Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Dimensions of Landscape Ecology : Wildlife Responses to Variable Resources

Introduction. - Part 1: Relevant Temporal Theory: Resource Acquisition and Animal Response in Dynamic Landscapes: Keeping the Books. - Pulsed Resources and Community Responses: An Exploration of Factors Influencing Outcomes. - Invoking the Ghosts of Landscapes Past to Understand the Landscape Ecology of the Present.and the Future. - Modeling Adaptive Behavior in Event-Driven Environments: Temporally Explicit Individual-Based Ecology. - Temporal Scaling in Complex Systems: Resonant Frequencies and Biotic Variability. - Part 2: Statistics of Time: Using Statistical Models to Study Temporal Dynamics of Animal-Landscape Relations. - Multivariate Landscape Trajectory Analysis: An Example Using Simulation Modeling of American Marten Habitat Change Under Four Timber Harvest Scenarios. - Part 3: Temporally Focused Case Studies: Assessing Grouse Habitats in the Alps: the Complication of Small-Scale Spatio-Temporal Variation in Rainfall Patterns. - Exploring the Temporal Effects of Seasonal Water Availability on the Snail Kite of Florida. - Three Axes of Ecological Studies: Matching Process and Time in Landscape Ecology. - Building and Using Habitat Models For Assessing Temporal Changes in Forest Ecosystems. - Foraging Responses of the Endangered Gouldian Finch to Temporal Differences in Seed Availability in Northern Australian Savanna Grasslands. - Spending Time in the Forest: Responses of Cavity Nesters to Temporal Changes in Forest Health in Interior British Columbia. - Niche Opportunities and Introduced Birds: Temporal Variation in Resource Abundance. - About the Contributors. - Index.
How are beliefs represented in the mind?

Abstract The commentators of our target article present several detailed arguments to refute the opposing theory. The real issue, however, seems to be the fundamental question of how the mind represents the content of beliefs. We distinguish between qualitative, quantitative and comparative approaches to modeling uncertain beliefs. We describe which theory falls into which of these classes. We also argue that the comparative level is the most fundamental, and challenge commentators to justify why they think that beliefs have more or less structure in the human mind than can be captured at the comparative level.
Hydrogeomorphic approach to assessing wetland functions: guidelines for developing regional guidebooks - chapter 3: developing a reference wetland system

Abstract : In the Hydrogeomorphic (HGM) Approach, reference wetlands are the group of wetlands selected from a specific geographic area to represent the entire range of variability exhibited by a regional wetland class. Reference standard wetlands are the subset of reference wetlands used to establish the standard or comparison for calibrating assessment model variables and functional indices under the HGM Approach. This chapter provides guidelines for selecting a set of reference wetlands to represent a regional wetland subclass. It begins with the definition of terms, and continues with discussions on the purpose of reference wetlands, selection strategies, number of reference wetland sites, designation of reference wetland standard sites, and use of historical information in reconstructing reference standard wetlands.
The roles of temporal envelope and fine structure information in auditory perception

Within the cochlea, broadband sounds like speech and music are filtered into a series of narrowband signals, each with a relatively slowly varying envelope (ENV) imposed on a rapidly oscillating carrier (the temporal fine structure, TFS). Information about ENV and TFS is conveyed in the timing and short-term rate of action potentials in the auditory nerve. This paper describes the role of ENV and TFS information in pitch perception, binaural processing, and the perception of speech in the presence of background sounds. The paper also describes the effects of hearing loss and age on the processing of TFS and ENV information. The monaural and binaural processing of TFS information is adversely affected by both hearing loss and increasing age. The monaural processing of ENV information is little affected by hearing loss or by increasing age. The binaural processing of ENV information deteriorates somewhat with increasing age but is not markedly affected by hearing loss. The reduced TFS processing abilities found for older/hearing-impaired subjects may partially account for the difficulties that such subjects experience in complex listening situations.
Sex differences in seizure presentation in Dravet syndrome model mice, Scn1a+/-

Dravet syndrome (DS) is an epileptic encephalopathy mostly due to haploinsufficiency of the SCN1A voltagegated sodium channel subunit. Disease presentation (i.e., severe seizures and early life mortality) is highly recapitulated in mice haploinsufficient in Scn1a (Scn1a+/-). However, phenotypic characterization in Scn1a+/- mice in a sex and temporal manner is limited. Given the reliance of mouse models for studying disease pathophysiology and for the development of novel treatments, we tested whether mortality and seizure morbidity differed among young and adult male and female Scn1a+/- animals in the F1 hybrid C57×129S6 background. We found increased mortality in female Scn1a+/- mice regardless of age compared to their male counterparts (n = 120-125 mice/sex; p < 0.05). Interestingly, long-term video EEG recordings revealed the opposite for morbidity as seizure frequency and severity were escalated in adult male Scn1a+/- animals (n = 21-30 mice/sex; p < 0.05 or p < 0.01). Adult female Scn1a+/- mice, however, are more hyperactive (p < 0.05), which could be related to sleep impairment and contribute to the increased mortality despite decreased seizure morbidity. Overall, the phenotypic presentation of Scn1a+/- mice is sex-dependent and may have translational implications for therapeutic drug discovery and basic biology understanding in DS. Short Summary Sex differences in mortality and seizure morbidity are discovered in Scn1a haploinsufficient mice, Scn1a+/-, which faithfully model the epileptic encephalopathy disorder, Dravet syndrome (DS). Female Scn1a+/- mice die more across all ages, whereas adult male Scn1a+/- mice have more seizures that are of greater severity. Hyperactivity, as a proxy for sleep disruption, may contribute to the increased mortality in female Scn1a+/- mice despite decreased seizure incidence and severity. These sex-specific findings may have considerable impact in therapeutic discovery and development for DS and other SCN1A-related disorders.
The resolution of face perception varies systematically across the visual field

Visual abilities tend to vary predictably across the visual field – for simple low-level stimuli, visibility is better along the horizontal vs. vertical meridian and in the lower vs. upper visual field. In contrast, face perception abilities have been reported to show either distinct or entirely idiosyncratic patterns of variation in peripheral vision, suggesting a dissociation between the spatial properties of low- and higher-level vision. To assess this link more clearly, we extended methods used in low-level vision to develop an acuity test for face perception, measuring the smallest size at which facial gender can be reliably judged in peripheral vision. In 3 experiments, we show the characteristic inversion effect, with better acuity for upright faces than inverted, demonstrating the engagement of high-level face-selective processes in peripheral vision. We also observe a clear advantage for gender acuity on the horizontal vs. vertical meridian and a smaller-but-consistent lower- vs. upper-field advantage. These visual field variations match those of low-level vision, indicating that higher-level face processing abilities either inherit or actively maintain the characteristic patterns of spatial selectivity found in early vision. The commonality of these spatial variations throughout the visual hierarchy means that the location of faces in our visual field systematically influences our perception of them.
Abstraction of reward context facilitates relative reward coding in neural populations of the anterior cingulate cortex

The anterior cingulate cortex (ACC) is believed to be involved in many cognitive processes, including linking goals to actions and tracking decision-relevant contextual information. ACC neurons robustly encode expected outcomes, but how this relates to putative functions of ACC remains unknown. Here, we approach this question from the perspective of population codes by analyzing neural spiking data in the ventral and dorsal banks of the ACC in monkeys trained to perform a stimulus-motor mapping task. We found that neural populations favor a representational geometry that emphasizes contextual information, while facilitating the independent, abstract representation of multiple task-relevant variables. In addition, trial outcomes were primarily encoded relative to task context, suggesting that the population structures we observe could be a mechanism allowing feedback to be interpreted in a context-dependent manner. Together, our results point to a prominent role for ACC in context-setting and relative interpretation of outcomes, facilitated by abstract, or “untangled,” representations of task variables. Author Summary The ability to interpret events in light of the current context is a critical facet of higher-order cognition. The anterior cingulate cortex is suggested to be important for tracking information about current contexts, while alternate views hold that its function is more related to the motor system and linking goals to appropriate motor responses. Here, we evaluated these two possibilities by recording anterior cingulate neurons from monkeys performing a stimulus-motor mapping task in which compound cues both defined the current reward context and instructed appropriate motor responses. By analyzing geometric properties of neural population activity, we found that the ACC prioritized context information, representing it as a dominant, abstract concept. Ensuing trial outcomes were then coded relative to these contexts, suggesting an important role for these representations in context-dependent evaluation. Such mechanisms may be critical for the abstract reasoning and generalization characteristic of biological intelligence.
PixelAsParam: A Gradient View on Diffusion Sampling with Guidance

Diffusion models recently achieved state-of-the-art in image generation. They mainly utilize the denoising framework, which leverages the Langevin dynamics process for image sampling. Recently, the guidance method has modified this process to add conditional information to achieve a controllable generator. However, the current guidance on denoising processes suffers from the trade-off between diversity, image quality, and conditional information. In this work, we propose to view this guidance sampling process from a gradient view, where image pixels are treated as parameters being optimized, and each mathematical term in the sampling process represents one update direction. This perspective reveals more insights into the conflict problems between updated directions on the pixels, which cause the trade-off as previously mentioned. We then investigate the conflict problems and propose to solve them by a simple projection method. The experimental results evidently improve over different baselines on datasets with various resolutions.
The Entity-Relationship Model: Towards a unified view of Data

An improved method of operation is provided for a catalytic, low pressure process for continuously reforming a hydrocarbon charge stock boiling in the gasoline range in order to produce a high octane effluent stream in which process the hydrocarbon charge stock and hydrogen are continuously contacted in a reforming zone with a reforming catalyst containing a catalytically effective amount of a platinum group metal at reforming conditions including a pressure of 25 to 250 psig. The improved method of operation involves continuously adding a refractory light hydrocarbon to the reforming zone in an amount sufficient to result in a mole ratio of refractory light hydrocarbon to hydrogen entering the reforming zone of about 0.4:1 to about 10:1. Moreover, the refractory light hydrocarbon addition is commenced at start-up of the process and continued throughout the duration of the reforming run. The principal advantage associated with this improved method of operation is increased stability of the reforming catalyst and particularly, increased temperature stability at octane.
Early Deprivation Impairs Perforant Pathway Connectivity and Contextual Memory in Adolescent Male Mice

Early-life adversity causes reduced hippocampal volume and abnormal hippocampal connectivity and function, with evidence indicating more prominent deficits in males compared to females. Reelin-positive projections from the lateral entorhinal cortex (LEC) to the dorsal hippocampus are essential for encoding contextual and semantic memories in diverse mammalian species, including humans and rodents. However, the impact of early-life adversity on these projections and their contribution to hippocampal-dependent deficits have not been reported. Using a modified limited bedding (LB) mouse model of early adversity that extends the impoverished conditions from birth to postnatal day 25 (P25), we found severe impairment in contextual fear conditioning for adolescent LB male but not LB female mice. Using retrograde tracing, we found that the number of reeling-positive projections from the LEC to the dorsal hippocampus is significantly reduced in LB males but not LB females. Further, the number of projections was highly correlated with deficits in contextual memory and hypomyelination in perforant pathway terminals located in the dorsal hippocampus. Ex vivo high-resolution diffusion magnetic resonance imaging confirmed reduced structural connectivity between the entorhinal cortex and the dorsal hippocampus and revealed extensive cortical atrophy that resembled abnormalities reported in children exposed to severe deprivation. Given the essential role that reelin-positive projections play in contextual memory, these findings suggest a novel mechanism to explain the pronounced contextual memory deficits seen in LB males.
Innate sleep apnoea in spontaneously hypertensive rats is associated with microvascular rarefaction and neuronal loss in the preBötzinger Complex

Sleep apnoea is a major threat to physical health and carries a significant economic burden. These impacts are worsened by its interaction with, and induction of, its comorbidities. Sleep apnoea holds a bidirectional relationship with hypertension which drives atherosclerosis, ultimately culminating in vascular dementia. To enable a better understanding of this sequalae of events, we investigated innate sleep apnoea in spontaneously hypertensive rats (SHRs), which have a range of cardiovascular disorders. SHRs displayed a higher degree of sleep disordered breathing, which emanates from poor vascular health leading to a loss of preBötC neurons. This model also displays small vessel white matter disease, a form of vascular dementia, likely associated with neuroinflammation in the hippocampus and the related deficits in both long- and short-term memory. Therefore, hypertension induces sleep apnoea through vascular damage in the respiratory column, culminating in neuronal loss in the inspiratory oscillator. This induction of sleep apnoea which in turn will independently exacerbate hypertension and neural inflammation, increasing the rate of vascular dementia.
Modulation of recovery from neonatal hyperoxic lung injury by sex as a biological variable

Recovery from lung injury during the neonatal period requires the orchestration of many biological pathways. The modulation of such pathways can drive the developing lung towards proper repair or persistent maldevelopment that can lead to a disease phenotype. Sex as a biological variable can regulate these pathways differently in the male and female lung exposed to neonatal hyperoxia. In this study, we assessed the contribution of cellular diversity in the male and female neonatal lung following injury. Our objective was to investigate sex and cell-type specific transcriptional changes that drive repair or persistent injury in the neonatal lung and delineate the alterations in the immune-endothelial cell communication networks using single cell RNA sequencing (sc-RNAseq) in a murine model of hyperoxic injury. We generated transcriptional profiles of >55,000 cells isolated from the lungs of postnatal day 1 (PND 1) and postnatal day 21 (PND 21) neonatal male and female C57BL/6 mice exposed to 95% FiO2 between PND 1-5 (saccular stage of lung development). We show the presence of sex-based differences in the transcriptional states of lung endothelial and immune cells at PND 1 and PND 21. Furthermore, we demonstrate that biological sex significantly influences the response to injury, with a greater number of differentially expressed genes showing sex-specific patterns than those shared between male and female lungs. Pseudotime trajectory analysis highlighted genes needed for lung development that were altered by hyperoxia. Finally, we show intercellular communication between endothelial and immune cells at saccular and alveolar stages of lung development with sex-based biases in the crosstalk and identify novel ligand-receptor pairs. Our findings provide valuable insights into the cell diversity, transcriptional state, developmental trajectory, and cell-cell communication underlying neonatal lung injury, with implications for understanding lung development and possible therapeutic interventions while highlighting the crucial role of sex as a biological variable.
Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks

Spiking neural networks (SNNs) provide an alternative solution to conventional artificial neural networks with energy-saving and high-efficiency characteristics after hardware implantation. However, due to its non-differentiable activation function and the temporally delayed accumulation in outputs, the direct training of SNNs is extraordinarily tough even adopting a surrogate gradient to mimic the backpropagation. For SNN training, this non-differentiability causes the intrinsic gradient error that would be magnified through layerwise backpropagation, especially through multiple layers. In this paper, we propose a novel approach to reducing gradient error from a new perspective called surrogate module learning (SML). Surrogate module learning tries to construct a shortcut path to back-propagate a more accurate gradient to a certain SNN part utilizing the surrogate modules. Then, we develop a new loss function for concurrently training the network and enhancing the surrogate modules’ surrogate capacity. We demonstrate that when the outputs of surrogate modules are close to the SNN output, the fraction of the gradient error drops significantly. Our method consistently and significantly enhances the performance of SNNs on all experiment datasets, including CIFAR-10/100, ImageNet, and ES-ImageNet. For example, for spiking ResNet-34 architecture on ImageNet, we increased the SNN accuracy by 3.46%. Codes are available at https://github. com/brain-intelligence-lab/ surrogate_module_learning .
Cross-functional Analysis of Generalization in Behavioral Learning

Abstract In behavioral testing, system functionalities underrepresented in the standard evaluation setting (with a held-out test set) are validated through controlled input-output pairs. Optimizing performance on the behavioral tests during training (behavioral learning) would improve coverage of phenomena not sufficiently represented in the i.i. d. data and could lead to seemingly more robust models. However, there is the risk that the model narrowly captures spurious correlations from the behavioral test suite, leading to overestimation and misrepresentation of model performance—one of the original pitfalls of traditional evaluation. In this work, we introduce BeLUGA, an analysis method for evaluating behavioral learning considering generalization across dimensions of different granularity levels. We optimize behavior-specific loss functions and evaluate models on several partitions of the behavioral test suite controlled to leave out specific phenomena. An aggregate score measures generalization to unseen functionalities (or overfitting). We use BeLUGA to examine three representative NLP tasks (sentiment analysis, paraphrase identification, and reading comprehension) and compare the impact of a diverse set of regularization and domain generalization methods on generalization performance.1
Increasing Hispanics in the Educator Workforce: A Science Methods Intervention to Improve Passing Rates on an EC-6 Science Certification Examination

ABSTRACT Although increasing numbers of teachers of color are entering the teacher pipeline, they continue to be in high demand, but short supply. Research shows teachers of color have lower pass rates on certification exams, a single factor that functions as a gatekeeper to teacher licensure. This study explores the impact of a science methods intervention on Hispanic elementary teacher certification scores. Results show the mean score for the post-intervention (241.63) was 17 points higher than the pre-intervention score (224.63) and the results were statistically significant (t = −5.816, df = 18, p = .000). In this study, not only did the Science certification scores improve, the scores for Hispanic and White EPSTs were not statistically significantly different (t = .394, df = 50, p = .695).
The Saddle-Point Method in Differential Privacy

We characterize the differential privacy guarantees of privacy mechanisms in the large-composition regime, i.e., when a privacy mechanism is sequentially applied a large number of times to sensitive data. Via exponentially tilting the privacy loss random variable, we derive a new formula for the privacy curve expressing it as a contour integral over an integration path that runs parallel to the imaginary axis with a free real-axis intercept. Then, using the method of steepest descent from mathematical physics, we demonstrate that the choice of saddle-point as the real-axis intercept yields closed-form accurate approximations of the desired contour integral. This procedure—dubbed the saddle-point accountant (SPA)—yields a constant-time accurate approximation of the privacy curve. Theoretically, our results can be viewed as a refinement of both Gaussian Differential Privacy and the moments accountant method found in R ´ enyi Differential Privacy. In practice, we demonstrate through numerical experiments that the SPA provides a precise approximation of privacy guarantees competitive with purely numerical-based methods (such as FFT-based accountants), while enjoying closed-form mathematical expressions.
Learning to Initiate and Reason in Event-Driven Cascading Processes

Reasoning and interacting with dynamic environments is a fundamental problem in AI, but it becomes extremely challenging when actions can trigger cascades of cross-dependent events. We introduce a new supervised learning setup called {\em Cascade} where an agent is shown a video of a physically simulated dynamic scene, and is asked to intervene and trigger a cascade of events, such that the system reaches a"counterfactual"goal. For instance, the agent may be asked to"Make the blue ball hit the red one, by pushing the green ball". The agent intervention is drawn from a continuous space, and cascades of events makes the dynamics highly non-linear. We combine semantic tree search with an event-driven forward model and devise an algorithm that learns to search in semantic trees in continuous spaces. We demonstrate that our approach learns to effectively follow instructions to intervene in previously unseen complex scenes. It can also reason about alternative outcomes, when provided an observed cascade of events.