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EC-YOLOX : a deep learning algorithm for floating objects detection in ground images of complex water environments
No full textCorrect detection of floating objects in complex water environments is a challenge because of the problems of obscuration and dense floating objects. In view of the above issues, this article proposed a network called EC-YOLOX by introducing the coordinate attention (CA) and efficient channel attention (ECA) mechanism and improving the loss function to further the multifeature extraction and detection accuracy of floating objects. In this article, ablation experiments and comparison experiments were conducted on the river floating objects dataset. The ablation experiments showed that the ECA and CA mechanism played a great role in EC-YOLOX, which can reduce the missed detection rate by 5.86% and increase the mean average precision (mAP) by 5.53% compared with YOLOX. The EC-YOLOX was also applicable to different types of floating objects; the mAP of the ball, plastic garbage, plastic bag, leaf, milk box, grass, and branches were, respectively, improved by 4%, 4%, 4%, 6%, 4%, 18%, and 5%. The mAP of the comparison experiments was improved by 15.13%, 9.30%, and 8.03% compared to faster R-CNN, YOLOv5, and YOLOv3, respectively. This method facilitates the precise extraction of floating objects from images, which holds paramount importance for monitoring and safeguarding water environments. It offers significant contributions to water environment monitoring and protection
Preempting polarization : an experiment on opinion formation
No full textBlind adoption of opinions put forward by political parties and influential figures can sometimes be harmful. Focusing on cases where the partisan gap on policy support has not yet arisen, we investigate whether its formation can be prevented by encouraging prior active engagement with non-partisan information. To address this question, we recruited N=851 Republicans for a study about net neutrality, an issue largely unfamiliar to the electorate, which refers to equal treatment of all internet traffic. In a pre-registered experiment, we randomly changed the order in which the following two types of information were provided: (i) partisan, underscoring Republicans’ opposition and Democrats’ support, and (ii) non-partisan, where the participants evaluated factual arguments about the pros and cons of the policy. Despite holding total information constant, we find that those who saw the non-partisan block first donated 46% more to a charity advocating for net neutrality (p=0.001). The treatment effect persisted in an obfuscated follow-up study, conducted several weeks after the intervention. However, we do not find an effect on donations when repeating the main study with a sample of Democrats
Trend to equilibrium for run and tumble equations with non-uniform tumbling kernels
No full textWe study the long-time behaviour of a run and tumble model which is a kinetic-transport equation describing bacterial movement under the effect of a chemical stimulus. The experiments suggest that the non-uniform tumbling kernels are physically relevant ones as opposed to the uniform tumbling kernel which is widely considered in the literature to reduce
the complexity of the mathematical analysis. We consider two cases: (i) the tumbling kernel depends on the angle between pre- and post-tumbling velocities, (ii) the velocity space is unbounded and the post-tumbling velocities follow the Maxwellian velocity distribution.
We prove that the probability density distribution of bacteria converges to an equilibrium distribution with explicit (exponential for (i) and algebraic for (ii)) convergence rates, for any probability measure initial data. To the best of our knowledge, our results are the first results concerning the long-time behaviour of run and tumble equations with non-uniform
tumbling kernel
Optimising the diagnostic accuracy of First post-contrAst SubtracTed breast MRI (FAST MRI) through interpretation-training : a multicentre e-learning study, mapping the learning curve of NHS Breast Screening Programme (NHSBSP) mammogram readers using an enriched dataset
No full textBackground: Abbreviated breast MRI (FAST MRI) is being introduced into clinical practice to screen women with mammographically dense breasts or with a personal history of breast cancer. This study aimed to optimise diagnostic accuracy through the adaptation of interpretation-training. Methods: A FAST MRI interpretation-training programme (short presentations and guided hands-on workstation teaching) was adapted to provide additional training during the assessment task (interpretation of an enriched dataset of 125 FAST MRI scans) by giving readers feedback about the true outcome of each scan immediately after each scan was interpreted (formative assessment). Reader interaction with the FAST MRI scans used developed software (RiViewer) that recorded reader opinions and reading times for each scan. The training programme was additionally adapted for remote e-learning delivery. Study design: Prospective, blinded interpretation of an enriched dataset by multiple readers. Results: 43 mammogram readers completed the training, 22 who interpreted breast MRI in their clinical role (Group 1) and 21 who did not (Group 2). Overall sensitivity was 83% (95%CI 81–84%; 1994/2408), specificity 94% (95%CI 93–94%; 7806/8338), readers’ agreement with the true outcome kappa = 0.75 (95%CI 0.74–0.77) and diagnostic odds ratio = 70.67 (95%CI 61.59–81.09). Group 1 readers showed similar sensitivity (84%) to Group 2 (82% p = 0.14), but slightly higher specificity (94% v. 93%, p = 0.001). Concordance with the ground truth increased significantly with the number of FAST MRI scans read through the formative assessment task (p = 0.002) but by differing amounts depending on whether or not a reader had previously attended FAST MRI training (interaction p = 0.02). Concordance with the ground truth was significantly associated with reading batch size (p = 0.02), tending to worsen when more than 50 scans were read per batch. Group 1 took a median of 56 seconds (range 8–47,466) to interpret each FAST MRI scan compared with 78 (14–22,830, p < 0.0001) for Group 2. Conclusions: Provision of immediate feedback to mammogram readers during the assessment test set reading task increased specificity for FAST MRI interpretation and achieved high diagnostic accuracy. Optimal reading-batch size for FAST MRI was 50 reads per batch. Trial registration (25/09/2019): ISRCTN16624917
Teaching-track economists in the United Kingdom
No full textIn this companion paper to Arico et al (2024), we use a mixed-methods approach to characterize teaching-track faculty positions in the United Kingdom. We find these roles are more prevalent in the United Kingdom compared to the United States or Canada, and notably more oriented toward scholarship and administration duties. A high value is placed by role holders on the existence of formal networks that connect teaching-track economists across universities. We provide some context to help understand these findings, which will be relevant for academics considering these roles as well as department and university leaders
Nonlinear impairment compensation in multi-channel communication systems based on correlated digital backpropagation with separation of walk-off effect
No full textDigital backpropagation (DBP) is a commonly used method to compensate for the nonlinear impairments of optical fiber channels in the electrical domain, offering a new approach to enhancing the data capacity without affecting the system performance. However, due to the repeated Fourier transform and inverse transform of the split-step Fourier method (SSFM), the complexity of DBP algorithm has increased significantly. In this paper, a correlated backpropagation algorithm with the separation of the walk-off effect is developed, which improves the computational step and significantly reduces the complexity of the algorithm. Simulation results demonstrate that in a 6-channel PDM-16QAM system, the proposed hybrid algorithm reduces the computational complexity by 73.96 % compared to the traditional DBP algorithm for an 800 km transmission
‘Let me tell you a story’ : the politics of macroeconomic models
No full textVarious social science literatures suggest that the general character of macroeconomic models reflects their assumptive base. A more specialist literature in the Weintraub-Boumans-Morgan tradition shows how the mathematics of those models moulds together logical implications of particular starting assumptions, insights from generally accepted theoretical propositions, and professionalised common-sense about how the world works. I go one step further in arguing that a process of narrative moulding operates in tandem with this mathematical moulding. A naming strategy provides the mathematical properties of macroeconomic models with economic labels to create the feeling that they are something more than a merely mathematical structure. A storytelling strategy then informs policy-makers of where the solution to the system of equations positions the outer limits of both political desirability and political possibility. Future dedicated research programmes into the narrative dimensions of macroeconomic models can be expected to shed further light on how theory models can masquerade as policy models and substitute models as surrogate models
Structural and functional characterization of the interaction between the influenza A virus RNA polymerase and the CTD of host RNA polymerase II
No full textInfluenza A viruses, causing seasonal epidemics and occasional pandemics, rely on interactions with host proteins for their RNA genome transcription and replication. The viral RNA polymerase utilizes host RNA polymerase II (Pol II) and interacts with the serine 5 phosphorylated (pS5) C-terminal domain (CTD) of Pol II to initiate transcription. Our study, using single-particle electron cryomicroscopy (cryo-EM), reveals the structure of the 1918 pandemic influenza A virus polymerase bound to a synthetic pS5 CTD peptide composed of four heptad repeats mimicking the 52 heptad repeat mammalian Pol II CTD. The structure shows that the CTD peptide binds at the C-terminal domain of the PA viral polymerase subunit (PA-C) and reveals a previously unobserved position of the 627 domain of the PB2 subunit near the CTD. We identify crucial residues of the CTD peptide that mediate interactions with positively charged cavities on PA-C, explaining the preference of the viral polymerase for pS5 CTD. Functional analysis of mutants targeting the CTD-binding site within PA-C reveals reduced transcriptional function or defects in replication, highlighting the multifunctional role of PA-C in viral RNA synthesis. Our study provides insights into the structural and functional aspects of the influenza virus polymerase-host Pol II interaction and identifies a target for antiviral development