Miracle-dz/UniFAR-FTUs huggingface dataset:
Target detection method based on supervised saliency map and efficient subwindow search

In order to realize fast target detection under complex image scene, a novel method is proposed based on supervised saliency map and efficient subwindow search. Supervised saliency map generation mainly includes: (1) the original image is segmented by different parameters to obtain multi-segmentation results; (2) regional feature is mapped for salient value by random forest regressor; (3) obtain saliency map by fusing multi-level segmentation results. Efficient subwindow search method is implemented by transforming salient target detection as maximum saliency density, and using branch and bound algorithm to localize the maximum saliency density in global optimum. The experimental results show that the new method can not only detect salient region, but also recognize this region in some extent.
The ecology of the African buffalo in the eastern Kalahari region, South Africa

This study was conducted on Tswalu Kalahari Reserve in the eastern Kalahari region of South Africa. The long-term sustainability of the valued African or Cape buffalo Syncerus caffer caffer was investigated in an area that falls outside their permanent historical distribution. The habitat utilisation of the buffalo population and their range use patterns were investigated. Seasonal differences were apparent in habitat utilisation and were guided by nutritional needs and climatic variables. Range use patterns revealed an increase in range size during the cold, dry season. The buffalo density on Tswalu was the lowest recorded in the literature to date with 0.15 buffalo/km2. The animals showed seasonal changes in their feeding preferences with occasional browsing. During the cold, dry season the population was under severe nutritional stress. Population growth during the study period was 11.8% but this was within the norm expected for a free-living buffalo population. Annual recruitment for the study period was 33%, with half of the female population with calves at heel. However, the population is ageing with 54.2% of the population in the adult age class. Optimising the sex ratio and age structure could improve the productivity. Together with this, the nutritional needs of the buffalo should be met by supplementation, especially during periods of poor rainfall, to assist in optimal production and survival. Population viability analysis showed that the population is vulnerable over the medium term. i University of Pretoria etd – Cromhout, M (2007)
Prospective and Retrospective Metacognitive Abilities and Their Association with Impaired Self-awareness in Patients with Traumatic Brain Injury

Abstract Metacognitive impairment often occurs in patients with traumatic brain injury (TBI) and is associated with clinical problems. The aim of this study was to clarify the pathology of metacognitive impairment in TBI patients using a behavioral task, clinical assessment of self-awareness, and lesion-symptom mapping. Metacognitive abilities of TBI patients and healthy controls were assessed using a modified perceptual decision-making task. Self-awareness was assessed using the Patient Competency Rating Scale and the Frontal Systems Behavior Scale. The associations between estimated metacognitive abilities, self-awareness, and neuropsychological test results were examined. The correspondence between metacognitive disabilities and brain lesions was explored by ROI-based lesion-symptom mapping using structural magnetic resonance images. Overall, 25 TBI patients and 95 healthy controls were included in the analyses. Compared with that in healthy controls, the prospective metacognitive ability of TBI patients was lower, with metacognitive evaluations revealing a bias toward overestimating their abilities. Retrospective metacognitive ability showed a negative correlation with self-awareness but not with neuropsychological test results. In the lesion-symptom mapping analysis, the left pFC was associated with lower retrospective metacognitive ability. This study contributes to a better understanding of the pathology of metacognitive and self-awareness deficits in TBI patients and may explain the cause of impaired realistic goal setting and adaptive behavior in these patients.
Tearing and Breaking Off of Subducted Slabs as the Result of Collision of the Panama Arc‐Indenter with Northwestern South America

We present two regional, lithospheric cross sections that illustrate eastward‐ and southeastward‐dipping, subducted slabs to depths of 315 km beneath the surface of Colombia in northwestern South America. These cross‐sectional interpretations are based on relocated earthquake hypocentral solutions, models supported on gravity and magnetic regional data, and coda‐Q ( Q c ) tomography. The method of tomographic imaging based on spatial inversion of the coda wave has advantages of providing information on the lateral variations of the anelastic properties and thermal structure of the lithospheric system. Mapping of earthquake‐defined Benioff zones combined with tomographic imaging reveals the presence of an ∼240 km long east–west‐striking slab tear, named here the Caldas tear. The proposed Caldas tear separates a zone of shallow, 20°–30°‐dipping, southeastward subduction in the area of Colombia adjacent to Panama and the Caribbean Sea, which is not associated with subduction‐related volcanism, from an area of steeper, 30°–40°‐dipping, slab adjacent to the eastern Pacific Ocean that is associated with an active north–south chain of active arc volcanoes. We propose that the Caldas slab tear separating these two distinct subducted slabs originally formed as the southern boundary of the Panama indenter, an extinct island arc that began subducting beneath northwestern South America about 12 Ma. The area south of the Panama indenter is Miocene oceanic crust of the Nazca plate, which subducts eastward beneath northwestern South America at normal angles and melts to form a north–south‐trending active volcanic arc. In addition to the formation of the Caldas tear, we propose that impedance of the thicker crustal area of the Panama arc‐indenter over the past 12 Ma may have led to down‐dip break‐off of previously subducted oceanic crust that is marked by an extremely concentrated and active earthquake swarm of intermediate‐depth earthquakes beneath east‐central Colombia.
End-to-End Continuous Speech Emotion Recognition in Real-life Customer Service Call Center Conversations

Speech Emotion recognition (SER) in call center conversations has emerged as a valuable tool for assessing the quality of interactions between clients and agents. In contrast to controlled laboratory environments, real-life conversations take place under uncontrolled conditions and are subject to contextual factors that influence the expression of emotions. In this paper, we present our approach to constructing a large-scale real-life dataset (CusEmo) for continuous SER in customer service call center conversations. We adopted the dimensional approach for continuous emotion annotation while incorporating contextual information, such as the metadata of the interlocutors and the context of the call. The study also addresses the challenges encountered during the application of the End-to-End (E2E) SER system to the dataset, including determining the appropriate label sampling rate and input segment length, as well as integrating contextual information (interlocutor’s gender and empathy level) with different weights using multi-task learning. The result shows that incorporating the empathy level information can slightly improve the performance of the E2E SER model.
HI-FISH: WHOLE BRAIN IN SITU MAPPING OF NEURONAL ACTIVATION IN DROSOPHILA DURING SOCIAL BEHAVIORS AND OPTOGENETIC STIMULATION

Monitoring neuronal activity at single-cell resolution in freely moving Drosophila engaged in social behaviors is challenging because of their small size and lack of transparency. Extant methods, such as Flyception, are highly invasive. Whole-brain calcium imaging in head-fixed, walking flies is feasible but the animals cannot perform the consummatory phases of social behaviors like aggression or mating under these conditions. This has left open the fundamental question of whether neurons identified as functionally important for such behaviors using loss-or gain-of-function screens are actually active during the natural performance of such behaviors, and if so during which phase(s). Here we describe a method, called HI-FISH, for brain-wide mapping of active cells expressing the Immediate Early Gene hr38 using a high-sensitivity/low background amplification method called HCR-3.0. Using double-labeling for hr38 mRNA and for GFP, we describe the activity of several classes of aggression-promoting neurons during courtship and aggression, including P1a cells, an intensively studied population of male-specific interneurons. Using HI-FISH in combination with optogenetic activation of aggression-promoting neurons (opto-HI-FISH) we identify candidate downstream functional targets of these cells in a brain-wide, unbiased manner. Finally we compare the activity of P1a neurons during sequential performance of courtship and aggression, using intronic vs. exonic hr38 probes to differentiate newly synthesized nuclear transcripts from cytoplasmic transcripts synthesized at an earlier time. These data provide evidence suggesting that different subsets of P1a neurons may be active during courtship vs. aggression. HI-FISH and associated methods may help to fill an important lacuna in the armamentarium of tools for neural circuit analysis in Drosophila.
Dual ICA to extract interacting sets of genes and conditions from transcriptomic data

One of the challenges in RNA-Seq studies is finding subsets of genes that share a common mechanism of action or are associated with a regulon/pathway. Existing approaches often extract modules that reflect quantitative similarities (such as genes with correlated log-fold-changes) but do not adequately capture biological significance. In this work, we propose the Dual ICA methodology, which provides an agnostic way to extract "interacting modules" composed of sets of genes and conditions that exhibit strong associations. Dual ICA involves performing Independent Component Analysis (ICA) twice, once on the genes and once on the conditions. Using the resulting signal matrices, we extract respective sets of genes and conditions. The interaction between these sets is quantified using the coefficients from a linear regression and significance is determined through the Wald test and Z-score filtering. These coefficients are equivalent to the outer product of independent components obtained from the two signal matrices. Not only do the gene sets extracted align with known regulons, but the significant interacting modules they instantiate also encompass conditions that influence the expression of these regulons through shared mechanisms of action. Compared to traditional unsupervised clustering methods, Dual ICA demonstrates superior performance and provides explicit gene-condition sets for exploring functional relationships.
“I’m the leader and I’m going to save the world”: Characterizing Empowering and Disempowering Game Experiences

Empowering people through technology is a core concern of HCI, yet little is known about how players experience empowerment or disempowerment through videogames. We surveyed 250 participants about their dis-/empowering videogame experiences, investigating why they felt dis-/empowered, and how these experiences related to core player experience constructs including emotion and basic needs satisfaction. While empowering experiences were often positive, and disempowering experiences often negative, we found meaningful exceptions to this, and a surprising complexity in player accounts. We capture this diversity in seven themes. These range from ”heroic victories” which follow long periods of failure, to positive experiences of disempowerment, which were appreciated for their narrative meaning. By articulating these complex experiences, and relating them to quantitative measures we provide a foundation for understanding of the role of dis-/empowerment in player experience, and highlight avenues for future work. Data and analyses are available at https://osf.io/zhtu8/
Prospective Passion and Social Capital within DotA 2 Players

The Dualistic Model of Passion (obsessive and harmonious passion) can explain motivations for videogame play along with associated outcomes, such as the development of social capital; however, existing research exploring passion and social capital in videogaming has been cross-sectional. In the current study we surveyed players of DotA 2 at three time points, over six months (T1 n=462, T2 n=182, T3 n=115), to explore the stability of passion for DotA 2 over time and how such passion may lead to the development or erosion of social capital. Our key findings include that passion for playing DotA 2 is relatively stable over time and that harmonious passion predicts future bridging social capital, while obsessive passion predicts future bonding social capital. Importantly, our findings suggest the absence of a "slippery slope" scenario in which players who have a healthy pattern of engagement development obsessive passion or problematic play. Equally, however, our findings also suggest that those who are obsessive are unlikely to naturally trend towards a more harmonious style of engagement over time. We consider the implications of our findings for health practitioners, players and videogame developers and identify the differences between our longitudinal findings and the existing cross-sectional research.
Scanning electron microscope study of Apollo 15 green glass

Apollo 15 green glass droplets and related forms show a variety of low velocity impact features which occurred at the time of formation of the droplets. Composite forms, which consist of a crystallized core on which mounds of glass adhere, indicate a sequence of core formation and crystallization, followed by impact of molten droplets. The complicated and time dependent texture and morphology of the green glass forms are best explained by formation in a volcanic lava fountain rather than by meteorite impact.
Canonical Representation of Biological Networks Using Graph Convolution

Graph machine learning algorithms are being commonly applied to a broad range of prediction tasks in systems biology. These algorithms present many design choices depending on the specific application and available data, making it difficult to choose from different options. An important design criterion in this regard is the definition of "topological similarity" between two nodes in a network, which is used to design convolution matrices for graph convolution or loss functions to evaluate node embeddings. Many measures of topological similarity exist in network science literature (e.g., random walk based proximity, shared neighborhood) and recent comparative studies show that the choice of topological similarity can have a significant effect on the performance and reliability of graph machine learning models. We propose GraphCan, a framework for computing canonical representations for biological networks using a similarity-based Graph Convolutional Network (GCN). GraphCan integrates multiple node similarity measures to compute canonical node embeddings for a given network. The resulting embeddings can be utilized directly for downstream machine learning tasks. We comprehensively evaluate GraphCan in the context of various link prediction tasks in systems biology. Our results show that GraphCan consistently delivers improved prediction accuracy over algorithms that directly use the adjacency matrix of the input network, and the integration of multiple similarity measurements improves the robustness of the framework. The implementation of GraphCan can be found in https://github.com/Meng-zhen-Li/Similarity-based-GCN.git.
Technology-Enabled Interventions for Sustaining Behaviour Change in Adolescents: A Scoping Review for Research Gaps

Long-term behaviour change for adolescents plays an important role in improving the adolescent's future health. However, long-term behaviour changes are rarely sustained. This study aims to inform human-computer interaction researchers of the current state of research regarding the designing of technology-enabled interventions for sustaining behaviour change for adolescents, as well as provide recommendations for future research directions. Through a scoping review, 22 interventions were identified and analysed to report the behaviour change strategies, characteristics, levels of influence, and formats of technology used, as well as the frameworks used to develop these interventions. Based on the review's findings, three research gaps were identified: (1) the exploration of approaches to restructuring the environment; (2) the exploration of the effects of varying levels of social interactivity between people; and (3) the development of frameworks for building interventions.
Supporting Co-Regulation and Motivation in Learning Programming in Online Classrooms

Self-regulation of learning in programming has been extensively investigated, emphasising an individual's metacognitive and motivational regulation components. However, learning often happens in socially situated contexts, and little emphasis has been paid to studying social modes of regulation in programming. We designed Thyone, a collaborative Jupyter Notebook extension to support learners' programming regulation in an online classroom context with the overall aim to foster their intrinsic motivation toward programming. Thyone's salient features - Flowchart, Discuss and Share Cell - incorporate affordances for learners to co-regulate their learning and drive their motivation. In an exploratory quasi-experimental study, we investigated learners' engagement with Thyone's features and assessed its influence on their learning motivation in an introductory programming course. We found that Thyone facilitated the co-regulation of programming learning and that the users' engagement with Thyone appeared to positively influence components of their motivation: interest, autonomy, and relatedness. Our results inform the design of technological interventions to support co-regulation in programming learning.
Climate change discourses in use by the UK public : commonalities and variations over a fifteen year period

The ways in which climate change is understood by members of the UK public, are considered across a fifteen year period spanning 1997-2011. Qualitative datasets from six separate projects are analysed to trace commonalities and variation over time in the conceptualisation of climate change as a physical, social and personal phenomenon. Ways of understanding are presented as a series of discourses. These relate to people’s appraisal of climate science, the apprehension of climate change through informal evidence, and how climate is seen in relation to natural systems; as well as the means by which climate change is contextualised to social systems, to cultural and historical conditions, and with respect to daily life. Climate discourses across all domains are found to be relatively stable over time, though with subtle shifts in meaning and emphasis. Emergent trends include recent evidence of climate ‘fatigue’ and an increased tendency to question the anthropogenic component to climate change, but also the view that action on climate change has become normalised in recent years. Survey data are also used to explore the prevalence of identified ways of understanding, and to examine longitudinal changes in these. There is some evidence of decline in climate change concern and increase in scepticism over the past decade, though these trends are not pronounced. Cold weather events from 2009/2010 are interpreted by people as evidence of the veracity of climate change (more so than as disconfirming it). Cultural worldviews are found to underlie perceptions. Findings are interpreted in the context of cultural theoretical and discursive frameworks. These present the opportunity to explain the recurrent, patterned and socially-shared nature of public perspectives, and the ways in which these are used both to understand climate change and to account for the actions of oneself and others. The development of combined secondary and longitudinal qualitative analytic techniques is a central methodological concern of the thesis. The advantages and drawbacks, practicalities, and epistemological considerations of such an approach, are outlined in detail.
The Consistency of Gamification User Types: A Study on the Change of Preferences over Time

In recent decades, several studies have suggested and validated user models (e.g., Bartle, and Hexad) to represent different user profiles in games and gamified environments. However, when applying these user models in practice (e.g., to personalize gamification), several studies reported contradictory outcomes. Recently, some studies outlined that one of the possible explanations for these contradictory findings is that people can present changes in their user profiles over time. In this study (N = 118), we present an analysis of the consistency of gamification user orientations after six months of the initial identification, by analyzing the association between user orientations in the first and second data collection. Overall, our results corroborate prior research demonstrating that user orientations can not be considered stable over time and also that the strongest tendency of the users might not be sufficient to determine how users change. Furthermore, we were able to identify that some user orientations can be more stable than others and model some relationships between their profiles after six months. Based on the results, we indicate a research agenda that can further the knowledge about the topic, as well as indicate a set of suggestions on how to model user profiles based on our results.
Evaluating Similarity Variables for Peer Matching in Digital Health Storytelling

Peer matching can enhance the impact of social health technologies. By matching similar peers, online health communities can optimally facilitate social modeling that supports positive health attitudes and moods. However, little work has examined how to operationalize similarities in digital health tools, thus limiting our ability to perform optimal peer matching. To address this gap, we conducted a factorial experiment to examine how three categories of similarity variables (i.e., Demographic, Ability, Experiential) can be used to perform peer matching that supports the social modeling of physical activity. We focus this study on physical activity because it is a health behavior that reduces the risk of chronic diseases. We also prioritized this study for single-caregiver mothers who often face substantial barriers to being active because of immense employment and household responsibilities, especially Black single-caregiver mothers. We recruited 309 single-caregiver mothers (49% Black, 51% white), then we asked them to listen to peer audio storytelling about family physical activity. We randomly matched/mismatched the storyteller's profile using the three categories of similarity variables. Our analyses demonstrated that matching by Demographic variables led to a significantly higher Physical Activity Intention. Furthermore, our subgroup analyses indicated that Black single-caregiver mothers experienced a significant and immediate effect of peer matching in Physical Activity Intention, Self-efficacy, and mood. In contrast, white single-caregiver mothers did not report any significant immediate effect. Collectively, our data suggest that peer matching in health storytelling is potentially beneficial for racially minoritized groups; and that having diverse representations in health technology is required for promoting health equity.