Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct correlation of noise and flow of a jet using Laser Doppler

Ribner's self and shear noise theory has successfully described many features of jet noise. However, earlier attempts to cross-correlate postulated source terms and jet noise have been only partially successful owing to hot wire-flow interaction. Thus a nonintrusive laser Doppler velocimeter (LDV) has replaced the hot wire. Source strength distributions and far-field self and shear noise spectra are inferred from jet flow (measured with LDV) correlations with jet noise for a model air jet operating at Mach 0.3. Source distributions over slices of jet are unexpectedly somewhat pearshaped. Spectra computed from LDV-jet noise correlations are compatible with corresponding spectra extracted from farfield intensities and with theory. HE generation of noise by turbulent flow is described by a variety of theories. The governing equations differ primarily in the interpretation of certain terms as either source or propagation mechanisms. Measurable properties of the sound field are predicted by summation over all sources, typically a volume integral. These sources are described by an approximate model of the underlying process. Integration over the source region is a smoothing operation; thus pre- dictions tend to be somewhat insensitive to variations of parameters of the assumed model. It is therefore desirable to eliminate the empiricism of source modeling and to demonstrate a one-to-one correspondence between the postulated source mechanism and the radiated sound. Such relationships are readily measured in terms of cross-correla tions in the time domain and cross-spectral densities in the frequency domain. These functions are indicators of the measure of coherence between two signals. Statistically independent functions possess no coherence; input and output of a linear system, on the other hand, are well correlated. The source terms measured herein may be thought of as inputs and the jet noise as the output. The existence of coherence is not sufficient proof of a definite causal relationship between the assumed source terms and the radiated sound. Both may be the result of an unidentified forcing function. One must also demonstrate that the measured cross-correlations are consistent with the postulated source mechanism. Consider a collection of independent radiators as a rather heuristic model of jet nosie. The cross-correlation (cross- spectrum) of a single source and the far-field pressure is a measure of the contribution to the far-field pressure autocorrelation (power spectrum). The latter can be con- structed by adding the contributions of all sources. Closure occurs only if the source model is a valid description of the physical process. Jet noise diagnostics combine the measurement of cross- correlations between the postulated source terms and the
CANINE DISTEMPER VIRUS ECOLOGY: INSIGHTS FROM A LONGITUDINAL SEROLOGIC STUDY IN WILD RACCOONS (PROCYON LOTOR)

Abstract: Increasing reports of canine distemper virus (CDV) in a variety of hosts, and changing CDV dynamics, have led to renewed interest in the ecology of CDV infections in wildlife. Longitudinal serologic studies provide insights into intrapopulation and intraindividual pathogen dynamics, but few studies in wildlife have been conducted. We used data from 235 raccoons (Procyon lotor) captured on more than one occasion between May 2011 and November 2013 to investigate CDV dynamics in Ontario, Canada. Using mixed multivariable logistic regression, we found that juvenile raccoons were more likely to be seronegative from August to November than from May to July. Using paired titers from CDV-exposed individual raccoons, we determined that the winter breeding season, when there is high intraspecific contact and an increase in susceptible juveniles, may be a period of high risk for CDV exposure. Interestingly, CDV seropositive adult raccoons had nondetectable titers ranging from 1 mo to 1 yr later. Based on our preliminary investigation using two different statistical approaches, CDV exposure was associated with a decrease in parvovirus titer. This result raises important questions about whether virus-induced immune amnesia occurs after CDV exposure, which has been described for measles virus, a closely related pathogen. Overall, our results provide significant insights into CDV dynamics. Further research is needed to investigate whether CDV-induced immune amnesia occurs in raccoons and to determine the potential impacts of a reduced population immunity that may occur secondary to CDV exposure, particularly as it relates to rabies control efforts.
GROUND MOTION INTENSITY MEASURES FOR COLLAPSE CAPACITY PREDICTION: CHOICE OF OPTIMAL SPECTRAL PERIOD AND EFFECT OF SPECTRAL SHAPE

Previous research has shown that for extreme ground motions in California, the spectral shape is much different than that of a uniform hazard spectrum or a code design spectrum; and that differences in spectral shape significantly impact results of nonlinear dynamic analyses. This paper builds on this previous research and looks more closely at the question of selecting and scaling ground motions for nonlinear dynamic collapse analyses. Based on dynamic collapse simulation of single-degree-of-freedom models subjected to 70 ground motions, this work confirms the significant effects that spectral shape has on collapse capacity estimates. However, for collapse analyses, we find that the use of a more appropriate ground motion intensity measure can reduce how sensitive the collapse capacity estimates are to the spectral shape of the ground motions. A common ground motion intensity measure is the spectral acceleration at the building first mode period. However, when first-mode dominated ductile structures behave nonlinearly and are near collapse, the “effective period” of the structure may be much larger than the fundamental period. For these types of structures, this paper shows that the spectral acceleration at a period larger than the fundamental period is a more appropriate intensity measure for use in collapse simulation. This paper proposes an equation that predicts this optimal period as a function of the building properties: fundamental period, ductility, and the negative stiffness after reaching the ductility capacity. For ductile structures, this optimal extended period is approximately twice the fundamental period of the building.
Canine Parvovirus 2 in Free-Living Wild Mammals from Southern Brazil

Abstract: Pathogens from domestic canines represent a significant and constant threat to wildlife. This study looked for four common canine pathogens, Babesia vogeli, Ehrlichia canis, Leishmania infantum, and canine parvovirus 2 (CPV-2) in mammals from the Pampa Biome, southern Brazil. Animals killed by vehicular trauma on a road traversing this biome were evaluated over a 1-yr period. Tissues collected from 31 wild mammals and six dogs were further analyzed by specific real-time PCR assays for each pathogen. Babesia vogeli and L. infantum were not detected in any investigated animal. Ehrlichia canis was detected in one dog and CPV-2 in nine animals: four dogs, three white-eared opossums (Didelphis albiventris), one pampas fox (Lycalopex gymnocercus), and one brown rat (Rattus norvegicus). These results demonstrate the occurrence of important carnivore pathogens (E. canis and CPV-2) in domestic dogs and wild mammals from the Pampa Biome in southern Brazil.
Conditional Discriminations and Derived Relations: Pinpointing the Moment of Emergence

Four subjects were exposed to the four trial types that define stimulus equivalence from the beginning of the experiment. Procedures were designed to identify acquisition dynamics and relate these observations to responding indicative of equivalence class formation. The data show that, for all subjects, the acquisition of training conditional discriminations was correlated with systematic changes in the subjects' selection responses. The results also indicate that the traditional percent correct measures obscure some important information about the subjects' behavior. The data are discussed in the context of the following statements. 1) Subjects' performances on derived trials are not indicative of relations among stimuli at some other level of analysis but are instances of "equivalencing". 2) "Equivalencing" itself can be characterized as changes in the conditional and conditionally discriminative functions of stimuli involved in the experiment. The potential benefits of this preparation are discussed.
Sweroside alleviates hepatic steatosis in part by activating AMPK/mTOR‐mediated autophagy in mice

In this study, we investigated the effect of sweroside (SOS) on hepatic steatosis in mice and elucidated its molecular mechanisms. We conducted in vivo experiments using a C57BL/6 mice model of nonalcohol fatty liver disease (NAFLD) to explore the effect of SOS on hepatic steatosis in NAFLD mice. In in vitro experiments, primary mouse hepatocytes were treated with palmitic acid and SOS, and the protective effects of SOS on inflammation, lipogenesis, and fat deposition were analyzed. Autophagy‐related protein levels and their related signaling pathways were evaluated in both in vivo and in vitro experiments. The results demonstrated that SOS decreased the high‐fat‐induced intrahepatic lipid content both in vivo and in vitro. The autophagy level in the liver was decreased in NAFLD mice but was reactivated following SOS intervention. SOS intervention was found to partially activate autophagy via the adenosine monophosphate‐activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) signaling pathway. Consequently, when the AMPK/mTOR pathway was suppressed or autophagy was inhibited, the beneficial effects of SOS intervention on hepatic steatosis were diminished. These results indicate that SOS intervention attenuates hepatic steatosis by promoting autophagy in the liver of NAFLD mice, in part by activating the AMPK/mTOR signaling pathway.
Emotion prediction as computation over a generative theory of mind

From sparse descriptions of events, observers can make systematic and nuanced predictions of what emotions the people involved will experience. We propose a formal model of emotion prediction in the context of a public high-stakes social dilemma. This model uses inverse planning to infer a person’s beliefs and preferences, including social preferences for equity and for maintaining a good reputation. The model then combines these inferred mental contents with the event to compute ‘appraisals’: whether the situation conformed to the expectations and fulfilled the preferences. We learn functions mapping computed appraisals to emotion labels, allowing the model to match human observers’ quantitative predictions of 20 emotions, including joy, relief, guilt and envy. Model comparison indicates that inferred monetary preferences are not sufficient to explain observers’ emotion predictions; inferred social preferences are factored into predictions for nearly every emotion. Human observers and the model both use minimal individualizing information to adjust predictions of how different people will respond to the same event. Thus, our framework integrates inverse planning, event appraisals and emotion concepts in a single computational model to reverse-engineer people’s intuitive theory of emotions. This article is part of a discussion meeting issue ‘Cognitive artificial intelligence’.
Symbols and grounding in large language models

Large language models (LLMs) are one of the most impressive achievements of artificial intelligence in recent years. However, their relevance to the study of language more broadly remains unclear. This article considers the potential of LLMs to serve as models of language understanding in humans. While debate on this question typically centres around models’ performance on challenging language understanding tasks, this article argues that the answer depends on models’ underlying competence, and thus that the focus of the debate should be on empirical work which seeks to characterize the representations and processing algorithms that underlie model behaviour. From this perspective, the article offers counterarguments to two commonly cited reasons why LLMs cannot serve as plausible models of language in humans: their lack of symbolic structure and their lack of grounding. For each, a case is made that recent empirical trends undermine the common assumptions about LLMs, and thus that it is premature to draw conclusions about LLMs’ ability (or lack thereof) to offer insights on human language representation and understanding. This article is part of a discussion meeting issue ‘Cognitive artificial intelligence’.
Hybrid Speculative Synchronisation for Parallel Discrete Event Simulation

Parallel discrete-event simulation (PDES) is a well-established family of methods to accelerate discrete-event simulations. However, the available algorithms vary substantially in the performance achievable for different models, largely preventing generic solutions applicable by modellers without expert knowledge. For instance, in Time Warp, the processing elements execute events asynchronously and speculatively with high aggressiveness, leading to frequent and costly rollbacks if misspeculations occur often. In contrast, synchronous approaches such as the new Window Racer algorithm exhibit a more cautious form of speculation. In the present paper, we combine these two fundamentally different algorithms within a single runtime environment, allowing for a choice of the best algorithm for different model segments. We describe the architecture and the algorithmic considerations to support the efficient coexistence and interaction of the algorithms without violating the correctness of the simulation. Our experiments using a synthetic benchmark and an epidemics model show that the hybrid algorithm is less sensitive to its configuration and can deliver substantially higher performance in models with varying degrees of coupling among entities compared to each algorithm on its own.
Program Analysis and Machine Learning–based Approach to Predict Power Consumption of CUDA Kernel

The General Purpose Graphics Processing Unit has secured a prominent position in the High-Performance Computing world due to its performance gain and programmability. Understanding the relationship between Graphics Processing Unit (GPU) power consumption and program features can aid developers in building energy-efficient sustainable applications. In this work, we propose a static analysis-based power model built using machine learning techniques. We have investigated six machine learning models across three NVIDIA GPU architectures: Kepler, Maxwell, and Volta with Random Forest, Extra Trees, Gradient Boosting, CatBoost, and XGBoost reporting favorable results. We observed that the XGBoost technique-based prediction model is the most efficient technique with an R2 value of 0.9646 on Volta Architecture. The dataset used for these techniques includes kernels from different benchmarks suits, sizes, nature (e.g., compute-bound, memory-bound), and complexity (e.g., control divergence, memory access patterns). Experimental results suggest that the proposed solution can help developers precisely predict GPU applications power consumption using program analysis across GPU architectures. Developers can use this approach to refactor their code to build energy-efficient GPU applications.
System Verification and Runtime Monitoring with Multiple Weakly-Hard Constraints

A weakly-hard fault model can be captured by an (m,k) constraint, where 0≤ m≤ k, meaning that there are at most m bad events (faults) among any k consecutive events. In this article, we use a weakly-hard fault model to constrain the occurrences of faults in system inputs. We develop approaches to verify properties for all possible values of (m,k), where k is smaller than or equal to a given K, in an exact and efficient manner. By verifying all possible values of (m,k), we define weakly-hard requirements for the system environment and design a runtime monitor based on counting the number of faults in system inputs. If the system environment satisfies the weakly-hard requirements, then the satisfaction of desired properties is guaranteed; otherwise, the runtime monitor can notify the system to switch to a safe mode. This is especially essential for cyber-physical systems that need to provide guarantees with limited resources and the existence of faults. Experimental results with discrete second-order control, network routing, vehicle following, and lane changing demonstrate the generality and the efficiency of the proposed approaches.
Partial Diallel Analysis For Combining Ability in Wheat

Fifteen genotypes were crossed in a partial diallel fashion. Combining ability analysis.for seven characters in two environments showed that mean squares due to general combining ability (gca) and specific combining ability (sea) were significant, the former being larger in magnitude than the latter in both environments. However, gca/sca σ2g/σ2s the ratio was higher for days to heading, plant height, number of grains/ear and 1000-grain weight. The parents HD 2009 and WH 147 far total biomass, number of grains/ear and grain yield; Raj 821 and Sonalika for early flowering, shorter height and 1000-grain weight; hd 2122 for days to heading and plant height; P 1200 for days to heading and 1000-griin weight: and Kharchia-65 for tiller number and total biomass were good general combiners.
A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef

This is the first study that evaluated the coverage of journals from Africa in Web of Science, Scopus, and CrossRef. A list of active journals published in each of the 55 African countries was compiled from Ulrich's periodicals directory and African Journals Online (AJOL) website. Journal master lists for Web of Science, Scopus, and CrossRef were searched for the African journals. A total of 2,229 unique active African journals were identified from Ulrich (N = 2,117, 95.0%) and AJOL (N = 243, 10.9%) after removing duplicates. The volume of African journals in Web of Science and Scopus databases is 7.4% (N = 166) and 7.8% (N = 174), respectively, compared to the 45.6% (N = 1,017) covered in CrossRef. While making up only 17. % of all the African journals, South African journals had the best coverage in the two most authoritative databases, accounting for 73.5% and 62.1% of all the African journals in Web of Science and Scopus, respectively. In contrast, Nigeria published 44.5% of all the African journals. The distribution of the African journals is biased in favor of Medical, Life and Health Sciences and Humanities and the Arts in the three databases. The low representation of African journals in CrossRef, a free indexing infrastructure that could be harnessed for building an African‐centric research indexing database, is concerning.
The design and evaluation of a nudge‐based interface to facilitate consumers' evaluation of online health information credibility

Evaluating the quality of online health information (OHI) is a major challenge facing consumers. We designed PageGraph, an interface that displays quality indicators and associated values for a webpage, based on credibility evaluation models, the nudge theory, and existing empirical research concerning professionals' and consumers' evaluation of OHI quality. A qualitative evaluation of the interface with 16 participants revealed that PageGraph rendered the information and presentation nudges as intended. It provided the participants with easier access to quality indicators, encouraged fresh angles to assess information credibility, provided an evaluation framework, and encouraged validation of initial judgments. We then conducted a quantitative evaluation of the interface involving 60 participants using a between‐subject experimental design. The control group used a regular web browser and evaluated the credibility of 12 preselected webpages, whereas the experimental group evaluated the same webpages with the assistance of PageGraph. PageGraph did not significantly influence participants' evaluation results. The results may be attributed to the insufficiency of the saliency and structure of the nudges implemented and the webpage stimuli's lack of sensitivity to the intervention. Future directions for applying nudges to support OHI evaluation were discussed.
Optical flow estimation in aerated flows

ABSTRACT Optical flow estimation is known from Computer Vision where it is used to determine obstacle movements through a sequence of images following an assumption of brightness conservation. This paper presents the first study on application of the optical flow method to aerated stepped spillway flows. For this purpose, the flow is captured with a high-speed camera and illuminated with a synchronized LED light source. The flow velocities, obtained using a basic Horn–Schunck method for estimation of the optical flow coupled with an image pyramid multi-resolution approach for image filtering, compare well with data from intrusive conductivity probe measurements. Application of the Horn–Schunck method yields densely populated flow field data sets with velocity information for every pixel. It is found that the image pyramid approach has the most significant effect on the accuracy compared to other image processing techniques. However, the final results show some dependency on the pixel intensity distribution, with better accuracy found for grey values between 100 and 150.
A comprehensive evolutionary scenario for the origin and neofunctionalization of the Drosophila speciation gene Odysseus (OdsH)

Odysseus (OdsH) was the first gene described in Drosophila related to speciation and hybrid sterility. This gene was first described in the melanogaster subgroup and more specifically in the sterile hybrids from crosses between D. mauritiana and D. simulans. Its origin is attributed to the duplication of the gene unc-4, which would have occurred in the ancestor of the subgenus Sophophora. By using a much larger sample of Drosophila species, we showed that contrary to what has been previously proposed, OdsH origin occurred approximately 62 million years ago (Mya). Then, OdsH have experienced rapid neofunctionalization in male reproductive tracts, evidenced by its evolutionary rates, expression and transcription factor binding sites. Furthermore, the analysis of the OdsH peptide sequence allowed the identification of mutations in the DNA- and protein-binding domains of D. mauritiana that could result in incompatibility with genomes from other species. We then explored the expression of OdsH in the spermatocytes of D. arizonae and D. mojavensis, a pair of recently diverged sister species with incomplete reproductive isolation and expected to find the involvement of OdsH in hybrid sterility. Our data indicated that OdsH expression is not atypical in male-sterile hybrids from these species. In conclusion, we have demonstrated that the origin of OdsH occurred earlier than previously proposed and that its neofunctionalization in male sexual functions occurred rapidly after its origin. Our results also suggested that its role as a speciation gene, as in the melanogaster subgroup of species, may be restricted to this specific taxon.