Miracle-dz/UniFAR-FTUs huggingface dataset:
The graphical attractiveness and perceived effectiveness of cartographic presentations of spatio-temporal accessibility

A comparison was made of 6 mapping techniques based on a monocentric road network model. The analysed methods included two-dimensional and three-dimensional visualisations in three colour scale variants. All of the graphical solutions were based on elements of reference: points, lines, or surfaces. Perceived effectiveness was researched on the basis of visualisations of spatial accessibility measured along roads (road accessibility in kilometres), while graphical attractiveness - on the basis of visualisations of temporal accessibility counted in minutes. Test tasks covered by the internet survey consisted in a comparison of 6 mapping techniques and an indication of the best and worst visualisation. The number of positive and negative votes of respondents to the internet survey was used to calculate measures of perceived effectiveness and graphical attractiveness for each mapping technique. The impact of various colour scales on indications given by survey participants was also analysed.
Comparison of seismic sources for shallow seismic: sledgehammer and pyrotechnics

Abstract The pyrotechnic materials are one of the types of the explosives materials which produce thermal, luminous or sound effects, gas, smoke and their combination as a result of a self-sustaining chemical reaction. Therefore, pyrotechnics can be used as a seismic source that is designed to release accumulated energy in a form of seismic wave recorded by tremor sensors (geophones) after its passage through the rock mass. The aim of this paper was to determine the utility of pyrotechnics for shallow seismic engineering. The work presented comparing the conventional method of seismic wave excitation for seismic refraction method like plate and hammer and activating of firecrackers on the surface. The energy released by various sources and frequency spectra was compared for the two types of sources. The obtained results did not determine which sources gave the better results but showed very interesting aspects of using pyrotechnics in seismic measurements for example the use of pyrotechnic materials in MASW.
Implementasi Algoritma Fuzzy C Means Dan Statistical Region Merging Pada Segmentasi Citra

Segmentasi citra berbasis clustering pada penelitian ini menggunakan metode Fuzzy C Means dengan menerapkan fungsi objektif Xie Beni Index. Preprocessing diterapkan pada model yang dikembangkan ini menggunakan metode Statistical Region Merging. Spatial function diterapkan pada metode Fuzzy C Means untuk mengurangi noise pada saat clustering. Evaluasi sistem dilakukan dengan pengukuran nilai cluster validity (Xie Beni Index), waktu eksekusi, dan jumlah iterasi. Hasil pengujian pada tiga buah citra uji menunjukan metode yang diusulkan mampu melakukan segmentasi citra dengan baik
An Analysis of Two-Spirit, Lesbian, Gay, Bisexual, Transgender and Queer Research Funded by Canadian Institutes of Health Research

Purpose: Gender identity and sexual orientation are essential factors that must be incorporated into health research to ensure we unearth comprehensive and inclusive insights about the healthcare needs and experiences of diverse people. Despite the calls for more focus on sex and gender in health research, scant attention has been paid to gender identity or sexual orientation. Past research found that 0.35% of Canadian Institutes of Health Research (CIHR) grant abstracts mentioned studying lesbian, gay, bisexual, transgender, queer and/or Two-Spirit (2S/LGBTQ+)-specific health outcomes. However, the nature of that research was not explored. Methods: Here we examine the publicly available database of grant abstracts funded by CIHR from 2009-2020 to analyze what type of 2S/LGBTQ+-specific health outcomes would be studied. Results: We found that 58% of awarded grant abstracts mentioned studying sexually transmitted diseases, the majority of which were on human immunodeficiency virus (HIV). Less than 7% of funded 2S/LGBTQ+ grant abstracts mentioned studying cisgender women. Almost 40% mentioned including trans women/girls, and 30% mentioned including trans men/ boys. None of the studies examined mentioned work with the Two- Spirit community. Conclusion: These results reflect larger social and health inequities that require structural level changes in research to support lesbian, bisexual and queer women health.
Current circulation near additional energy degeneracy points in quadratic Fermionic networks

We study heat and particle current circulation (CC) in quadratic fermionic systems analysed using local Lindblad master equation. It was observed in an earlier study \cite{Our_circulation} that CC occurs near the additional energy degeneracy point (AEDP) in fermionic systems which have some form of asymmetry. We find general analytical expression to support this observation for quadratic fermionic networks. We then apply these ideas to the Su-Schrieffer-Heeger (SSH) model with periodic boundary conditions and a tight binding model with unequal hopping strengths in the upper and lower branches. In both these cases, we find the specific conditions required for observing CC and study the behavior of these currents with various system parameters. We find that having an unequal number of fermionic sites in the upper and lower branches is enough for generating CC in the SSH model. However, this asymmetry is not adequate for the tight-binding model and we require unequal hopping strengths in the upper and lower branches to induce CC in this model. Finally, we observe that for certain system parameters, the onset point of particle and heat CC are not the same. Based on all these observations, we describe how carefully examining the energy spectrum of the system gives a great deal of information about the possibility and behavior of CC in fermionic systems with asymmetries.
Field sources in a planar anisotropic CPT-odd gauge model

In the present paper we study some new classical Lorentz violating effects in planar electrodynamics due to the presence of stationary point-like field sources. Starting from the Carroll-Field-Jackiw model defined in (3+1) dimensions, which belongs to the electromagnetic CPT-odd sector of the Standard Model Extension (SME), we apply the dimensional reduction procedure obtaining a (2+1)-dimensional model that encompasses an electromagnetic sector composed of the Maxwell-Chern-Simons electrodynamics, a pure scalar sector described by a massless Klein-Gordon field, and a mixed sector where the background vector mediates contributions involving both the scalar and the gauge fields. For all the sectors of this planar theory, we explore some physical phenomena that arise from the interactions between external sources. Specifically, we obtain perturbative effects up to second order in the background vector related to the presence of both electric and scalar planar charges and Dirac points.
CineMPC: A Fully Autonomous Drone Cinematography System Incorporating Zoom, Focus, Pose, and Scene Composition

We present CineMPC, a complete cinematographic system that autonomously controls a drone to film multiple targets recording user-specified aesthetic objectives. Existing solutions in autonomous cinematography control only the camera extrinsics, namely, its position and orientation. In contrast, CineMPC is the first solution that includes the camera intrinsic parameters in the control loop, which are essential tools for controlling cinematographic effects such as focus, depth of field, and zoom. The system estimates the relative poses between the targets and the camera from an RGB-D image and optimizes a trajectory for the extrinsic and intrinsic camera parameters to film the artistic and technical requirements specified by the user. The drone and the camera are controlled in a nonlinear model predicted control (MPC) loop by reoptimizing the trajectory at each time step in response to current conditions in the scene. The perception system of CineMPC can track the targets' position and orientation despite the camera effects. Experiments in a photo-realistic simulation and with a real platform demonstrate the capabilities of the system to achieve a full array of cinematographic effects that are not possible without the control of the intrinsics of the camera. Code for CineMPC is implemented following a modular architecture in ROS and released to the community.
The Geometrization of Maxwell's Equations and the Emergence of Gravity and Antimatter

Coupling the Maxwell tensor to the Riemann-Christoffel curvature tensor is shown to lead to a geometricized theory of electrodynamics. While this geometricized theory leads directly to the classical Maxwell equations, it also extends their physical interpretation by giving charge density, mass density and the four-velocity that describes their motions geometric definitions. Assuming the existence of a conserved energy-momentum tensor, all solutions to the geometricized theory of electrodynamics developed here are shown to be consistent with the emergence of gravity obeying the General Relativity field equation augmented by a term that mimics the properties of dark matter and/or dark energy. Finally, due to the symmetries of the theory, the properties and phenomenology of antimatter emerge in solutions.
Supramolecular assemblies in active motor-filament systems: micelles, bilayers, and foams

Active matter systems evade the constraints of thermal equilibrium, leading to the emergence of intriguing collective behavior. A paradigmatic example is given by motor-filament mixtures, where the motion of motor proteins drives alignment and sliding interactions between filaments and their self-organization into macroscopic structures. After defining a microscopic model for these systems, we derive continuum equations, exhibiting the formation of active supramolecular assemblies such as micelles, bilayers and foams. The transition between these structures is driven by a branching instability, which destabilizes the orientational order within the micelles, leading to the growth of bilayers at high microtubule densities. Additionally, we identify a fingering instability, modulating the shape of the micelle interface at high motor densities. We study the role of various mechanisms in these two instabilities, such as contractility, active splay, and anchoring, allowing for generalization beyond the system considered here.
Neural Population Learning beyond Symmetric Zero-sum Games

We study computationally efficient methods for finding equilibria in n-player general-sum games, specifically ones that afford complex visuomotor skills. We show how existing methods would struggle in this setting, either computationally or in theory. We then introduce NeuPL-JPSRO, a neural population learning algorithm that benefits from transfer learning of skills and converges to a Coarse Correlated Equilibrium (CCE) of the game. We show empirical convergence in a suite of OpenSpiel games, validated rigorously by exact game solvers. We then deploy NeuPL-JPSRO to complex domains, where our approach enables adaptive coordination in a MuJoCo control domain and skill transfer in capture-the-flag. Our work shows that equilibrium convergent population learning can be implemented at scale and in generality, paving the way towards solving real-world games between heterogeneous players with mixed motives.
EmMixformer: Mix transformer for eye movement recognition

Eye movement (EM) is a new highly secure biometric behavioral modality that has received increasing attention in recent years. Although deep neural networks, such as convolutional neural network (CNN), have recently achieved promising performance, current solutions fail to capture local and global temporal dependencies within eye movement data. To overcome this problem, we propose in this paper a mixed transformer termed EmMixformer to extract time and frequency domain information for eye movement recognition. To this end, we propose a mixed block consisting of three modules, transformer, attention Long short-term memory (attention LSTM), and Fourier transformer. We are the first to attempt leveraging transformer to learn long temporal dependencies within eye movement. Second, we incorporate the attention mechanism into LSTM to propose attention LSTM with the aim to learn short temporal dependencies. Third, we perform self attention in the frequency domain to learn global features. As the three modules provide complementary feature representations in terms of local and global dependencies, the proposed EmMixformer is capable of improving recognition accuracy. The experimental results on our eye movement dataset and two public eye movement datasets show that the proposed EmMixformer outperforms the state of the art by achieving the lowest verification error.
Improved modelling of SEP event onset within the WSA–Enlil–SEPMOD framework

Multi-spacecraft observations of solar energetic particle (SEP) events enable not only a for deeper understanding and development of particle acceleration and transport theories, but also provide important constraints for model validation efforts. However, because of computational limitations, a given physics-based SEP model is usually best-suited to capture a particular phase of an SEP event, rather than its whole development from onset through decay. For example, magnetohydrodynamic (MHD) models of the heliosphere often incorporate solar transients only at the outer boundary of their so-called coronal domain—usually set at a heliocentric distance of 20–30 R☉. This means that particle acceleration at CME-driven shocks is also computed from this boundary onwards, leading to simulated SEP event onsets that can be many hours later than observed, since shock waves can form much lower in the solar corona. In this work, we aim to improve the modelled onset of SEP events by inserting a "fixed source" of particle injection at the outer boundary of the coronal domain of the coupled WSA–Enlil 3D MHD model of the heliosphere. The SEP model that we employ for this effort is SEPMOD, a physics-based test-particle code based on a field line tracer and adiabatic invariant conservation. We apply our initial tests and results of SEPMOD's fixed-source option to the 2021 October 9 SEP event, which was detected at five well-separated locations in the inner heliosphere—Parker Solar Probe, STEREO-A, Solar Orbiter, BepiColombo, and near-Earth spacecraft.
SARA: A Collection of Sensitivity-Aware Relevance Assessments

Large archival collections, such as email or government documents, must be manually reviewed to identify any sensitive information before the collection can be released publicly. Sensitivity classification has received a lot of attention in the literature. However, more recently, there has been increasing interest in developing sensitivity-aware search engines that can provide users with relevant search results, while ensuring that no sensitive documents are returned to the user. Sensitivity-aware search would mitigate the need for a manual sensitivity review prior to collections being made available publicly. To develop such systems, there is a need for test collections that contain relevance assessments for a set of information needs as well as ground-truth labels for a variety of sensitivity categories. The well-known Enron email collection contains a classification ground-truth that can be used to represent sensitive information, e.g., the Purely Personal and Personal but in Professional Context categories can be used to represent sensitive personal information. However, the existing Enron collection does not contain a set of information needs and relevance assessments. In this work, we present a collection of fifty information needs (topics) with crowdsourced query formulations (3 per topic) and relevance assessments (11,471 in total) for the Enron collection (mean number of relevant documents per topic = 11, variance = 34.7). The developed information needs, queries and relevance judgements are available on GitHub and will be available along with the existing Enron collection through the popular ir_datasets library. Our proposed collection results in the first freely available test collection for developing sensitivity-aware search systems.
DiffSHEG: A Diffusion-Based Approach for Real-Time Speech-driven Holistic 3D Expression and Gesture Generation

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint generation of synchronized expressions and gestures remains barely explored. To address this, our diffusion-based co-speech motion generation transformer enables uni-directional information flow from expression to gesture, facilitating improved matching of joint expression-gesture distributions. Furthermore, we introduce an outpainting-based sampling strategy for arbitrary long sequence generation in diffusion models, offering flexibility and computational efficiency. Our method provides a practical solution that produces high-quality synchronized expression and gesture generation driven by speech. Evaluated on two public datasets, our approach achieves state-of-the-art performance both quantitatively and qualitatively. Additionally, a user study confirms the superiority of DiffSHEG over prior approaches. By enabling the real-time generation of expressive and synchronized motions, DiffSHEG showcases its potential for various applications in the development of digital humans and embodied agents.
Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects

Our world is full of identical objects (\emphe.g., cans of coke, cars of same model). These duplicates, when seen together, provide additional and strong cues for us to effectively reason about 3D. Inspired by this observation, we introduce Structure from Duplicates (SfD), a novel inverse graphics framework that reconstructs geometry, material, and illumination from a single image containing multiple identical objects. SfD begins by identifying multiple instances of an object within an image, and then jointly estimates the 6DoF pose for all instances.An inverse graphics pipeline is subsequently employed to jointly reason about the shape, material of the object, and the environment light, while adhering to the shared geometry and material constraint across instances. Our primary contributions involve utilizing object duplicates as a robust prior for single-image inverse graphics and proposing an in-plane rotation-robust Structure from Motion (SfM) formulation for joint 6-DoF object pose estimation. By leveraging multi-view cues from a single image, SfD generates more realistic and detailed 3D reconstructions, significantly outperforming existing single image reconstruction models and multi-view reconstruction approaches with a similar or greater number of observations.
Autonomous Navigation of Tractor-Trailer Vehicles through Roundabout Intersections

In recent years, significant advancements have been made in the field of autonomous driving with the aim of increasing safety and efficiency. However, research that focuses on tractor-trailer vehicles is relatively sparse. Due to the physical characteristics and articulated joints, such vehicles require tailored models. While turning, the back wheels of the trailer turn at a tighter radius and the truck often has to deviate from the centre of the lane to accommodate this. Due to the lack of publicly available models, this work develops truck and trailer models using the high-fidelity simulation software CARLA, together with several roundabout scenarios, to establish a baseline dataset for benchmarks. Using a twin-q soft actor-critic algorithm, we train a quasi-end-to-end autonomous driving model which is able to achieve a 73% success rate on different roundabouts.
MISS: Multiclass Interpretable Scoring Systems

In this work, we present a novel, machine-learning approach for constructing Multiclass Interpretable Scoring Systems (MISS) - a fully data-driven methodology for generating single, sparse, and user-friendly scoring systems for multiclass classification problems. Scoring systems are commonly utilized as decision support models in healthcare, criminal justice, and other domains where interpretability of predictions and ease of use are crucial. Prior methods for data-driven scoring, such as SLIM (Supersparse Linear Integer Model), were limited to binary classification tasks and extensions to multiclass domains were primarily accomplished via one-versus-all-type techniques. The scores produced by our method can be easily transformed into class probabilities via the softmax function. We demonstrate techniques for dimensionality reduction and heuristics that enhance the training efficiency and decrease the optimality gap, a measure that can certify the optimality of the model. Our approach has been extensively evaluated on datasets from various domains, and the results indicate that it is competitive with other machine learning models in terms of classification performance metrics and provides well-calibrated class probabilities.
Peripheral factors affecting human colour perception

Human colour perception is mediated by multiple factors. These include: the external environment, physiological structures within the eye, and the neuronal pathways that originate in the eye. The aim of this thesis was to further investigate the impact of three main factors on both the perception and cortical representation of colour. These factors were: the external, changing seasonal environment, genetically determined differences in the number of photoreceptor types, and spatial filters inherent to cortical and pre-cortical luminance and chromatic pathways. Novel findings and methods were demonstrated in this thesis: 1) For the first time, it was found that natural seasonal changes in the chromatic environment (in York, UK) affect the perception of unique yellow; this finding supports the existence of a slow normalisation mechanism, which is governed by changes in the average chromatic environment. 2) Genetically atypical individuals, who have fewer photoreceptor types (dichromats), demonstrated no differences in achromatic contrast discrimination thresholds compared to colour-normal trichromats. Therefore, for this particular measure, dichromats do not appear to benefit from increased neuronal resources from ‘unused’ chromatic pathway populations. A multi-channel LED system was developed to allow the isolation of photoreceptor responses in individuals with an additional photoreceptor type (tetrachromats). Modelling of this system indicated that precision in the cone spectra used to generate the stimulus, relative to the observer’s actual cone sensitivities (i.e. peak wavelength sensitivities), is crucial for successful isolation of the cones. 3) fMRI-based population receptive field (pRF) mapping was used to measure pRF sizes in the pre-cortical channels. Between the pathways, no differences in pRF sizes were found, however, differences in fMRI measures of spatial frequency sensitivity were observed. These data indicate that spatial frequency tuning in early visual cortex may be decoupled from population receptive field sizes.