Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum variational principles for time-harmonic waves in a dissipative medium and associated variational principles of Hashin–Shtrikman type

Minimization variational principles for linear elastodynamic, acoustic or electromagnetic time-harmonic waves in dissipative media were obtained by Milton et al. (Milton et al. 2009 Proc. R. Soc. A 465, 367–396 (doi:10.1098/rspa.2008.0195)), generalizing the quasistatic variational principles of Cherkaev and Gibiansky (Cherkaev & Gibiansky 1994 J. Math. Phys. 35, 127–145 (doi:10.1063/1.530782)). Here, a further generalization is made to allow for a much wider variety of boundary conditions, and in particular Dirichlet and Neumann boundary conditions. In addition minimization or maximization principles of the Hashin–Shtrikman type, incorporating ‘polarization fields’, are developed. The corresponding principles for static problems have found substantial use in bounding the effective static properties of composite materials. The new dynamical principles offer the prospect of developing bounds on the effective dynamic properties of such materials.
Generating abelian groups by addition only

Abstract We define the positive diameter of a finite group G with respect to a generating set A ⊆ G to be the smallest non-negative integer n such that every element of G can be written as a product of at most n elements of A. This invariant, which we denote by , can be interpreted as the diameter of the Cayley digraph induced by A on G. In this paper we study the positive diameters of a finite abelian group G with respect to its various generating sets A. More specifically, we determine the maximum possible value of and classify all generating sets for which this maximum value is attained. Also, we determine the maximum possible cardinality of A subject to the condition that is “not too small”. Conceptually, the problems studied are closely related to our earlier work [Klopsch and Lev, J. Algebra 261: 145–171, 2003] and the results obtained shed a new light on the subject. Our original motivation came from connections with caps, sum-free sets, and quasi-perfect codes.
12 Years of Self-tracking for Promoting Physical Activity from a User Diversity Perspective: Taking Stock & Thinking Ahead

Despite the indisputable personal and societal benefits of regular physical activity, a large portion of the population does not follow the recommended guidelines, harming their health and wellness. The World Health Organization has called upon governments, practitioners, and researchers to accelerate action to address the global prevalence of physical inactivity. To this end, an emerging wave of research in ubiquitous computing has been exploring the potential of interactive self-tracking technology in encouraging positive health behavior change. Numerous findings indicate the benefits of personalization and inclusive design regarding increasing the motivational appeal and overall effectiveness of behavior change systems, with the ultimate goal of empowering and facilitating people to achieve their goals. However, most interventions still adopt a “one-size-fits-all” approach to their design, assuming equal effectiveness for all system features in spite of individual and collective user differences. To this end, we analyze a corpus of 12 years of research in self-tracking technology for health behavior change, focusing on physical activity, to identify those design elements that have proven most effective in inciting desirable behavior across diverse population segments. We then provide actionable recommendations for designing and evaluating behavior change self-tracking technology based on age, gender, occupation, fitness, and health condition. Finally, we engage in a critical commentary on the diversity of the domain and discuss ethical concerns surrounding tailored interventions and directions for moving forward.
OdomBeyondVision: An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum

This paper presents a multimodal indoor odometry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms. Not only does OdomBeyondVision contain the traditional navigation sensors, sensors such as IMUs, mechanical LiDAR, RGBD camera, it also includes several emerging sensors such as the single-chip mmWave radar, LWIR thermal camera and solid-state LiDAR. With the above sensors on UAV, UGV and handheld platforms, we respectively recorded the multimodal odometry data and their movement trajectories in various indoor scenes and different illumination conditions. We release the exemplar radar, radar-inertial and thermal-inertial odometry implementations to demonstrate their results for future works to compare against and improve upon. The full dataset including toolkit and documentation is publicly available at: https://github.com/MAPS-Lab/OdomBeyondVision.
Structure Learning for Hybrid Bayesian Networks

Bayesian networks have been used as a mechanism to represent the joint distribution of multiple random variables in a ﬂexible yet interpretable manner. One major challenge in learning the structure of a Bayesian network is how to model networks which include a mixture of continuous and discrete random variables, known as hybrid Bayesian networks. This paper overviews the literature on approaches to handle hybrid Bayesian networks. Typically one of two approaches is taken: either the data are considered to have a joint distribution which is designed for a mixture of discrete and continuous variables, or continuous random variables are discretized, resulting in discrete Bayesian networks. In this paper, we propose a strategy to model all random variables as Gaussian, referred to it as Run it As Gaussian (RAG) . We demonstrate that RAG results in more reliable estimates of graph structures theoretically and by simulation studies, than converting continuous random variables to discrete. Both strategies are also implemented on a childhood obesity data set. The two diﬀerent strategies give rise to signiﬁcant diﬀerences in the optimal graph structures, with the results of the simulation study suggesting that our strategy is more reliable.
Anisotropic Gigahertz Antiferromagnetic Resonances of the Easy-Axis van der Waals Antiferromagnet CrSBr.

We report measurements of antiferromagnetic resonances in the van der Waals easy-axis antiferromagnet CrSBr. The interlayer exchange field and magnetocrystalline anisotropy fields are comparable to laboratory magnetic fields, allowing a rich variety of gigahertz-frequency dynamical modes to be accessed. By mapping the resonance frequencies as a function of the magnitude and angle of applied magnetic field, we identify the different regimes of antiferromagnetic dynamics. The spectra show good agreement with a Landau-Lifshitz model for two antiferromagnetically coupled sublattices, accounting for interlayer exchange and triaxial magnetic anisotropy. Fits allow us to quantify the parameters governing the magnetic dynamics: At 5 K, the interlayer exchange field is μ0HE = 0.395(2) T, and the hard and intermediate-axis anisotropy parameters are μ0Hc = 1.30(2) T and μ0Ha = 0.383(7) T. The existence of within-plane anisotropy makes it possible to control the degree of hybridization between the antiferromagnetic resonances using an in-plane magnetic field.
Quasi-2D anomalous Hall Mott insulator of topologically engineered Jeff =1/2 electrons

Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee 37996, USA Department of Physics, University of Tokyo, Tokyo, Japan Department of Condensed Matter Physics and Materials Science, Brookhaven National Laboratory, Upton, New York 11973, USA Department of Physics, Oklahoma State University, Stillwater, OK 74078 Department of Condensed Matter Physics, Charles University, Ke Karlovu 5, 12116 Prague, Czech Republic Anhui Key Laboratory of Condensed Matter Physics at Extreme Conditions, High Magnetic Field Laboratory, HFIPS, Chinese Academy of Sciences, Hefei, Anhui 230031, China Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, USA School of Physical Sciences, Dublin City University, Dublin 9, Ireland
OmniXAI: A Library for Explainable AI

We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to address the pain points of understanding and interpreting the decisions made by machine learning (ML) in practice. OmniXAI aims to be a one-stop comprehensive library that makes explainable AI easy for data scientists, ML researchers and practitioners who need explanation for various types of data, models and explanation methods at different stages of ML process (data exploration, feature engineering, model development, evaluation, and decision-making, etc). In particular, our library includes a rich family of explanation methods integrated in a unified interface, which supports multiple data types (tabular data, images, texts, time-series), multiple types of ML models (traditional ML in Scikit-learn and deep learning models in PyTorch/TensorFlow), and a range of diverse explanation methods including"model-specific"and"model-agnostic"ones (such as feature-attribution explanation, counterfactual explanation, gradient-based explanation, etc). For practitioners, the library provides an easy-to-use unified interface to generate the explanations for their applications by only writing a few lines of codes, and also a GUI dashboard for visualization of different explanations for more insights about decisions. In this technical report, we present OmniXAI's design principles, system architectures, and major functionalities, and also demonstrate several example use cases across different types of data, tasks, and models.
Detecting the Severity of Major Depressive Disorder from Speech: A Novel HARD-Training Methodology

Major Depressive Disorder (MDD) is a common worldwide mental health issue with high associated socioeconomic costs. The prediction and automatic detection of MDD can, therefore, make a huge impact on society. Speech, as a non-invasive, easy to collect signal, is a promising marker to aid the diagnosis and assessment of MDD. In this regard, speech samples were collected as part of the Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD) research programme. RADAR-MDD was an observational cohort study in which speech and other digital biomarkers were collected from a cohort of individuals with a history of MDD in Spain, United Kingdom and the Netherlands. In this paper, the RADAR-MDD speech corpus was taken as an experimental framework to test the efficacy of a Sequence-to-Sequence model with a local attention mechanism in a two-class depression severity classification paradigm. Additionally, a novel training method, HARD-Training, is proposed. It is a methodology based on the selection of more ambiguous samples for the model training, and inspired by the curriculum learning paradigm. HARD-Training was found to consistently improve - with an average increment of 8.6% - the performance of our classifiers for both of two speech elicitation tasks used and each collection site of the RADAR-MDD speech corpus. With this novel methodology, our Sequence-to-Sequence model was able to effectively detect MDD severity regardless of language. Finally, recognising the need for greater awareness of potential algorithmic bias, we conduct an additional analysis of our results separately for each gender.
Alg\`ebres amass\'ees et applications

Sergey Fomin and Andrei Zelevinsky have invented cluster algebras at the beginning of this decade with the aim of creating an algebraic framework for the study of canonical bases in quantum groups and total positivity in algebraic groups. It soon turned out that the combinatorics of cluster algebras also appear in many other subjects and notably in the representation theory of quivers and finite-dimensional algebras. In this talk, we give a concise introduction to cluster algebras and sketch two significant applications concerning the study of certain discrete dynamical systems and the construction of dual semicanonical bases. ----- Sergey Fomin et Andrei Zelevinsky ont invent\'e les alg\`ebres amass\'ees (cluster algebras) au d\'ebut des ann\'ees 2000 dans le but de fournir un cadre alg\'ebrique \`a l'\'etude des bases canoniques dans les groupes quantiques et de la positivit\'e totale dans les groupes alg\'ebriques. Il s'est av\'er\'e rapidement que la combinatoire des alg\`ebres amass\'ees intervenait \'egalement dans de nombreux autres sujets et notamment en th\'eorie des repr\'esentations des carquois et des alg\`ebres de dimension finie. Dans cet expos\'e, nous donnons une introduction concise aux alg\`ebres amass\'ees et esquissons deux applications significatives portant sur l'\'etude de certains syst\`emes dynamiques discrets et la construction de bases duales semi-canoniques.
Measuring surplus capacity for multiobjective optimal design of foul sewer systems

ABSTRACT This paper proposes a new performance index of foul sewer systems, i.e. sewer conveyance capacity (SCC) index, to quantify the surplus capacity for multi-objective optimization design problems. The use of the new SCC index is demonstrated using a hypothetical network and a real-world foul sewer network. Results obtained show clear trade-offs between SCC and the other two objectives considered, i.e., capital and operational costs and greenhouse gas emissions. The results show that the upstream sewers in the system often have a relatively large surplus capacity, while the sewer mains operate close to the design capacity. Moreover, SCC is compared with three common indicators at both individual sewer and system-wide levels. Strong correlations between SCC and other indicators are revealed, implying that SCC is a good representation of system performance and can provide a more comprehensive picture of the foul sewer system performance.
On Pointwise Gradient Estimates for the Complex Monge-Ampere Equation

In this note, a gradient estimate for the complex Monge-Ampere equation is established. It differs from previous estimates of Yau, Hanani, Blocki, P. Guan, B. Guan - Q. Li in that it is pointwise, and depends only on the infimum of the solution instead of its $C^0$ norm.
Optimization of the GPU-based data evaluation for the low coherence interferometry

Abstract Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg–Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.
Non‐intrusive parameter estimation method for autotuned DC–DC converter based on quasi‐impulse response

A non-intrusive method to estimate the values of power-stage components online and autotuning of feedback compensator for digitally controlled power converters is presented in this study. By using buck converter as an example, the presented autotuning controller has been designed to cover the wide-range variations in equivalent series resistance zero of the output capacitor and the resonant frequency of output filter L o C o . These two frequencies are estimated by examining the converter's quasi-impulse response during start-up and by measuring the output-voltage ripple during steady-state operation of the converter. Hence, due to the non-intrusive characteristic of the proposed control method, the operation of the converter is not affected. Using the acquired results, the online digital compensator is tuned automatically based on predefined crossover frequency and phase margin to provide the required output-voltage regulation and transient response under wide-range variations in the power-stage component values. To validate the effectiveness of the proposed control method, experimental results from a 12 to 1.5 V buck converter are presented.
Largeness of LERF and 1-relator groups

We consider largeness of groups given by a presentation of deficiency 1, where the group is respectively free-by-cyclic, LERF or 1-relator. We give the first examples of (finitely generated free)-by-(infinite cyclic) word hyperbolic groups which are large, show that a LERF deficiency 1 group with first Betti number at least 2 is large or the integers times the integers, and show that 2-generator 1-relator groups where the relator has height 1 obey the dichotomy that either the group is large or all its finite images are metacyclic.
FOCUS: PROTEOMICS On-Line Strong Cation Exchange -HPLC-ESI-MS/MS for Protein Identification and Process Optimization

We have developed an on-line strong cation exchange (SCX)-ESI-MS/MS platform for the rapid identification of proteins contained in mixtures. This platform consists of a SCX precolumn followed by a nanoflow SCX column on-line with an electrospray ion trap mass spectrometer. We also used this platform to study the dynamics of peptide separation/ extraction by SCX, in particular to understand the parameters affecting the performance of SCX in multidimensional chromatography. For example, we have demonstrated that the buffer typically used for tryptic digestion of protein mixtures can have a detrimental effect on the chromatographic behaviour of peptides during SCX separations, thereby affecting certain peptide quantitation approaches that rely on reproducible peptide fractionation. We have also demonstrated that band broadening results when a step (discontinuous) gradient approach is used to displace peptides from the SCX precolumn, reducing the separation power of SCX in multidimensional chromatography. In contrast, excellent chromatographic peak shapes are observed when a defined (continuous) gradient is used. Finally, using a tryptic digest of a protein extract derived from human K562 cells, we observed that larger molecular weight peptides are identified using this on-line SCX approach compared to the more conventional reverse phase (RP) LC/MS approach. Both methods used in tandem complement each other and can lead to a greater number of peptide identifications from a given sample. (J Am Soc Mass Spectrom 2003, 14, 719–727) © 2003 American Society for Mass Spectrometry
A partial $A_\infty$-structure on the cohomology of $C_n\times C_m$

Suppose k is a field of characteristic 2, and $n,m\geq 4$ powers of 2. Then the $A_\infty$-structure of the group cohomology algebras $H^*(C_n,k)$ and $(H^*(C_m,k)$ are well known. We give results characterizing an $A_\infty$-structure on $H^*(C_n\times C_m,k)$ including limits on non-vanishing low-arity operations and an infinite family of non-vanishing higher operations.
Highresolution analysis of a QTL for resistance to Stagonospora nodorum glume blotch on chromosome 3B of Bread Wheat (Triticum aestivum L)

Stagonospora nodorum glume blotch (SNG), caused by the necrotrophic fungus Stagonospora nodorum, is one of the economically important diseases of bread wheat (Triticum aestivum L.). Resistance to SNG is known to be quantitative and previous studies of a recombinant inbred line (RIL) population identified a major quantitative trait locus (QTL) for resistance to SNG on the short arm of chromosome 3B. To localize this QTL (QSng.sfr-3BS) with high resolution, we constructed a genetic map for the QTL target region using information from sequenced flow-sorted chromosomes 3B of the two parental cultivars, the physical map of chromosome 3B of cultivar 'Chinese Spring' and BAC-clone sequences. The mapping population of near-isogenic lines (NIL) was evaluated for SNG resistance in field infection tests. NILs segregated for disease resistance as well as for plant height, additionally, we observed a high environmental influence on the trait. Our analysis detected a strong negative correlation of SNG resistance and plant height. Further analysis of the target region identified two linked loci associated with SNG resistance. One of them was also associated with plant height, revealing an effect of QSng.sfr-3BS on plant height that was hidden in the RIL population. This result demonstrates an unexpectedly high genetic complexity of resistance controlled by QSng.sfr-3BS and shows the importance of the study of QTL in mendelized form in NILs.
Motivic structures in non-commutative geometry

We review some recent results and conjectures saying that, roughly speaking, periodic cyclic homology of a smooth non-commutative algebraic variety should carry all the additional "motivic" structures possessed by the usual de Rham cohomology of a smooth algebraic variety (specifically, an R-Hodge structure for varieties over R, and a filtered Dieudonne module structure for varieties over Z_p). To appear in Proc. ICM 2010.
Noncommutative supertori in two dimensions

First we consider the deformations of superspaces with = (1, 1) and = (2, 2) supersymmetries in two dimensions. Among these the construction of noncommutative supertorus with odd spin structure is possible only in the case of = (2, 2) supersymmetry broken down to = (1, 1). However, for the even spin structures the construction of noncommutative supertorus is possible for both = (1, 1) and = (2, 2) cases. The spin structures are realized by implementing the translational properties along the cycles of commutative supertorus in the operator version: Odd spin structure is realized by the translation in the fermionic direction in the same manner as in the construction of noncommutative torus, and even spin structures are realized with appropriate versions of the spin angular momentum operator.
Evaluation of Biot-Savart integrals on tetrahedral meshes

An arithmetically simple method has been developed for the evaluation of Biot--Savart integrals on tetrahedralized distributions of vorticity. In place of the usual approach of analytical formulae for the velocity induced by a linear distribution of vorticity on a tetrahedron, the integration is performed using Gaussian quadrature and a ray tracing technique from computer graphics. This eliminates completely the need for the evaluation of square roots, logarithms and arc tangents, and almost completely eliminates the requirement for trigonometric functions, with no operation more costly than a division required during the main calculation loop. An assessment of the algorithm's performance is presented, demonstrating its accuracy, second order convergence and near-linear speedup on parallel systems.