Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Evaluate Semantic Communications for Images with ViTScore Metric?

Semantic communications (SC) have been expected to be a new paradigm shifting to catalyze the next generation communication, whose main concerns shift from accurate bit transmission to effective semantic information exchange in communications. However, the previous and widely-used metrics for images are not applicable to evaluate the image semantic similarity in SC. Classical metrics to measure the similarity between two images usually rely on the pixel level or the structural level, such as the PSNR and the MS-SSIM. Straightforwardly using some tailored metrics based on deep-learning methods in CV community, such as the LPIPS, is infeasible for SC. To tackle this, inspired by BERTScore in NLP community, we propose a novel metric for evaluating image semantic similarity, named Vision Transformer Score (ViTScore). We prove theoretically that ViTScore has 3 important properties, including symmetry, boundedness, and normalization, which make ViTScore convenient and intuitive for image measurement. To evaluate the performance of ViTScore, we compare ViTScore with 3 typical metrics (PSNR, MS-SSIM, and LPIPS) through 5 classes of experiments. Experimental results demonstrate that ViTScore can better evaluate the image semantic similarity than the other 3 typical metrics, which indicates that ViTScore is an effective performance metric when deployed in SC scenarios.
Learning Sequential Acquisition Policies for Robot-Assisted Feeding

A robot providing mealtime assistance must perform specialized maneuvers with various utensils in order to pick up and feed a range of food items. Beyond these dexterous low-level skills, an assistive robot must also plan these strategies in sequence over a long horizon to clear a plate and complete a meal. Previous methods in robot-assisted feeding introduce highly specialized primitives for food handling without a means to compose them together. Meanwhile, existing approaches to long-horizon manipulation lack the flexibility to embed highly specialized primitives into their frameworks. We propose Visual Action Planning OveR Sequences (VAPORS), a framework for long-horizon food acquisition. VAPORS learns a policy for high-level action selection by leveraging learned latent plate dynamics in simulation. To carry out sequential plans in the real world, VAPORS delegates action execution to visually parameterized primitives. We validate our approach on complex real-world acquisition trials involving noodle acquisition and bimanual scooping of jelly beans. Across 38 plates, VAPORS acquires much more efficiently than baselines, generalizes across realistic plate variations such as toppings and sauces, and qualitatively appeals to user feeding preferences in a survey conducted across 49 individuals. Code, datasets, videos, and supplementary materials can be found on our website: https://sites.google. com/view/vaporsbot.
Limits of economy and fidelity for programmable assembly of size-controlled triply-periodic polyhedra

We propose and investigate an extension of the Caspar-Klug symmetry principles for viral capsid assembly to the programmable assembly of size-controlled triply-periodic polyhedra, discrete variants of the Primitive, Diamond, and Gyroid cubic minimal surfaces. Inspired by a recent class of programmable DNA origami colloids, we demonstrate that the economy of design in these crystalline assemblies -- in terms of the growth of the number of distinct particle species required with the increased size-scale (e.g. periodicity) -- is comparable to viral shells. We further test the role of geometric specificity in these assemblies via dynamical assembly simulations, which show that conditions for simultaneously efficient and high-fidelity assembly require an intermediate degree of flexibility of local angles and lengths in programmed assembly. Off-target misassembly occurs via incorporation of a variant of disclination defects, generalized to the case of hyperbolic crystals. The possibility of these topological defects is a direct consequence of the very same symmetry principles that underlie the economical design, exposing a basic tradeoff between design economy and fidelity of programmable, size controlled assembly.
Angle Range and Identity Similarity Enhanced Gaze and Head Redirection based on Synthetic data

Redirecting head pose and gaze direction of the human face is an important synthesis approach for various downstream tasks, particularly appearance-based gaze estimation. In this paper, we propose a method for improving the angular accuracy and photo-reality of gaze and head redirection in full-face images. The problem with current models is that they cannot handle redirection at large angles, and this limitation mainly comes from the lack of training data. To resolve this problem, we create data augmentation by monocular 3D face reconstruction to extend the head pose and gaze range of the real data, which allows the model to handle a wider redirection range. In addition to the main focus on data augmentation, we also propose a framework with better image quality and identity preservation of unseen subjects even training with synthetic data. Experiments show that our method significantly improves redirection performance in terms of redirection angular accuracy while maintaining high image quality, especially when redirecting to large angles.
osmAG: Hierarchical Semantic Topometric Area Graph Maps in the OSM Format for Mobile Robotics

Maps are essential to mobile robotics tasks like localization and planning. We propose the open street map (osm) XML based Area Graph file format to store hierarchical, topometric semantic multi-floor maps of indoor and outdoor environments, since currently no such format is popular within the robotics community. Building on-top of osm we leverage the available open source editing tools and libraries of osm, while adding the needed mobile robotics aspect with building-level obstacle representation yet very compact, topometric data that facilitates planning algorithms. Through the use of common osm keys as well as custom ones we leverage the power of semantic annotation to enable various applications. For example, we support planning based on robot capabilities, to take the locomotion mode and attributes in conjunction with the environment information into account. The provided C++ library is integrated into ROS. We evaluate the performance of osmAG using real data in a global path planning application on a very big osmAG map, demonstrating its convenience and effectiveness for mobile robots.
Learning Spiking Neural Network from Easy to Hard Task

Starting with small and simple concepts, and gradually introducing complex and difficult concepts is the natural process of human learning. Spiking Neural Networks (SNNs) aim to mimic the way humans process information, but current SNNs models treat all samples equally, which does not align with the principles of human learning and overlooks the biological plausibility of SNNs. To address this, we propose a CL-SNN model that introduces Curriculum Learning(CL) into SNNs, making SNNs learn more like humans and providing higher biological interpretability. CL is a training strategy that advocates presenting easier data to models before gradually introducing more challenging data, mimicking the human learning process. We use a confidence-aware loss to measure and process the samples with different difficulty levels. By learning the confidence of different samples, the model reduces the contribution of difficult samples to parameter optimization automatically. We conducted experiments on static image datasets MNIST, Fashion-MNIST, CIFAR10, and neuromorphic datasets N-MNIST, CIFAR10-DVS, DVS-Gesture. The results are promising. To our best knowledge, this is the first proposal to enhance the biologically plausibility of SNNs by introducing CL.
Integrated Robotics Networks with Co-optimization of Drone Placement and Air-Ground Communications

Terrestrial robots, i.e., unmanned ground vehicles (UGVs), and aerial robots, i.e., unmanned aerial vehicles (UAVs), operate in separate spaces. To exploit their complementary features (e.g., fields of views, communication links, computing capabilities), a promising paradigm termed integrated robotics network therefore emerges, which provides communications for cooperative UAVs-UGVs applications. However, how to efficiently deploy UAVs and schedule the UAVs-UGVs connections according to different UGV tasks become challenging. In this paper, we consider the sum-rate maximization problem, where UGVs plan their trajectories autonomously and are dynamically associated with UAVs according to their planned trajectories. Although this problem is a NP-hard mixed integer program, a fast polynomial time algorithm using alternating gradient descent and penalty-based binary relaxation, is devised. Simulation results demonstrate the effectiveness of the proposed algorithm.
A Visual Analytic Environment to Co-locate Peoples' Tweets with City Factual Data

Social Media platforms (e.g., Twitter, Facebook, etc.) are used heavily by public to provide news, opinions, and reactions towards events or topics. Integrating such data with the event or topic factual data could provide a more comprehensive understanding of the underlying event or topic. Targeting this, we present our visual analytics tool, called VC-FaT, that integrates peoples' tweet data regarding crimes in San Francisco city with the city factual crime data. VC-FaT provides a number of interactive visualizations using both data sources for better understanding and exploration of crime activities happened in the city during a period of five years.
TECVis: A Visual Analytics Tool to Compare People's Emotion Feelings

Twitter is one of the popular social media platforms where people share news or reactions towards an event or topic using short text messages called"tweets". Emotion analysis in these tweets can play a vital role in understanding peoples' feelings towards the underlying event or topic. In this work, we present our visual analytics tool, called TECVis, that focuses on providing comparison views of peoples' emotion feelings in tweets towards an event or topic. The comparison is done based on geolocations or timestamps. TECVis provides several interaction and filtering options for navigation and better exploration of underlying tweet data for emotion feelings comparison.
After-Fatigue Condition: A Novel Analysis Based on Surface EMG Signals

This study introduces a novel muscle activation analysis based on surface electromyography (sEMG) signals to assess the muscle’s after-fatigue condition. Previous studies have mainly focused on the before-fatigue and fatigue conditions. However, a comprehensive analysis of the after-fatigue condition has been overlooked. The proposed method analyzes muscle fatigue indicators at various maximal voluntary contraction (MVC) levels to compare the before-fatigue, fatigue, and after-fatigue conditions using amplitude-based, spectral-based, and muscle fiber conduction velocity (CV) parameters. In addition, the contraction time of each MVC level is also analyzed with the same indicators. The results show that in the after-fatigue condition, the muscle activation changes significantly in the ways such as higher CV, power spectral density shifting to the right, and longer contraction time until exhaustion compared to the before-fatigue and fatigue conditions. The results can provide a comprehensive and objective evaluation of muscle fatigue and recovery, which can be helpful in clinical diagnosis, rehabilitation, and sports performance.
Inverse problem for fractional order subdiffusion equation

The study examines the inverse problem of finding the appropriate right-hand side for the subdiffusion equation with the Caputo fractional derivative in a Hilbert space represented by $H$. The right-hand side of the equation has the form $g(t)f$ and an element $f\in H$ is unknown. If the sign of $g(t)$ is a constant, then the existence and uniqueness of the solution is proved. When $g(t)$ changes sign, then in some cases, the existence and uniqueness of the solution is proved, in other cases, we found the necessary and sufficient condition for a solution to exist. Obviously, we need an extra condition to solve this inverse problem. We take the additional condition in the form $\int\limits_0^Tu(t)dt=\psi$. Here $\psi $ is a given element, of $H$.
PhysioZoo: The Open Digital Physiological Biomarkers Resource

PhysioZoo is a collaborative platform designed for the analysis of continuous physiological time series. The platform currently comprises four modules, each consisting of a library, a user interface, and a set of tutorials: (1) PhysioZoo HRV, dedicated to studying heart rate variability (HRV) in humans and other mammals; (2) PhysioZoo SPO2, which focuses on the analysis of digital oximetry biomarkers (OBM) using continuous oximetry (SPO2) measurements from humans; (3) PhysioZoo ECG, dedicated to the analysis of electrocardiogram (ECG) time series; (4) PhysioZoo PPG, designed to study photoplethys-mography (PPG) time series. In this proceeding, we introduce the PhysioZoo platform as an open resource for digital physiological biomarkers engineering, facilitating streamlined analysis and data visualization of physiological time series while ensuring the reproducibility of published experiments. We welcome researchers to contribute new libraries for the analysis of various physiological time series, such as electroencephalography, blood pressure, and phonocardiography. You can access the resource at physiozoo.com. We encourage researchers to explore and utilize this platform to advance their studies in the field of continuous physiological time-series analysis.
Tourism Promotion and Power: Creating Images, Creating Identities

INTO THE TOURISM IMAGE. Reading the Image. Creating and Consuming the Image. Culture and the Image. THE IMAGE AND CHANGING MARKETS. Fragmenting Identities, Fragmenting Power. Power, Image and Markets. Branding, Identity and Power. CHANGING WORLDS, CHANGING IMAGES? The Image, Politics and Power. The Gendered and Sexualised Image. Images of "Them" and "Us". Changing Ways of Seeing the Image. Bibliography. Index.
Links between early-life contextual factors and later-life cognition and the role of educational attainment

Abstract Objective: Educational attainment is a well-documented predictor of later-life cognition, but less is known about upstream contextual factors. This study aimed to identify which early-life contextual factors uniquely predict later-life global cognition and whether educational attainment mediates these relationships. Method: Participants were drawn from the Michigan Cognitive Aging Project (N = 485; M age = 63.51; SD age = 3.13; 50% non-Hispanic Black). Early-life exposures included U.S. region of elementary school (Midwest, South, Northeast), average parental education, household composition (number of adults (1, 2, 3+), number of children), school racial demographics (predominantly White, predominantly Black, diverse), self-reported educational quality, and school type (public/private). Later-life global cognition was operationalized with a factor score derived from a comprehensive neuropsychological battery. Sequential mediation models controlling for sociodemographics estimated total, direct, and indirect effects of early-life contextual factors on cognition through educational attainment (years). Results: Higher educational quality, higher parental education, and attending a private school were each associated with better cognition; attending a predominantly Black or diverse school and reporting three or more adults in the household were associated with lower cognition. After accounting for educational attainment, associations remained for educational quality, school type, and reporting three or more adults in the household. Indirect effects through educational attainment were observed for school region, educational quality, school racial demographics, and parental education. Conclusions: School factors appear to consistently predict later-life cognition more than household factors, highlighting the potential long-term benefits of school-level interventions for cognitive aging. Future research should consider additional mediators beyond educational attainment such as neighborhood resources and childhood adversity.
Sampling templates guided compression reconstruction network

For reconstruction in spatial compressive imaging, we use a module to fuse and extract the information in sampling templates, this obtained feature vector becomes the attention weight, which is multiplied with the feature maps of the compressed measurement frames. In addition, unlike previous networks using segmented images, we use full measurement frames collected as our network input. Thus the local information of objects can be preserved and blocky effect can be avoid. We have tested the network performance on the datasets, Set5, Set14, BSD100, Urban100, Manga109, with 25% compression rate, respectively. We obtain the PSNR\SIM values in the range, [26.5dB, 31.9dB]\[0.82, 0.90]. This result is better than [23.6dB, 29.0dB]\[0.72, 0.85] obtained using the best algorithms in the same application based on our knowledge.
Food security and food production systems

to climate but such impacts are much less well known. Climate-related disasters are among the main drivers of food insecurity, both in the aftermath of a disaster and in the long run. Drought is a major driver of food insecurity, and contributes to a negative impact on nutrition. Floods and tropical storms also affect food security by destroying livelihood assets. The relationship between climate change and food production depends to a large degree on when and which adaptation actions are taken. Other links in the food chain from production to consumption are sensitive to climate but such impacts are much less well known. flats (Pratchett et al., 2011). Extreme events such as increased severity of tropical cyclones could also impact on some species. Under both B1 and A2 emissions scenarios, the vulnerability of coastal fisheries as a whole in 2035, as estimated through the framework described in Bell et al. (2009), is considered to be low. Extended to 2100, the projected impacts under the A2 emissions scenario are more severe, with reductions in coastal fisheries production by 20 to 35% in the west and 10 to 30% in the east (Pratchett et al., 2011).
Protocol for a qualitative study exploring the pharmacist’s role in supporting postsecondary students with psychotropic medication management

Introduction Findings from the National College Health Assessment (2019) stated that anxiety and depression are the most prevalent diagnosed mental illnesses among Canadian postsecondary students with one-fifth of students self-reporting a lifetime diagnosis. Psychotropic medications can be an important component of a multifaceted approach to the management and treatment of mental illness and are the most commonly dispensed via community pharmacies. Community pharmacies provide an opportunity for pharmacists to have a prominent role in supporting patients’ psychotropic medication management. However, there has been limited exploration of how pharmacists can address patients’ psychotropic medication management needs, experiences and opportunities for improvements especially for emerging adults. Methods and analysis This qualitative study will incorporate Thorne’s approach to interpretative description. Purposeful snowball sampling will be used to identify students (18–25 years) taking psychotropic medication(s) to manage their mental health. Participants will be interviewed one on one using a semistructured interview guide virtually. Inductive thematic analysis is underway with data analysis being iterative and reflexive using NVivo. Information provided from the interviews will be reviewed and summarised into key themes. Ethics and dissemination This study was approved by the University of Toronto Health Sciences Research Ethics Board (REB #43185). It is expected that there will be a very low risk for mild psychological and social harm for participants as they will have the ability to stop the interview at any time and will be aware of confidentiality. The results from this study will be used to create or adapt healthcare team services including the role of pharmacists within the healthcare ecosystem at the university and contribute to developing the next stage of research to evaluate feasibility and effectiveness of programmes at the university that help postsecondary students to manage psychotropic medication.
Time-worn pebbles or unpolished gemstones? (Un)usable pasts and possible futures of comparative education

ABSTRACT This article draws on the contributions to this special issue to highlight the urgent need to restore checks and balances in our evaluation of ‘usable pasts’ in comparative education. Considering that our reading of the field’s history not only moulds our understanding of comparative education now but also shapes our imagination of its potential futures, reflecting our implicit biases and the way we construct and narrate its history becomes imperative. This article unveils the persistence of silences and exclusions concerning specific histories, countries, and topics, and highlights the possible influence of evolving geopolitical power dynamics on the future of comparative education. Consequently, it urges critical examination of the field’s positionality amid shifting geopolitical tensions and calls for a thorough scrutiny of entrenched silences and the reductionist use of sweeping policy signifiers such as globalisation, decolonisation, excellence, and the notion of ‘future’ as explanatory concepts.