discrete generative model by learning a smoothed energy function, sampling from the smoothed data manifold with Langevin Markov chain Monte Carlo (MCMC), and projecting back to the true data manifold with one-step denoising. Our Discrete Walk-Jump Sampling formalism combines the contrastive divergence training of an energy-based model and improved sample quality of a score-based model, while simplifying training and sampling by requiring only a single noise level. We evaluate the robustness of our approach on generative modeling of antibody proteins and introduce the distributional conformity score to benchmark protein generative models. By optimizing and sampling from our models for the proposed distributional conformity score, 97-100% of generated samples are successfully expressed and purified and 70% of functional designs show equal or improved binding affinity compared to known functional antibodies on the first attempt in a single round of laboratory experiments. We also report the first demonstration of long-run fast-mixing MCMC chains where diverse antibody protein classes are visited in a single MCMC chain.
description: ICLR 2024 oral presentation, top 1.2% of submissions; {ICLR 2023 Physics for Machine Learning, NeurIPS 2023 GenBio, MLCB 2023} Spotlight
Erasure conversion in Majorana qubits via local quasiparticle detection
Creators: name: Alase, Abhijeet
name: Stubbs, Kevin D.
name: Sanders, Barry C.
name: Feder, David L.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quasiparticle poisoning errors in Majorana-based qubits are not suppressed by the underlying topological properties, which undermines the usefulness of this proposed platform. This work tackles the errors originating from intrinsically excited quasiparticles by developing an erasure conversion scheme based on local quasiparticle detection. To model such measurements, we begin by constructing the quasiparticle position operator for the Kitaev chain. A measurement probe coupling to this operator is shown to allow projective measurements in the Wannier quasiparticle basis. Detection of quasiparticles in a region of width $d$ adjacent to each Majorana zero-energy mode allows implementation of an error-detecting Majorana stabilizer code $\mathcal{C}_d$ based on microscopic fermionic (non-topological) physical degrees of freedom. The implementation of $\mathcal{C}_d$ converts a large fraction of Pauli errors to erasure errors, thus achieving `erasure conversion' in Majorana qubits. We show that the fraction of Pauli errors escaping conversion to erasure errors is exponentially small in $d$, a result tied to the exponential localization of Wannier functions which we prove rigorously. The suppression in Pauli error rate comes at the cost of the erasure rate increasing sublinearly with $d$, but this can be readily compensated for by a suitable outer code, with the net effect being a higher threshold rate of quasiparticle poisoning. The framework developed here serves as a basis for understanding how realistic measurements, such as conductance measurements, could be utilized for achieving fault tolerance in these systems.
description: 23 pages including appendices, 8 figures
Active learning of effective Hamiltonian for super-large-scale atomic structures
Creators: name: Ma, Xingyue
name: Chen, Hongying
name: He, Ri
name: Yu, Zhanbo
name: Prokhorenko, Sergei
name: Wen, Zheng
name: Zhong, Zhicheng
name: Iñiguez, Jorge
name: Bellaiche, L.
name: Wu, Di
name: Yang, Yurong
Publisher: name: arXiv
Year: 2023
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: Machine Learning (cs.LG)
subject: Applied Physics (physics.app-ph)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics. However, the parameterization of the effective Hamiltonian is complicated and can be difficult for some complex systems such as high-entropy perovskites. Here, we propose a general form of effective Hamiltonian and develop an active machine learning approach to parameterize the effective Hamiltonian based on Bayesian linear regression. The parameterization is employed in molecular dynamics simulations with the prediction of energy, forces, stress and their uncertainties at each step, which decides whether first-principles calculations are executed to retrain the parameters. Structures of BaTiO$_3$, Pb(Zr$_{0.75}$Ti$_{0.25}$)O$_3$ and (Pb,Sr)TiO$_3$ system are taken as examples to show the accuracy of this approach, as compared with conventional parametrization method and experiments. This machine learning approach provides a universal and automatic way to compute the effective Hamiltonian parameters for any considered complex systems with super-large-scale (more than $10^7$ atoms) atomic structures.
description: 11 pages, 4 figures
OpenAIRE Nexus - D2.1 Dissemination & Exploitation plan report
Creators: name: Pavlidou, Androniki
name: Czesniak, Andreas
name: Vieira, André
name: Moura, Paula
name: Ioannidis, Alex
name: Tournoy, Raphael
name: Papadopoulou, Elli
name: Terrovitis, Manolis
name: Grypari, Ioanna
name: Dimitropoulos, Harry
name: Atzori, Claudio
name: La Bruzzo, Sandro
name: Peroni, Silvio
name: Pierrakos, Dimitris
name: Iatropoulou, Katerina
Publisher: name: Zenodo
Year: 2021
Subjects: OpenAIRE, Nexus

description: This deliverable describes the overall communication strategy of the OpenAIRE-Nexus project, along with the dissemination activities and exploitation plan, with the aim of: i. maximising exposure of OpenAIRE-Nexus’ portfolio of services in a quantitative (KPIs) and qualitative way, ii. engaging with EOSC users and fostering collaboration with INFRAEOSC-03 and INFRAEOSC-07 projects. The communication strategy aims to achieve the OpenAIRE-Nexus communication and project objectives. The major components of this strategy presented in the next sections are identified per OpenAIRE-Nexus portfolio service and are based on: ● Project communication goals. ● Service paths towards sustainability and innovation. ● Project communication plan. ● Communication and dissemination channels. ● Exploitation plan. Information from previous experiences and lessons learnt from past OpenAIRE projects and current INFRAEOSC-03, INFRAEOSC-07 projects are also considered. The report is structured to follow the methodology used to describe the value proposition of the OpenAIRE services portfolios, and based on a well-defined business and brand strategy used by entrepreneurship schools -SMART (S.M.A.R.T - Specific, Measurable, Attainable, Realistic, Timely) objectives and metrics -and communicate the messages to OpenAIRE users and the Open Science community. After the initial analysis of the portfolio services, the report focuses on the potential exploitation techniques that can drive the OpenAIRE portfolio services uptake.
Supplementary document for Instructive errors of Bouguer, Lambert and Arago in the first determinations of angular reflectances on flat surfaces: discussion - 5960758.pdf
Creators: name: Simonot, Lionel
name: Hébert, Mathieu
Publisher: name: Optica Publishing Group
Year: 2022
Subjects: Uncategorized

description: Figures from the original books by Bouguer, Lambert and Arago
Cardinal Characteristics on Bounded Generalised Baire Spaces
Creators: name: van der Vlugt, Tristan
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic (math.LO)
subject: FOS: Mathematics

description: We will give an overview of four families of cardinal characteristics defined on subspaces $\prod_{α\inκ}b(α)$ of the generalised Baire space ${}^κκ$, where $κ$ is strongly inaccessible and $b\in{}^κκ$. The considered families are bounded versions of the dominating, eventual difference, localisation and anti-localisation numbers, and their dual cardinals. We investigate parameters for which these cardinals are non-trivial and how the cardinals relate to each other and to other cardinals of the generalised Cichoń diagram. Finally we prove that different choices of parameters may lead to consistently distinct cardinals.
description: 52 pages
Single machine rescheduling for new orders: properties and complexity results
Creators: name: Rener, Elena
name: Salassa, Fabio
name: T'kindt, Vincent
Publisher: name: arXiv
Year: 2023
Subjects: subject: Discrete Mathematics (cs.DM)
subject: FOS: Computer and information sciences

description: Rescheduling problems arise in a variety of situations where a previously planned schedule needs to be adjusted to deal with unforeseen events. A common problem is the arrival of new orders, i.e. jobs, which have to be integrated into the schedule of the so-called old jobs. The maximum and total absolute time deviations of the completion times of these jobs are modeled as a disruption constraint to limit the change in the original schedule. Disruption constraints affect the shape of an optimal schedule, particularly with respect to the sequencing of old jobs and the insertion of idle time. We therefore give a classification into idle and no-idle problems for a set of single-machine rescheduling problems with different objective functions. We then prove the complexity of five rescheduling problems that have been left open in the literature.
First principles theory of the nitrogen interstitial in hBN: a plausible model for the blue emitter
Creators: name: Ganyecz, Ádám
name: Babar, Rohit
name: Benedek, Zsolt
name: Aharonovich, Igor
name: Barcza, Gergely
name: Ivády, Viktor
Publisher: name: arXiv
Year: 2023
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Color centers in hexagonal boron nitride (hBN) have attracted considerable attention due to their remarkable optical properties enabling robust room temperature photonics and quantum optics applications in the visible spectral range. On the other hand, identification of the microscopic origin of color centers in hBN has turned out to be a great challenge that hinders in-depth theoretical characterization, on-demand fabrication, and development of integrated photonic devices. This is also true for the blue emitter, which is an irradiation damage in hBN emitting at 436 nm wavelengths with desirable properties. Here, we propose the negatively charged nitrogen split interstitial defect in hBN as a plausible microscopic model for the blue emitter. To this end, we carry out a comprehensive first principles theoretical study of the nitrogen interstitial. We carefully analyze the accuracy of first principles methods and show that the commonly used HSE hybrid exchange-correlation functional fails to describe the electronic structure of this defect. Using the generalized Koopman's theorem, we fine tune the functional and obtain a zero-phonon photoluminescence (ZPL) energy in the blue spectral range. We show that the defect exhibits high emission rate in the ZPL line and features a characteristic phonon side band that resembles the blue emitter's spectrum. Furthermore, we study the electric field dependence of the ZPL and numerically show that the defect exhibits a quadratic Stark shift for perpendicular to plane electric fields, making the emitter insensitive to electric field fluctuations in first order. Our work emphasize the need for assessing the accuracy of common first principles methods in hBN and exemplifies a workaround methodology. Furthermore, our work is a step towards understanding the structure of the blue emitter and utilizing it in photonics applications.
description: 33 pages, 10 figures, 3 tables
MPEC 2024-L124 : 2024 LQ3
Creators: name: Minor Planet Center Staff
Publisher: name: The Minor Planet Center
Year: 2024
Subjects: subject: Small Solar System bodies
valueUri: http://astrothesaurus.org/uat/1469
subject: 2024 LQ3

description: The Minor Planet Electronic Circulars contain information on unusual minor planets, routine data on comets and natural satellites, and occasional editorial announcements.  They are published on behalf of Division F of the International Astronomical Union by the Minor Planet Center, Smithsonian Astrophysical Observatory, Cambridge, MA 02138, U.S.A.
Privacy Violations in Election Results
Creators: name: Kuriwaki, Shiro
name: Lewis, Jeffrey B.
name: Morse, Michael
Publisher: name: arXiv
Year: 2023
Subjects: subject: Cryptography and Security (cs.CR)
subject: Applications (stat.AP)
subject: FOS: Computer and information sciences

description: After an election, should election officials release a copy of each anonymous ballot? Some policymakers have championed public disclosure to counter distrust, but others worry that it might undermine ballot secrecy. We introduce the term vote revelation to refer to the linkage of a vote on an anonymous ballot to the voter's name in the public voter file, and detail how such revelation could theoretically occur. Using the 2020 election in Maricopa County, Arizona, as a case study, we show that the release of individual ballot records would lead to no revelation of any vote choice for 99.83% of voters as compared to 99.95% under Maricopa's current practice of reporting aggregate results by precinct and method of voting. Further, revelation is overwhelmingly concentrated among the few voters who cast provisional ballots or federal-only ballots. We discuss the potential benefits of transparency, compare remedies to reduce or eliminate privacy violations, and highlight the privacy-transparency tradeoff inherent in all election reporting.
description: Published version in Science Advances
Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humans
Creators: name: Reviriego, Pedro
name: Conde, Javier
name: Merino-Gómez, Elena
name: Martínez, Gonzalo
name: Hernández, José Alberto
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computation and Language (cs.CL)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: The introduction of Artificial Intelligence (AI) generative language models such as GPT (Generative Pre-trained Transformer) and tools such as ChatGPT has triggered a revolution that can transform how text is generated. This has many implications, for example, as AI-generated text becomes a significant fraction of the text, would this have an effect on the language capabilities of readers and also on the training of newer AI tools? Would it affect the evolution of languages? Focusing on one specific aspect of the language: words; will the use of tools such as ChatGPT increase or reduce the vocabulary used or the lexical richness? This has implications for words, as those not included in AI-generated content will tend to be less and less popular and may eventually be lost. In this work, we perform an initial comparison of the vocabulary and lexical richness of ChatGPT and humans when performing the same tasks. In more detail, two datasets containing the answers to different types of questions answered by ChatGPT and humans, and a third dataset in which ChatGPT paraphrases sentences and questions are used. The analysis shows that ChatGPT tends to use fewer distinct words and lower lexical richness than humans. These results are very preliminary and additional datasets and ChatGPT configurations have to be evaluated to extract more general conclusions. Therefore, further research is needed to understand how the use of ChatGPT and more broadly generative AI tools will affect the vocabulary and lexical richness in different types of text and languages.
Scotland and Immigration: Moving beyond political narratives of openness
Creators: name: Nicolson, Marcus
Publisher: name: Eurac Research
Year: 2022

description: Young adult migrants in Scotland experience racism and discrimination in their everyday lives. This makes it difficult to establish stable identities and to gain a sense of security in the new setting. These traumatic experiences go against the dominant political narrative that Scotland is a receptive country for migrants. As a response, individual migrants are encouraged to adapt their lived experiences to fit with the larger narrative in their security seeking processes.

Debates on immigration continue to polarize debates in world politics. For example, the recent plans announced by the UK government, to process asylum seeker claims in Rwanda, have been met with international condemnation. The devolved nations of the UK have tried to distance themselves from the UK’s hostile immigration policies. Scotland is one such country which has presented a pro-immigration politics.
Disentanglement Learning via Topology
Creators: name: Balabin, Nikita
name: Voronkova, Daria
name: Trofimov, Ilya
name: Burnaev, Evgeny
name: Barannikov, Serguei
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Information Theory (cs.IT)
subject: Differential Geometry (math.DG)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics

description: We propose TopDis (Topological Disentanglement), a method for learning disentangled representations via adding a multi-scale topological loss term. Disentanglement is a crucial property of data representations substantial for the explainability and robustness of deep learning models and a step towards high-level cognition. The state-of-the-art methods are based on VAE and encourage the joint distribution of latent variables to be factorized. We take a different perspective on disentanglement by analyzing topological properties of data manifolds. In particular, we optimize the topological similarity for data manifolds traversals. To the best of our knowledge, our paper is the first one to propose a differentiable topological loss for disentanglement learning. Our experiments have shown that the proposed TopDis loss improves disentanglement scores such as MIG, FactorVAE score, SAP score, and DCI disentanglement score with respect to state-of-the-art results while preserving the reconstruction quality. Our method works in an unsupervised manner, permitting us to apply it to problems without labeled factors of variation. The TopDis loss works even when factors of variation are correlated. Additionally, we show how to use the proposed topological loss to find disentangled directions in a trained GAN.
Organisational readiness to participate in a labelled product service cluster: a structural equation model analysis
Creators: name: Jamai, Kaoutar
name: Gellynck, Xavier
name: Abidar, Ali
name: De Steur, Hans
name: Jamai, Kaoutar
name: Gellynck, Xavier
name: Abidar, Ali
name: De Steur, Hans
Publisher: name: Unknown
Year: 2022
Subjects: subject: Institutional and Behavioral Economics
subject: organisational readiness
subject: small and medium enterprise
subject: labelled products
subject: Morocco
subject: PLS-SEM

description: In the present competitive environment, organisations must inevitably progress to gain and maintain a long-term competitive advantage. Hence, organisations must embrace organisational readiness for change (ORC), which denotes the level of preparedness of an organisation to adopt a change through deploying new management strategies and new projects. This study evaluated the ORC of 70 Moroccan SMEs involved in the sector of labelled agri-food products to join a future innovative cluster. Three dimensions were employed to measure ORC, namely organisational culture, motivation, and climate. Partial least squares-structural equation modelling (PLS-SEM) was used to examine the impact of ORC dimensions on the perceived benefits for the firm. The findings demonstrate that the human factor appeared to be more favourably disposed to change. Organisational motivation displayed a significantly positive effect on perceived benefits through minimising production costs when working together in innovative projects. Despite this, the impact of organisational climate and culture was insignificant. This shows that the selected firms need more support to adopt new changes through integrating a new service cluster and, cooperating together in innovative projects. Our study may support SMEs, policymakers, and researchers in devising guidelines that promote better practices for the agro-food SMEs to function effectively.
GANESH: Generalizable NeRF for Lensless Imaging
Creators: name: Madavan, Rakesh Raj
name: Kaimal, Akshat
name: K, Badhrinarayanan
name: Gupta, Vinayak
name: Choudhary, Rohit
name: Shanmuganathan, Chandrakala
name: Mitra, Kaushik
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Lensless imaging offers a significant opportunity to develop ultra-compact cameras by removing the conventional bulky lens system. However, without a focusing element, the sensor's output is no longer a direct image but a complex multiplexed scene representation. Traditional methods have attempted to address this challenge by employing learnable inversions and refinement models, but these methods are primarily designed for 2D reconstruction and do not generalize well to 3D reconstruction. We introduce GANESH, a novel framework designed to enable simultaneous refinement and novel view synthesis from multi-view lensless images. Unlike existing methods that require scene-specific training, our approach supports on-the-fly inference without retraining on each scene. Moreover, our framework allows us to tune our model to specific scenes, enhancing the rendering and refinement quality. To facilitate research in this area, we also present the first multi-view lensless dataset, LenslessScenes. Extensive experiments demonstrate that our method outperforms current approaches in reconstruction accuracy and refinement quality. Code and video results are available at https://rakesh-123-cryp.github.io/Rakesh.github.io/
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
Creators: name: Liu, Tongkun
name: Li, Bing
name: Du, Xiao
name: Jiang, Bingke
name: Geng, Leqi
name: Wang, Feiyang
name: Zhao, Zhuo
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Image reconstruction-based anomaly detection models are widely explored in industrial visual inspection. However, existing models usually suffer from the trade-off between normal reconstruction fidelity and abnormal reconstruction distinguishability, which damages the performance. In this paper, we find that the above trade-off can be better mitigated by leveraging the distinct frequency biases between normal and abnormal reconstruction errors. To this end, we propose Frequency-aware Image Restoration (FAIR), a novel self-supervised image restoration task that restores images from their high-frequency components. It enables precise reconstruction of normal patterns while mitigating unfavorable generalization to anomalies. Using only a simple vanilla UNet, FAIR achieves state-of-the-art performance with higher efficiency on various defect detection datasets. Code: https://github.com/liutongkun/FAIR.
description: 12 pages, 10 figures
Monmouth University Poll: October 2014 Kansas
Creators: name: Monmouth University Polling Institute
Publisher: name: Roper Center for Public Opinion Research
Year: 2022

description: Registered to vote (1); voter likelihood (1); Senator Pat Roberts vs. Greg Orman for U.S. Senate (5); Governor Sam Brownback vs. State Representative Paul Davis for Kansas Governor (3); President Barack Obama job performance (1); Republican/Democratic control of U.S. Senate (1).
Lepcha also known as “Rong”
Creators: name: Pitek, Emily
Publisher: name: Database of Religious History (DRH)
Year: 2018

description: The Lepcha live along the southern and eastern slopes of Mount Kanchenjunga in the Himalayas, which is located in the districts of Sikkim and Darjeeling, India. This entry focuses specifically on the Lepchas of Lingthem, a town within Sikkim, India. The Lepchas practice at least two different religions, the older Mun religion (named after the priests), and Mahayana Buddhism (often referred to as Lamaism due to Tibetan influence). While the religions are quite contradictory with each other, they are practiced simultaneously and without animosity. Buddhism was introduced to the Sikkim area in the sixteenth century, and the majority of Lepchas now follow the Buddhist faith. As such, when using the term “religious group” this entry is referring to the Buddhist Lepchas.
Twisted convolution algebras with coefficients in a differential subalgebra
Creators: name: Flores, Felipe I.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Operator Algebras (math.OA)
subject: FOS: Mathematics
subject: Primary 43A20, Secondary 47L65, 47L30

description: Let $({\sf G},α, ω,\mathfrak B)$ be a measurable twisted action of the locally compact group ${\sf G}$ on a Banach $^*$-algebra $\mathfrak B$ and $\mathfrak A$ a differential Banach $^*$-subalgebra of $\mathfrak B$, which is stable under said action. We observe that $L^1_{α,ω}({\sf G},\mathfrak A)$ is a differential subalgebra of $L^1_{α,ω}({\sf G},\mathfrak B)$. We use this fact to provide new examples of groups with symmetric Banach $^*$-algebras. In particular, we prove that discrete rigidly symmetric extensions of compact groups are symmetric or that semidirect products ${\sf K}\rtimes{\sf H}$, with ${\sf H}$ symmetric and ${\sf K}$ compact, are symmetric.
description: 9 pages. Some typos are fixed. The title is changed
Supplementary document for Characterization of the human iridocorneal angle in vivo using a custom design goniolens with OCT gonioscopy - 5961538.pdf
Creators: name: Martins, Alessandra Carmichael
name: Gast, Thomas
name: Burns, Stephen
name: Walker, Brittany
name: king, brett
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: subject: Optical Physics not elsewhere classified
subject: Biological Techniques
subject: Biological Physics
subject: FOS: Biological sciences

description: Gonioscopic OCT images for all subjects
Fertilizantes Tocantins: growing in the challenging fertilizer business
Creators: name: Neves, Marcos Fava
name: Neto, Lourival Carmo Monaco
name: Cambaúva, Vinícius
name: Castro, Luciano Thomé E
name: Lourenço, Carlos Eduardo
name: Neves, Marcos Fava
name: Neto, Lourival Carmo Monaco
name: Cambaúva, Vinícius
name: Castro, Luciano Thomé E
name: Lourenço, Carlos Eduardo
Publisher: name: Unknown
Year: 2022
Subjects: subject: Agribusiness
subject: fertilizer
subject: agricultural inputs
subject: agribusiness
subject: Brazil

description: Fertilizantes Tocantins was founded by José Eduardo Motta in 2003, out of his desire of taking advantage of the fast-growing agricultural businesses in the northern region of Brazil. He had previous knowledge of the fertilizer sector due to his work in his father’s business for several years. After an impressive success and enormous growth rates until 2016, 50% plus one shares of the company were sold to EuroChem, a European fertilizer producer. This was part of Fertilizantes Tocantins’ strategy to achieve even greater and sustainable growth. In 2020 EuroChem bought the remaining shares of Fertilizantes Tocantins, becoming its sole controller. The company still maintains most of its operational structure and now is fueled with capital and other assets from EuroChem. The challenge ahead lies in being able to maintain the organizational culture and winning position while bringing the best of its controller’s assets to achieve the goal of being a leader in the Brazilian fertilizer market.
Dynamical subset sampling of quantum error correcting protocols
Creators: name: Heußen, Sascha
name: Winter, Don
name: Rispler, Manuel
name: Müller, Markus
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum error correcting (QEC) stabilizer codes enable protection of quantum information against errors during storage and processing. Simulation of noisy QEC codes is used to identify the noise parameters necessary for advantageous operation of logical qubits in realistic quantum computing architectures. Typical quantum error correction techniques contain intermediate measurements and classical feedback that determine the actual noisy circuit sequence in an instance of performing the protocol. Dynamical subset sampling enables efficient simulation of such non-deterministic quantum error correcting protocols for any type of quantum circuit and incoherent noise of low strength. As an importance sampling technique, dynamical subset sampling allows one to effectively make use of computational resources to only sample the most relevant sequences of quantum circuits in order to estimate a protocol's logical failure rate with well-defined error bars. We demonstrate the capabilities of dynamical subset sampling with examples from fault-tolerant (FT) QEC. We show that, in a typical stabilizer simulation with incoherent Pauli noise of strength $p = 10^{-3}$, our method can reach a required sampling accuracy on the logical failure rate with two orders of magnitude fewer samples than direct Monte Carlo simulation. Furthermore, dynamical subset sampling naturally allows for efficient simulation of realistic multi-parameter noise models describing faulty quantum processors. It can be applied not only for QEC in the circuit model but any noisy quantum computing framework with incoherent fault operators including measurement-based quantum computation and quantum networks.
description: 33 pages, 26 figures
Primordial power spectrum from an objective collapse mechanism: The simplest case
Creators: name: Ocampo, Martin Miguel
name: Palermo, Octavio
name: León, Gabriel
name: Bengochea, Gabriel R.
Publisher: name: arXiv
Year: 2024
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: In this work we analyzed the physical origin of the primordial inhomogeneities during the inflation era. The proposed framework is based, on the one hand, on semiclassical gravity, in which only the matter fields are quantized and not the spacetime metric. Secondly, we incorporate an objective collapse mechanism based on the Continuous Spontaneous Localization (CSL) model, and we apply it to the wavefunction associated with the inflaton field. This is introduced due to the close relation between cosmology and the so-called ``measurement problem'' in Quantum Mechanics. In particular, in order to break the homogeneity and isotropy of the initial Bunch-Davies vacuum, and thus obtain the inhomogeneities observed today, the theory requires something akin to a ``measurement'' (in the traditional sense of Quantum Mechanics). This is because the linear evolution driven by Schrödinger's equation does not break any initial symmetry. The collapse mechanism given by the CSL model provides a satisfactory mechanism for breaking the initial symmetries of the Bunch-Davies vacuum. The novel aspect in this work is that the constructed CSL model arises from the simplest choices for the collapse parameter and operator. From these considerations, we obtain a primordial spectrum that has the same distinctive features as the standard one, which is consistent with the observations from the Cosmic Microwave Background.
description: 9 pages. Final version. Published in BAAA 65
title: Verminderung von Bodenerosion und Nährstoffaustrag durch den Anbau von Durchwachsener Silphie auf erosionsgefährdeten Standorten
Creators: name: Panten, Kerstin
name: Bloem, Elke
name: Koch, Tobias
Publisher: name: Bundesbehörden und Einrichtungen im Geschäftsbereich des Bundesministeriums für Ernährung und Landwirtschaft (BMEL)
Year: 2024
Subjects: subject: 630

description: Flyer aus dem JKI
PhyloJunction: a computational framework for simulating, developing, and teaching evolutionary models
Creators: name: Mendes, Fábio
name: Landis, Michael
Publisher: name: Zenodo
Year: 2024
Subjects: Evolutionary modeling
simulation
graphical model

description: We introduce PhyloJunction, a computational framework designed to facilitate the prototyping, testing, and characterization of evolutionary models. PhyloJunction is distributed as an open-source Python library that can be used to implement a variety of models, through its flexible graphical modeling architecture and dedicated model specification language. Model design and use are exposed to users via command-line and graphical interfaces, which integrate the steps of simulating, summarizing, and visualizing data. This paper describes the features of PhyloJunction – which include, but are not limited to, a general implementation of a popular family of phylogenetic diversification models – and, moving forward, how it may be expanded to not only include new models, but to also become a platform for conducting and teaching statistical learning.
description: Funding provided by: National Science FoundationROR ID: https://ror.org/021nxhr62Award Number: DEB-204034
Softening of $dd$ excitation in the resonant inelastic x-ray scattering spectra as a signature of Hund's coupling in nickelates
Creators: name: Kumar, Umesh
name: Melnick, Corey
name: Kotliar, Gabriel
Publisher: name: arXiv
Year: 2023
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We investigate the effects of Hund's coupling on the resonant X-ray absorption spectra of the recently discovered family of layered nickelate superconductors. We contrast two scenarios depending on the relative strength of the ratio of the effective Hund's coupling ($J_H$) to the crystal fields ($Δ$) in these systems. We carry out the cluster and DFT+DMFT simulations of the RIXS signal at the Ni $L$-edge for different values of Hund's coupling. We find the latter dominates for the parent compound while the former becomes important for sufficiently large doping. Our results are consistent with the observations of a softening of a RIXS peak as a function of doping by Rossi {\sl et al.}~\cite{PhysRevB.104.L220505}, only when the Hund coupling is sizeable. To interpret the results, we separate the theoretical RIXS signal into spin conserving and non-spin conserving channels and conclude that the infinite layer nickelates are in a regime where $Δ$ and $J$ compete effectively and suggest further experimental tests of the theory.
description: 6+6 pages, 5+5 figures
Generalized $XY$ model with competing antiferromagnetic and antinematic interactions
Creators: name: Žukovič, Milan
Publisher: name: arXiv
Year: 2024
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: We study effects of $q$-order antinematic (AN$_q$) interactions on the critical behavior of the antiferromagnetic (AF) $XY$ model on a square lattice. It is found that the evolution of the phase diagram topology of such AF-AN$_q$ models with the parameter $q$ does not follow the same line as for the corresponding FM-N$_q$ models with the ferromagnetic (FM) and $q$-order nematic (N$_q$) interactions. Their phase diagrams are similar only for odd values of the parameter $q$. In such cases the respective phases reported in the FM-N$_q$ models are observed in the AF-AN$_q$ models on each of the two AF-coupled sublattices and the corresponding phase transitions are concluded to be of the same kind. On the other hand, for even values of $q$ the phase diagrams of the AF-AN$_q$ models are different from the FM-N$_q$ models and their topology does not change with $q$. Besides the pure AF and AN$_q$ phases, observed at higher temperatures in the regions of the dominant respective couplings, at low temperatures there is a new canted (C)AF phase, which results from the competition between the AF and AN$_q$ ordering tendencies and has no counterpart in the FM-N$_q$ model. The phase transitions to the CAF phase from both AF and AN$_q$ phases appear to be of the BKT nature.
description: 22 pages
Learnable Cross-modal Knowledge Distillation for Multi-modal Learning with Missing Modality
Creators: name: Wang, Hu
name: Ma, Congbo
name: Zhang, Jianpeng
name: Zhang, Yuan
name: Avery, Jodie
name: Hull, Louise
name: Carneiro, Gustavo
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: The problem of missing modalities is both critical and non-trivial to be handled in multi-modal models. It is common for multi-modal tasks that certain modalities contribute more compared to other modalities, and if those important modalities are missing, the model performance drops significantly. Such fact remains unexplored by current multi-modal approaches that recover the representation from missing modalities by feature reconstruction or blind feature aggregation from other modalities, instead of extracting useful information from the best performing modalities. In this paper, we propose a Learnable Cross-modal Knowledge Distillation (LCKD) model to adaptively identify important modalities and distil knowledge from them to help other modalities from the cross-modal perspective for solving the missing modality issue. Our approach introduces a teacher election procedure to select the most ``qualified'' teachers based on their single modality performance on certain tasks. Then, cross-modal knowledge distillation is performed between teacher and student modalities for each task to push the model parameters to a point that is beneficial for all tasks. Hence, even if the teacher modalities for certain tasks are missing during testing, the available student modalities can accomplish the task well enough based on the learned knowledge from their automatically elected teacher modalities. Experiments on the Brain Tumour Segmentation Dataset 2018 (BraTS2018) shows that LCKD outperforms other methods by a considerable margin, improving the state-of-the-art performance by 3.61% for enhancing tumour, 5.99% for tumour core, and 3.76% for whole tumour in terms of segmentation Dice score.
Tame deformations of highly singular function germs
Creators: name: Joiţa, Cezar
name: Stockinger, Matteo
name: Tibăr, Mihai
Publisher: name: arXiv
Year: 2023
Subjects: subject: Algebraic Geometry (math.AG)
subject: Complex Variables (math.CV)
subject: FOS: Mathematics
subject: 14B07, 32S30, 14D06, 32S55, 14P15

description: We give analytic and algebraic conditions under which a deformation of real analytic functions with non-isolated singular locus is a deformation with fibre constancy.
description: final version
Monmouth University Poll: October 2014 New Jersey 2nd Congressional District
Creators: name: Monmouth University Polling Institute
Publisher: name: Roper Center for Public Opinion Research
Year: 2022

description: Registered to vote (1); voter likelihood (1); Congressman Frank LoBiondo vs. Bill Hughes for U.S. Congress (4); opinion of public figures (2); President Barack Obama job performance (1); U.S. House of Representatives job performance (1); LoBiondo vs. Hughes on issues/concerns (5); Republican/Democratic control of Congress (1).
Flavour Physics at LHCb -- 50 years of the KM paradigm
Creators: name: Koppenburg, Patrick
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Experiment (hep-ex)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: The LHCb experiment is in operation since 2009 and has provided measurements of the KM matrix with unprecedented precision. 50 years after the original paper we are in the position of pinning down the parameters of the theory, or possibly to show its limitations. In these proceedings the status of LHCb is shown in a historical perspective, along with some anecdotes.
description: Proceedings for the PTEP KM50 Special Section
Supplementary document for Characterization of the human iridocorneal angle in vivo using a custom design goniolens with OCT gonioscopy - 5961538.pdf
Creators: name: Martins, Alessandra Carmichael
name: Gast, Thomas
name: Burns, Stephen
name: Walker, Brittany
name: king, brett
Publisher: name: Optica Publishing Group
Year: 2022
Subjects: subject: Optical Physics not elsewhere classified
subject: Biological Techniques
subject: Biological Physics
subject: FOS: Biological sciences

description: Gonioscopic OCT images for all subjects
2-Form U(1) Spin Liquids: Classical Model and Quantum Aspects
Creators: name: Chung, Kristian Tyn Kai
name: Gingras, Michel J. P.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We introduce a novel geometrically frustrated classical Ising model, dubbed the "spin vorticity model", whose ground state manifold is a novel classical spin liquid, a "2-form Coulomb phase". We study the thermodynamics of this model both analytically and numerically, exposing the presence of algebraically decaying correlations and demonstrating an extensive ground state entropy, and give a comprehensive account of its ground state properties and excitations. Each classical ground state may be decomposed into collections of closed 2-dimensional membranes, supporting fractionalized string excitations attached to the boundaries of open membranes. At finite temperature, the model can then be described as a gas of closed strings in a background of fluctuating membranes. We demonstrate that the emergent gauge structure of the low-temperature phase is naturally captured in the formalism of 2-form electrodynamics, which describes 1-dimensional charged strings coupled to a rank-2 anti-symmetric gauge field. After establishing the classical spin vorticity model, we consider perturbing it with quantum exchange interactions, from which we derive an effective membrane exchange model of the quantum dynamics of these membranes, which maps to a frustrated 2-form U(1) lattice gauge theory. We show the existence of a fine-tuned Rokhsar-Kivelson point where the quantum ground state is an equal weight superposition of all classical ground state configurations. We further demonstrate how to quantize the string excitations, by coupling a 1-form string field to the emergent 2-form U(1) gauge field, thus mapping a quantum spin model to a 2-form gauge-Higgs model. We discuss the stability of the gapless deconfined phase of this gauge theory and the possibility of realizing a novel class of phases of quantum matter: 2-form U(1) quantum spin liquids.
description: 44 pages, 19 figures, 1 table
Uplifting edges in higher order networks: spectral centralities for non-uniform hypergraphs
Creators: name: Contreras-Aso, Gonzalo
name: Pérez-Corral, Cristian
name: Romance, Miguel
Publisher: name: arXiv
Year: 2023
Subjects: subject: Spectral Theory (math.SP)
subject: Mathematical Physics (math-ph)
subject: Computational Physics (physics.comp-ph)
subject: Physics and Society (physics.soc-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: Spectral analysis of networks states that many structural properties of graphs, such as centrality of their nodes, are given in terms of their adjacency matrices. The natural extension of such spectral analysis to higher order networks is strongly limited by the fact that a given hypergraph could have several different adjacency hypermatrices, hence the results obtained so far are mainly restricted to the class of uniform hypergraphs, which leaves many real systems unattended. A new method for analysing non-linear eigenvector-like centrality measures of non-uniform hypergraphs is presented in this paper that could be useful for studying properties of $\mathcal{H}$-eigenvectors and $\mathcal{Z}$-eigenvectors in the non-uniform case. In order to do so, a new operation - the $\textit{uplift}$ - is introduced, incorporating auxiliary nodes in the hypergraph to allow for a uniform-like analysis. We later argue why this is a mathematically sound operation, and we furthermore use it to classify a whole family of hypergraphs with unique Perron-like $\mathcal{Z}$-eigenvectors. We supplement the theoretical analysis with several examples and numerical simulations on synthetic and real datasets.
description: 29 pages, 8 figures
Helical Rope Cluster Packings of Tetrahedra: Dense Configurations in Finite and Infinite Spaces
Creators: name: Gohil, Harshkumar
Publisher: name: Zenodo
Year: 2025
Subjects: tetrahedral packing
aperiodic packing
packing density
polyhedral packing
synthetic biology
tetrahedra
packing
3D Euclidean space
non-lattice packing

description: Latex file.
Supplementary document for Mask 3D parameter optimization for improving imaging contrast of plasmonic lithography - 6987778.pdf
Creators: name: He, Jianfang
name: Ding, Huwen
name: Wei, Yayi
name: Ye, Tian-Chun
Publisher: name: Optica Publishing Group
Year: 2024
Subjects: Uncategorized

description: 518309