Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Evaluation of a New Spectral-Domain Optical Coherence Tomography-Based Biometer

The VEMoS-AXL system is a new optical biometer based on spectral domain optical coherence tomography (SD-OCT) that has been tested in terms of intrasession repeatability and compared with a swept-source optical coherence tomography biometer (SS-OCT), which is recognized as the gold standard for the performance of an agreement analysis. A biometric analysis was performed three consecutive times in 120 healthy eyes of 120 patients aged between 18 and 40 years with the SD-OCT system, and afterwards, a single measurement was obtained with the SS-OCT system. Within-subject standard deviations were 0.004 mm, 4.394 µm, and 0.017 mm for axial length (AL), central corneal thickness (CCT), and anterior chamber depth (ACD) measures obtained with the SD-OCT biometer, respectively. The agreement between devices was good for AL (limits of agreement, LoA: −0.04 to 0.03 mm) and CCT (LoA: −4.36 to 14.38 µm), whereas differences between devices were clinically relevant for ACD (LoA: 0.03 to 0.21 mm). In conclusion, the VEMoS-AXL system provides consistent measures of anatomical parameters, being most of them interchangeable with those provided by the SS-OCT-based gold standard.
HOW TO MAKE A POLITY (IN THE CENTRAL MESA VERDE REGION)

The degree to which prehispanic societies in the northern upland Southwest were hierarchical or egalitarian is still debated and seems likely to have changed through time. This paper examines the plausibility of village-spanning polities in the northern Southwest by simulating the coevolution of hierarchy and warfare using extensions to the Village Ecodynamics Project's agent-based model. We additionally compile empirical data on the population size distribution of habitations and ritual spaces (kivas) and the social groups that used them in three large regions of the Pueblo Southwest and analyze these through time. All lines of evidence refute an “autonomous village” model during the Pueblo II period (A.D. 890–1145); rather, they support the existence of village-spanning polities during the Pueblo II and probably into the Pueblo III period (A.D. 1145–1285) in some areas. One or more polities connecting the northern Southwest, with tribute flowing to an apex in Chaco Canyon, appears plausible during Pueblo II for the areas we examine. During Pueblo III, more local organizations likely held sway until depopulation in the late thirteenth century. El grado de igualitarismo o jerarquización social en el seno de las sociedades prehispánicas del norte de las tierras altas del suroeste de Estados Unidos y los cambios de dicho aspecto a través del tiempo continúan siendo objeto de debate. Este trabajo examina la plausibilidad del surgimiento de sistemas de gobierno a nivel de villas múltiples en la región del Suroeste a través de simulaciones sobre la coevolución de la jerarquía y del conflicto utilizando una extensión de la modelización basada en agentes del proyecto Village Ecodynamics. Además, recopilamos datos empíricos sobre la distribución de los tamaños poblacionales en los lugares de habitación y los espacios rituales (kivas), y sobre los grupos sociales que las utilizaron, para tres de las mayores regiones del Suroeste norteamericano, analizando estos datos a través del tiempo. Todas evidencias refutan el modelo de villas autónomas durante el periodo Pueblo II (890–1145 d.C.). Al contrario, las evidencias sugieren el surgimiento de sistemas de gobierno a nivel de villas múltiples durante el periodo Pueblo II y probablemente durante el Pueblo III (1145–1285 d.C.) en algunas áreas. Parece plausible que durante el periodo Pueblo II, uno o más sistemas de gobierno conectaron la zona norte del suroeste de Estados Unidos mediante un sistema de tributos que fluyó hacia un epicentro situado en Chaco Canyon. Probablemente durante el periodo Pueblo III y hasta la despoblación de la región del final del siglo XIII, las organizaciones locales ganaron en influencia.
Evaluating the Efficiency of Surface-Based Air Heating Systems

This study explores the synergistic potential of integrating forced air heating with flat surface heating, presenting a promising solution for structures with intermittent occupancy or where conventional water-based heating proves impractical. The objective is to enhance thermal comfort and reduce long-term energy consumption. A comprehensive examination of the interaction between heated surfaces and forced air heating reveals that excess energy generated can be redirected for more efficient heat distribution. Various scenarios were tested, indicating that the power necessary for maintaining consistent surface temperature could be significantly reduced. A noteworthy approach involves utilizing heat from pellet smoke to maximize heat recovery efficiency from pellet combustion. This, however, raises issues related to smoke introduction into heated spaces. Despite challenges, this approach provides a means to minimize the delivery of overheated air and accumulate energy within room partitions, thereby enhancing system efficiency. The study concludes that while the stand-alone flat surface heating system is better suited as a supplementary heating source within buildings, it offers a compelling alternative within traditional construction, aligning with historical systems.
Three-Dimension Calculation for the Scattering Problem for Non-Spherical Potential

The interaction of the 238U with a neutron is studied. Correct accounting for the non-spherical shape of the uranium nucleus is in focus. The optical potential is used as a model. It is shown that the spherically symmetric and non-spherical potentials give different scattering patterns, in particular different resonance features of the cross-section. The possibility of using the method as an extension of the particle–rotor model of the nucleus is illustrated.
Deadly designs : the impact of road design on road crash patterns along Jamaica’s North Coast Highway

Jamaica has struggled to curb the number of road crash fatalities, having had on average 25 fatalities per month between 2010 and 2014, while many more persons have been injured. The causes of crashes are multidimensional, however this study focused on understanding one aspect of reducing crashes - safe road design. The aim of this study was to determine the relationships between road design characteristics and fatal road crash distribution along the North Coast Highway (NCH) in Jamaica. The Anselin Local Moran’s I and the Getis-Ord Gi* models were employed to look at the distribution of crash hotspots. This paper also utilised Esri’s Weighted Sum Analysis tool to devise a scoring method for determining how safe or dangerous road segments were based on the presence, absence and type of road design features. The design variables selected for this study included bus stops, pedestrian crossings, traffic lights, intersections, places of interest, sidewalks, speed limit, soft shoulders, medians, lanes and roadside barriers. This study also used the zero-inflated negative binomial (ZINB) regression model to identify the empirical relationships between crash counts, crash types, road design features and safety scores. Results The ZINB model identified road segments with many places of interest (POIs), single lane, medians and many intersections as being significantly related to the segments with the most crash counts (irrespective of crash type). This study demonstrates how the spatial analysis of road design features and crash distribution can be used to determine how effective road design features are in advancing road safety and where to implement road safety plans.
Effect of oblique irradiation on the onset of thermal-phototactic-bioconvection in an isotropic scattering algal suspension

In this study, our focus is mainly to check the effect of light scattering on the onset of thermal-phototactic-bioconvection in an algal suspension where the suspension is illuminated by the collimated oblique irradiation from above while simultaneously applying heating or cooling from below. We conduct a numerical investigation into the linear stability of a suspension containing phototactic algae, focusing particularly on how the angle of incidence of oblique collimated irradiation influences the system. Our solutions reveal a transition of the most unstable mode from a stationary to an overstable state, or vice versa, under certain parameter configurations as the angle of incidence varies. Additionally, we frequently observe oscillatory instabilities in cases where the upper surface is rigid, particularly as the angle of incidence increases within the suspension.
A boundary for hyperbolic digraphs and semigroups

Based on a notion by Gray and Kambites of hyperbolicity in the setting of semimetric spaces like digraphs or semigroups, we will construct (under a small additional geometric assumption) a boundary based on quasi-geodesic rays and anti-rays that is preserved by quasi-isometries and, in the case of locally finite digraphs and right cancellative semigroups, refines their ends. Among other results, we show that it is possible to equip the space, if it is finitely based, together with its boundary with a pseudo-semimetric.
Exploiting Style Latent Flows for Generalizing Deepfake Detection Video Detection

This paper presents a new approach for the detection of fake videos, based on the analysis of style latent vectors and their abnormal behavior in temporal changes in the generated videos. We discovered that the generated facial videos suffer from the temporal distinctiveness in the temporal changes of style latent vectors, which are inevitable during the generation of temporally stable videos with various facial expressions and geometric transformations. Our framework utilizes the StyleGRU module, trained by contrastive learning, to represent the dynamic properties of style latent vectors. Additionally, we introduce a style attention module that integrates StyleGRU-generated features with content-based features, enabling the detection of visual and temporal artifacts. We demonstrate our approach across various benchmark scenarios in deepfake detection, showing its superiority in cross-dataset and cross-manipulation scenarios. Through further analysis, we also validate the importance of using temporal changes of style latent vectors to improve the generality of deepfake video detection.
What Motivates People to Trust 'AI' Systems?

Companies, organizations, and governments across the world are eager to employ so-called 'AI' (artificial intelligence) technology in a broad range of different products and systems. The promise of this cause c\'el\`ebre is that the technologies offer increased automation, efficiency, and productivity - meanwhile, critics sound warnings of illusions of objectivity, pollution of our information ecosystems, and reproduction of biases and discriminatory outcomes. This paper explores patterns of motivation in the general population for trusting (or distrusting) 'AI' systems. Based on a survey with more than 450 respondents from more than 30 different countries (and about 3000 open text answers), this paper presents a qualitative analysis of current opinions and thoughts about 'AI' technology, focusing on reasons for trusting such systems. The different reasons are synthesized into four rationales (lines of reasoning): the Human favoritism rationale, the Black box rationale, the OPSEC rationale, and the 'Wicked world, tame computers' rationale. These rationales provide insights into human motivation for trusting 'AI' which could be relevant for developers and designers of such systems, as well as for scholars developing measures of trust in technological systems.
Redefining Event Types and Group Evolution in Temporal Data

Groups -- such as clusters of points or communities of nodes -- are fundamental when addressing various data mining tasks. In temporal data, the predominant approach for characterizing group evolution has been through the identification of ``events". However, the events usually described in the literature, e.g., shrinks/growths, splits/merges, are often arbitrarily defined, creating a gap between such theoretical/predefined types and real-data group observations. Moving beyond existing taxonomies, we think of events as ``archetypes"characterized by a unique combination of quantitative dimensions that we call ``facets". Group dynamics are defined by their position within the facet space, where archetypal events occupy extremities. Thus, rather than enforcing strict event types, our approach can allow for hybrid descriptions of dynamics involving group proximity to multiple archetypes. We apply our framework to evolving groups from several face-to-face interaction datasets, showing it enables richer, more reliable characterization of group dynamics with respect to state-of-the-art methods, especially when the groups are subject to complex relationships. Our approach also offers intuitive solutions to common tasks related to dynamic group analysis, such as choosing an appropriate aggregation scale, quantifying partition stability, and evaluating event quality.
Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines

Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. However, the process by which the encoder produces the text representation is unknown. We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. Using the Diffusion Lens, we perform an extensive analysis of two recent T2I models. Exploring compound prompts, we find that complex scenes describing multiple objects are composed progressively and more slowly compared to simple scenes; Exploring knowledge retrieval, we find that representation of uncommon concepts requires further computation compared to common concepts, and that knowledge retrieval is gradual across layers. Overall, our findings provide valuable insights into the text encoder component in T2I pipelines.
Chiral Spin-Liquid-Like State in Pyrochlore Iridate Thin Films

The pyrochlore iridates have become ideal platforms to unravel fascinating correlated and topolog? ical phenomena that stem from the intricate interplay among strong spin-orbit coupling, electronic correlations, lattice with geometric frustration, and itinerancy of the 5d electrons. The all-in-all? out antiferromagnetic state, commonly considered as the magnetic ground state, can be dramatically altered in reduced dimensionality, leading to exotic or hidden quantum states inaccessible in bulk. Here, by means of magnetotransport, resonant elastic and inelastic x-ray scattering experiments, we discover an emergent quantum disordered state in (111) Y2Ir2O7 thin films (thickness less than 30 nm) per? sisting down to 5 K, characterized by dispersionless magnetic excitations. The anomalous Hall effect observed below an onset temperature near 135 K corroborates the presence of chiral short-range spin configurations expressed in non-zero scalar spin chirality, breaking the macroscopic time-reversal symmetry. The origin of this chiral state is ascribed to the restoration of magnetic frustration on the pyrochlore lattice in lower dimensionality, where the competing exchange interactions together with enhanced quantum fluctuations suppress any long-range order and trigger spin-liquid-like behavior with degenerate ground-state manifold.
Evidence of a Past Merger of the Galactic Center Black Hole

The origin of supermassive black holes (SMBHs) residing in the centers of most galaxies remains a mystery. Various growth models, such as accretion and hierarchical mergers, have been proposed to explain the existence and cosmological evolution of these SMBHs, but no direct observational evidence is available to test these models. The Event Horizon Telescope (EHT) offered direct imaging of nearby SMBHs, in particular, the one at the center of the Milky Way Galaxy named Sgr~A*. Measurements suggest that the Sgr~A* BH spins rapidly with significant spin axis misalignment relative to the angular momentum of the Galactic plane. Through investigating various SMBH growth models, here we show that the spin properties of Sgr~A* provides strong evidence of a past SMBH merger. Inspired by the merger between the Milky Way and Gaia-Enceladus, which has a 4:1 mass ratio as inferred from Gaia data, we have discovered that a 4:1 major merger of SMBH with a binary angular momentum inclination angle of 15-45 degrees with respect to the line of sight (LOS), can successfully replicate the measured spin properties of Sgr A*. This merger event in our galaxy provides observational support for the theory of hierarchical BH mergers in the formation and growth of SMBHs. The inferred merger rate, consistent with theoretical predictions, suggests a promising detection rate of SMBH mergers for space-borne gravitational wave detectors expected to operate in 2030s.
Hybrid Soft Electrostatic Metamaterial Gripper for Multi-surface, Multi-object Adaptation

One of the trendsetting themes in soft robotics has been the goal of developing the ultimate universal soft robotic gripper. One that is capable of manipulating items of various shapes, sizes, thicknesses, textures, and weights. All the while still being lightweight and scalable in order to adapt to use cases. In this work, we report a soft gripper that enables delicate and precise grasps of fragile, deformable, and flexible objects but also excels in lifting heavy objects of up to 1617x its own body weight. The principle behind the soft gripper is based on extending the capabilities of electroadhesion soft grippers through the enhancement principles found in metamaterial adhesion cut and patterning. This design amplifies the adhesion and grasping payload in one direction while reducing the adhesion capabilities in the other direction. This counteracts the residual forces during peeling (a common problem with electroadhesive grippers), thus increasing its speed of release. In essence, we are able to tune the maximum strength and peeling speed, beyond the capabilities of previous electroadhesive grippers. We study the capabilities of the system through a wide range of experiments with single and multiple-fingered peel tests. We also demonstrate its modular and adaptive capabilities in the real-world with a two-finger gripper, by performing grasping tests of up to $5$ different multi-surfaced objects.
Large Lakes Dominate CO2 Evasion From Lakes in an Arctic Catchment

CO2 evasion from freshwater lakes is an important component of the carbon cycle. However, the relative contribution from different lake sizes may vary, since several parameters underlying CO2 flux are size dependent. Here we estimated the annual lake CO2 evasion from a catchment in northern Sweden encompassing about 30,000 differently sized lakes. We show that areal CO2 fluxes decreased rapidly with lake size, but this was counteracted by the greater overall coverage of larger lakes. As a result, total efflux increased with lake size and the single largest lake in the catchment dominated the CO2 evasion (53% of all CO2 evaded). By contrast, the contribution from the smallest ponds (about 27,000) was minor (<6%). Our results emphasize the importance of accounting for both CO2 flux rates and areal contribution of various sized lakes in assessments of CO2 evasion at the landscape scale.
The Prime Geodesic Theorem for the Picard Manifold

We prove the prime geodesic theorem for the Picard manifold whose error term shrinks as the hybrid subconvex exponent $\theta$ for quadratic Dirichlet $L$-functions over Gaussian integers decreases. Our rate of decay is faster than that of Balkanova-Frolenkov (2022) and Kaneko (2022), and leads to the exponent $\frac{202}{139}+\varepsilon$ in the prime geodesic theorem under the generalised Lindel\"{o}f hypothesis $\theta = 0$, improving upon the existing conditional results. This provides further solid evidence towards the validity of the conjectural exponent $1+\varepsilon$.
Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation

High-dimensional sparse data emerge in many critical application domains such as cybersecurity, healthcare, anomaly detection, and trend analysis. To quickly extract meaningful insights from massive volumes of these multi-dimensional data, scientists employ unsupervised analysis tools based on tensor decomposition (TD) methods. However, real-world sparse tensors exhibit highly irregular shapes, data distributions, and sparsity, which pose significant challenges for making efficient use of modern parallel architectures. This study breaks the prevailing assumption that compressing sparse tensors into coarse-grained structures (i.e., tensor slices or blocks) or along a particular dimension/mode (i.e., mode-specific) is more efficient than keeping them in a fine-grained, mode-agnostic form. Our novel sparse tensor representation, Adaptive Linearized Tensor Order (ALTO), encodes tensors in a compact format that can be easily streamed from memory and is amenable to both caching and parallel execution. To demonstrate the efficacy of ALTO, we accelerate popular TD methods that compute the Canonical Polyadic Decomposition (CPD) model across a range of real-world sparse tensors. Additionally, we characterize the major execution bottlenecks of TD methods on multiple generations of the latest Intel Xeon Scalable processors, including Sapphire Rapids CPUs, and introduce dynamic adaptation heuristics to automatically select the best algorithm based on the sparse tensor characteristics. Across a diverse set of real-world data sets, ALTO outperforms the state-of-the-art approaches, achieving more than an order-of-magnitude speedup over the best mode-agnostic formats. Compared to the best mode-specific formats, which require multiple tensor copies, ALTO achieves more than 5.1x geometric mean speedup at a fraction (25%) of their storage.
Nonequilibrium Phase Transition in a 2D Ferromagnetic Spins with Effective Interactions

We investigate nonequilibrium phase transitions in a 2D ferromagnetic Ising model on a square lattice with effective interactions using Monte Carlo-based computational algorithms. We verify the effective parameter $h$ by employing mean-field theory and derive self-consistent equations (SCEs) using two familiar dynamics: Metropolis and Glauber. For $-1<h<1$, both dynamics are expected to estimate the same SCE. We find the relation between $T_{c}$ and $T_{c}^{0}$ where $T_{c}$ ($T_{c}^{0}$) is the critical temperature of the model with (without) the effective interactions. Here, $T_{c}^{0}$ refers to the well-known analytical result of the equilibrium Ising model. We perform the simulations for different lattice sizes that enable us to measure physical quantities of interest. From numerical data, we determine $T_{c}$ and relevant exponents for various values of $h$ by employing finite-size scaling (FSS). We find that the FSS result of $T_{c}$, which is quite different from $T_{c}^{0}$, is in agreement with that of its analytical result, and the accuracy is good regardless of the types of model. The numerical results of the exponents are consistent with the analytical values of the equilibrium 2D Ising model, which belongs to the same universality class.