Miracle-dz/UniFAR-FTUs huggingface dataset:
The process of polarisation as a loss of dimensionality: measuring changes in polarisation using Singular Value Decomposition of network graphs

The increasing polarisation in our societies is a major international concern. Current approaches to defining and detecting polarisation largely rely on finding evidence of bimodality in social networks or voter opinion surveys. It is difficult to detect temporal trends in polarisation, as the results usually fall into a binary of polarised or non-polarised, which cannot robustly show that subsequent increases in bimodality are statistically significant. Our work is aligned with Baldassari and Gelman's theory that polarisation should be defined as increasing correlation between positions in the ideological field. We also draw from post-structuralist work which argues that polarisation is the process of both the ideological and material layers of society being segregated into two poles, as in cases of apartheid. Thus, in order to measure the polarisation in a society, it would be beneficial to be able to assess social networks directly. In this paper we use Random Dot Product Graphs to embed social networks in metric spaces. In the case of a social network, the embedded dimensionality corresponds to the number of reasons any two people may form a social connection. A decrease in the optimal dimensionality for the embedding of the network graph, as measured using truncated Singular Value Decomposition of the graph adjacency matrix, indicates increasing polarisation in the network. We apply this method to two different Twitter networks based on discussions of climate change, and show that our methods agree with other researchers' detection of polarisation in this space. We also use networks generated by stochastic block models to explore how an increase of the isolation between distinct communities in a network, or the increase in the predominance of one community over the other, are identifiable as polarisation processes.
Existence and role of low energy charge-paramagnon modes in the strange metal phase of Bi$_2$Sr$_2$CaCu$_2$O$_{8+y}$

The strange metal phase is characteristic for the $T$-linear dc resistivity behaviour over a large $T$-range. The effect of the strength of the charge-paramagnon interactions on the charge fluctuations in optimally doped and underdoped regions of Bi$_2$Sr$_2$CaCu$_2$O$_{8+y}$ (Bi-2212) may shine light on the anomalous behaviour of the optical conductivity response in the energy range 50 - 500 meV. We present a preliminary analysis of a single initial run of electron energy loss spectroscopy (EELS) measurements done in a scanning transmission electron microscope (STEM) which exhibit linear dispersive modes separated by 50 meV energy gaps up to 250 meV in optimally doped Bi-2212. Our observations show similarities with the fluctuating stripes as predicted by Zaanen.
Differentiation and Death of Premyelinating Oligodendrocytes in Developing Rodent Brain

Previous studies have indicated that newly formed oligodendrocytes are dynamic cells whose production, survival, and differentiation depend upon axonal influences. This study has characterized the appearance and fate of newly formed oligodendrocytes in developing rat brain. Oligodendrocytes appear in predictable locations and radially extend DM-20–positive processes that cover 80-μm domains in the cortex and 40-μm domains in the corpus callosum. These premyelinating oligodendrocytes have one of two fates: they myelinate axons or degenerate. Between 7 and 21 d after birth, ∼20% of premyelinating oligodendrocytes identified in the cerebral cortex were degenerating. Oligodendrocytes that ensheathed axons expressed and selectively targeted proteolipid protein to compact myelin and did not degenerate. These observations support the hypothesis that axonal influences affect oligodendrocyte survival, differentiation, and expression of proteolipid protein gene products.
DVLO: Deep Visual-LiDAR Odometry with Local-to-Global Feature Fusion and Bi-Directional Structure Alignment

Information inside visual and LiDAR data is well complementary derived from the fine-grained texture of images and massive geometric information in point clouds. However, it remains challenging to explore effective visual-LiDAR fusion, mainly due to the intrinsic data structure inconsistency between two modalities: Images are regular and dense, but LiDAR points are unordered and sparse. To address the problem, we propose a local-to-global fusion network with bi-directional structure alignment. To obtain locally fused features, we project points onto image plane as cluster centers and cluster image pixels around each center. Image pixels are pre-organized as pseudo points for image-to-point structure alignment. Then, we convert points to pseudo images by cylindrical projection (point-to-image structure alignment) and perform adaptive global feature fusion between point features with local fused features. Our method achieves state-of-the-art performance on KITTI odometry and FlyingThings3D scene flow datasets compared to both single-modal and multi-modal methods. Codes will be released later.
Missing Data and Measurement Variability in Assessing Progression-Free Survival Endpoint in Randomized Clinical Trials

Progression-free survival (PFS) is frequently used as the primary efficacy endpoint in the evaluation of cancer treatment that is considered for marketing approval. Missing or incomplete data problems become more acute with a PFS endpoint (compared with overall survival). In a given clinical trial, it is common to observe incomplete data due to premature treatment discontinuation, missed or flawed assessments, change of treatment, lack of follow-up, and unevaluable data. When incomplete data issues are substantial, interpretation of the data becomes tenuous. Plans to prevent, minimize, or properly analyze incomplete data are critical for generalizability of results from the clinical trial. Variability in progressive disease measurement between radiologists further contributes to data problems with a PFS endpoint. The repercussions of this on phase III clinical trials are complex and depend on several factors, including the magnitude of the variability and whether there is a systematic reader evaluation bias favoring one treatment arm particularly in open-label trials. Clin Cancer Res; 19(10); 2613–20. ©2013 AACR.
Object Pose Estimation via the Aggregation of Diffusion Features

Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very large benchmarks. However, these methods experience a significant performance drop when dealing with unseen objects. We believe that it results from the limited generalizability of image features. To address this problem, we have an in-depth analysis on the features of diffusion models, e.g. Stable Diffusion, which hold substantial potential for modeling unseen objects. Based on this analysis, we then innovatively introduce these diffusion features for object pose estimation. To achieve this, we propose three distinct architectures that can effectively capture and aggregate diffusion features of different granularity, greatly improving the generalizability of object pose estimation. Our approach outperforms the state-of-the-art methods by a considerable margin on three popular benchmark datasets, LM, O-LM, and T-LESS. In particular, our method achieves higher accuracy than the previous best arts on unseen objects: 98.2% vs. 93.5% on Unseen LM, 85.9% vs. 76.3% on Unseen O-LM, showing the strong generalizability of our method. Our code is released at https://github.com/Tianfu18/diff-feats-pose.
Tunnel-shaped potential force fields for improved hand-guiding of robotic arms

In this paper we introduce a new approach for improving hand-guiding of robotic arms. We present the tunnel-shaped potential force field (TSPFF) which guides the user along a reference trajectory in order to improve the user comfort of handling robots. The reference trajectory is computed using the learning data of experienced users. The TSPFF is realized by an impedance control of the robot. The main focus of this paper is to find a robust parametrization of the TSPFF. For this purpose the stability of user-robot interaction is analyzed by means of the Lyapunov stability theory. The results are complemented by simulation studies in which the influence of the parametrization on control performance and user comfort is analyzed. The resulting rules for parametrization are validated by experimental studies with a robot with six degrees of freedom.
Level of environmental threat posed by horticultural trade in Cactaceae

Ornamental horticulture has been identified as an important threat to plant biodiversity and is a major pathway for plant invasions worldwide. In this context, the family Cactaceae is particularly challenging because it is considered the fifth most threatened large taxonomic group in the world; several species are among the most widespread and damaging invasive species; and Cactaceae is one of the most popular horticultural plant groups. Based on the Convention on International Trade in Endangered Species of Wild Flora and Fauna and the 11 largest online auction sites selling cacti, we documented the international cactus trade. To provide an in‐depth look at the dynamics of the industry, we surveyed the businesses involved in the cactus trade in South Africa (a hotspot of cactus trade and invasions). We purchased seeds of every available species and used DNA barcoding to identify species to the genus level. Although <20% of this trade involved threatened species and <3% involved known invasive species, many species were identified by a common name. However, only 0.02% of the globally traded cacti were collected from wild populations. Despite a large commercial network, all South African imports (of which 15% and 1.5% were of species listed as threatened and invasive, respectively) came from the same source. With DNA barcoding, we identified 24% of the species to genus level. Based on our results, we believe that if trade restrictions are placed on the small proportion of cacti that are invasive and there is no major increase in harvesting of native populations, then the commercial trade in cactus poses a negligible environmental threat. However, there are currently no effective methods for easily identifying which cacti are traded, and both the illicit harvesting of cacti from the wild and the informal trade in invasive taxa pose on‐going conservation challenges.
Vision-Based Force Estimation for Minimally Invasive Telesurgery Through Contact Detection and Local Stiffness Models

In minimally invasive telesurgery, obtaining accurate force information is difficult due to the complexities of in-vivo end effector force sensing. This constrains development and implementation of haptic feedback and force-based automated performance metrics, respectively. Vision-based force sensing approaches using deep learning are a promising alternative to intrinsic end effector force sensing. However, they have limited ability to generalize to novel scenarios, and require learning on high-quality force sensor training data that can be difficult to obtain. To address these challenges, this paper presents a novel vision-based contact-conditional approach for force estimation in telesurgical environments. Our method leverages supervised learning with human labels and end effector position data to train deep neural networks. Predictions from these trained models are optionally combined with robot joint torque information to estimate forces indirectly from visual data. We benchmark our method against ground truth force sensor data and demonstrate generality by fine-tuning to novel surgical scenarios in a data-efficient manner. Our methods demonstrated greater than 90% accuracy on contact detection and less than 10% force prediction error. These results suggest potential usefulness of contact-conditional force estimation for sensory substitution haptic feedback and tissue handling skill evaluation in clinical settings.
Finding Rectangle Intersections by Divide-and-Conquer

In this correspondence we reconsider three geometrical problems for which we develop divide-and-conquer algorithms. The first problem is to find all pairwise intersections among a set of horizontal and vertical line segments. The second is to report all points enclosures occurring in a mixed set of points and rectangles, and the third is to find all pairwise intersections in a set of isooriented rectangles. We derive divide-and-conquer algorithms for the first two problems which are then combined to solve the third. In each case a space-and time-optimal algorithm is obtained, that is O(n) space and O(n log n + k) time, where n is the number of given objects and k is the number of reported pairs. These results show that divide-and-conquer can be used in place of line sweep, without additional asymptotic cost, for some geometrical problems. This raises the natural question: For which class of problems are the line sweep and divide-and-conquer paradigms interchangeable?
Deep Learning for Traffic Flow Prediction using Cellular Automata-based Model and CNN-LSTM architecture

Recent works have attempted to use deep learning to predict future states of traffic flow, but have met with mixed results. These approaches face two key challenges. First, training deep learning neural networks requires large amounts of training data which are not yet easily available for traffic flow systems. Second, even when data is available, the neural networks require access to historical data that covers most possible traffic flow dynamics to successfully predict future traffic states. Specifically, these deep learning approaches do not fully leverage domain-knowledge about traffic flow dynamics, despite a significant existing knowledge-base. In this work, we propose to solve both issues using a Convolutional Neural Network (CNNs) with Long Short Term Memory (LSTM) deep learning architecture to successfully predict traffic flow, while leveraging a cellular automata-based statistical mechanics model of traffic flow to generate training and test data. Another major contribution of this paper is the insight that training data for a large traffic system can actually be sampled from the simulations of a much smaller traffic system. This is achieved through observing that the normalized energy distribution of the statistical mechanics model is scale invariant, which significantly eases the burden of data generation for large scale traffic systems. The resulting simulations indicate good agreement between the predicted and the true traffic flow dynamics.
Immediate vs . delayed insertion of intrauterine contraception after second trimester abortion : study protocol for a randomized controlled trial

Background: We describe the rationale and protocol for a randomized controlled trial (RCT) to assess whether intrauterine contraception placed immediately after a second trimester abortion will result in fewer pregnancies than current recommended practice of intended placement at 4 weeks post-abortion. Decision analysis suggests the novel strategy could substantially reduce subsequent unintended pregnancies and abortions. This paper highlights considerations of design, implementation and evaluation of a trial expected to provide rigorous evidence for appropriate insertion timing and health economics of intrauterine contraception after second trimester abortion. Methods/Design: Consenting women choosing to use intrauterine contraception after abortion for a pregnancy of 12 to 24 weeks will be randomized to insertion timing groups either immediately (experimental intervention) or four weeks (recommended care) post abortion. Primary outcome measure is pregnancy rate at one year. Secondary outcomes include: cumulative pregnancy rates over five year follow-up period, comprehensive health economic analyses comparing immediate and delayed insertion groups, and device retention rates, complication rates (infection, expulsion) and, contraceptive method satisfaction. Web-based Contraception Satisfaction Questionnaires, clinical records and British Columbia linked health databases will be used to assess primary and secondary outcomes. Enrolment at all clinics in the province performing second trimester abortions began in May 2010 and is expected to complete in late 2011. Data on one year outcomes will be available for analysis in 2014. Discussion: The RCT design combined with access to clinical records at all provincial abortion clinics, and to information in provincial single-payer linked administrative health databases, birth registry and hospital records, offers a unique opportunity to evaluate such an approach by determining pregnancy rate at one through five years among enrolled women. We highlight considerations of design, implementation and evaluation of a trial expected to provide rigorous evidence for appropriate insertion timing and health economics of intrauterine contraception after second trimester abortion. Trial registration: Current Controlled Trials ISRCTN19506752
Long-Term Effects of Bupivacaine on Cartilage in a Rabbit Shoulder Model

Background Previous investigations have reported on the chondrotoxicity of bupivacaine in short-term in vivo and in vitro models. This study was designed to provide additional information on the long-term effects of bupivacaine infusion on articular cartilage in an established rabbit shoulder model. Hypothesis Infusion of bupivacaine into the rabbit shoulder will have long-term deleterious effects on articular cartilage. Study Design Controlled laboratory study. Methods Thirty-six rabbits were randomized into 3 groups and were infused over 48 hours with saline (S), bupivacaine alone (B), or bupivacaine with epinephrine (B+E) into the glenohumeral joint. Animals were sacrificed after 3 months, and tissue samples were analyzed with live/dead cell assay, proteoglycan (PG) synthesis and content assays, and conventional histological evaluation. Results No macroscopic or radiographic changes were detected in the infused shoulders. Sulfate uptake of infused shoulders relative to controls was elevated to 112% ± 39% (S), 166% ± 67% (B), and 210% ± 127% (B+E). Statistical analysis of PG content demonstrated significantly increased levels in bupivacaine groups compared with saline. There were no significant differences among groups in cell count, percentage of living cells, or histological grade. Conclusions No permanent impairment of cartilage function was detected 3 months after intra-articular infusion of bupivacaine. Cartilage metabolism was increased, indicating a possible reparative response. This suggests that, at least in the model used, articular cartilage has the ability to recover from the chondrotoxic effects of bupivacaine infusion. Before extrapolating these results to human cartilage, other factors including underlying cartilage injury or disease, decreased chondrocyte density, and increased bupivacaine dosing need to be taken into account. Clinical Relevance Bupivacaine toxicity has recently been implicated in the development of chondrolysis after arthroscopic shoulder procedures, but these findings suggest that additional noxious stimuli might be required before permanent damage ensues.
LocoMan: Advancing Versatile Quadrupedal Dexterity with Lightweight Loco-Manipulators

Quadrupedal robots have emerged as versatile agents capable of locomoting and manipulating in complex environments. Traditional designs typically rely on the robot's inherent body parts or incorporate top-mounted arms for manipulation tasks. However, these configurations may limit the robot's operational dexterity, efficiency and adaptability, particularly in cluttered or constrained spaces. In this work, we present LocoMan, a dexterous quadrupedal robot with a novel morphology to perform versatile manipulation in diverse constrained environments. By equipping a Unitree Go1 robot with two low-cost and lightweight modular 3-DoF loco-manipulators on its front calves, LocoMan leverages the combined mobility and functionality of the legs and grippers for complex manipulation tasks that require precise 6D positioning of the end effector in a wide workspace. To harness the loco-manipulation capabilities of LocoMan, we introduce a unified control framework that extends the whole-body controller (WBC) to integrate the dynamics of loco-manipulators. Through experiments, we validate that the proposed whole-body controller can accurately and stably follow desired 6D trajectories of the end effector and torso, which, when combined with the large workspace from our design, facilitates a diverse set of challenging dexterous loco-manipulation tasks in confined spaces, such as opening doors, plugging into sockets, picking objects in narrow and low-lying spaces, and bimanual manipulation.
A Sociotechnical Readiness Level Framework for the Development of Advanced Nuclear Technologies

The Technology Readiness Level (TRL) scale was initially developed by NASA in the 1970s and is now widely used in space, nuclear, and other complex technology sectors in the US and beyond. The TRL scale is particularly useful for determining where extrapolation of untested sub-systems or features could produce technical risk, cause expensive redesigns, or act as a roadblock to technology development. In this paper, we propose the development of a sociotechnical readiness level (SRL), premised on the understanding that the successful development and eventual use of a technology requires achieving not only full technological readiness but also anticipating, prioritizing, and addressing societal concerns that may arise during the course of development of a technology. Failures to anticipate and address societal factors in the early stages of technology development have led to high-profile delays and, in some cases, ultimate failures of nuclear technology projects. The sociotechnical readiness scale, which conceptually draws on the design research and science and technology studies scholarship, centers on principles of equity and environmental justice in technology design, and emphasizes the need for social engagement during the process of technology development. Nowhere is such an approach to technology development more vital or needed than for the long-term management of spent nuclear fuel.