JURNAL AGROTEKNOLOGI
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Segmenting invisible moving objects
No full textBiological visual systems are exceptionally good at perceiving objects that undergo changes in appearance, pose, and position. In this paper, we aim to train a computational model with similar functionality to segment the moving objects in videos. We target the challenging cases when objects are ``invisible'' in the RGB video sequence, for example, breaking camouflage, where visual appearance from a static scene can barely provide informative cues, or locating the objects as a whole even under partial occlusion. To this end, we make the following contributions: (i) In order to train a motion segmentation model, we propose a scalable pipeline for generating synthetic training data, significantly reducing the requirements for labour-intensive annotations; (ii) We introduce a dual-head architecture (hybrid of ConvNets and Transformer) that takes a sequence of optical flows as input, and learns to segment the moving objects even when they are partially occluded or stop moving at certain points in videos; (iii) We conduct thorough ablation studies to analyse the critical components in data simulation, and validate the necessity of Transformer layers for aggregating temporal information and for developing object permanence. When evaluating on the MoCA camouflage dataset, the model trained only on synthetic data demonstrates state-of-the-art segmentation performance, even outperforming strong supervised approaches. In addition, we also evaluate on the popular benchmarks DAVIS2016 and SegTrackv2, and show competitive performance despite only processing optical flow
Cancellation of Tollmien-Schlichting waves with surface heating
No full textTwo-dimensional boundary layer flows in quiet disturbance environments are known to become unstable to Tollmien–Schlichting waves. The experimental work of Liepmann et al. (J Fluid Mech 118:187–200, 1982), Liepmann and Nosenchuck (J Fluid Mech 118:201–204, 1982) showed how it is possible to control and reduce unstable Tollmien–Schlichting wave amplitudes using unsteady surface heating. We consider the problem of an oncoming planar compressible subsonic boundary layer flow with a three-dimensional vibrator mounted on a flat plate, and with surface heating present. It is shown using asymptotic methods based on triple-deck theory that it is possible to choose an unsteady surface heating distribution to cancel out the response due to the vibrator. An approximation based on the exact formula is used successfully in numerical computations to confirm the findings. The results presented here are a generalisation of the analogous results for the two-dimensional problem in Brennan et al. (J Fluid Mech 909:A16-1, 2020)
Associations between lifetime classic psychedelic use and cardiometabolic diseases
No full textThe objective of the current study was to investigate the associations between lifetime classic psychedelic use and cardiometabolic diseases. Using data from the National Survey on Drug Use and Health (2005–2014), the present study examined the associations between lifetime classic psychedelic use and two types of cardiometabolic disease: heart disease and diabetes. Respondents who reported having tried a classic psychedelic at least once in their lifetime had lower odds of heart disease in the past year (adjusted odds ratio (aOR) = 0.77 (0.65–0.92), p = .006) and lower odds of diabetes in the past year (adjusted odds ratio (aOR) = 0.88 (0.78–0.99), p = .036). Classic psychedelic use might be beneficial for cardiometabolic health, but more research is needed to investigate potential causal pathways of classic psychedelics on cardiometabolic diseases
Mortality and critical care unit admission associated with the SARS-CoV-2 lineage B.1.1.7 in England: an observational cohort study
No full textBackground
A more transmissible variant of SARS-CoV-2, the variant of concern 202012/01 or lineage B.1.1.7, has emerged in the UK. We aimed to estimate the risk of critical care admission, mortality in patients who are critically ill, and overall mortality associated with lineage B.1.1.7 compared with non-B.1.1.7. We also compared clinical outcomes between these two groups.
Methods
For this observational cohort study, we linked large primary care (QResearch), national critical care (Intensive Care National Audit & Research Centre Case Mix Programme), and national COVID-19 testing (Public Health England) databases. We used SARS-CoV-2 positive samples with S-gene molecular diagnostic assay failure (SGTF) as a proxy for the presence of lineage B.1.1.7. We extracted two cohorts from the data: the primary care cohort, comprising patients in primary care with a positive community COVID-19 test reported between Nov 1, 2020, and Jan 26, 2021, and known SGTF status; and the critical care cohort, comprising patients admitted for critical care with a positive community COVID-19 test reported between Nov 1, 2020, and Jan 27, 2021, and known SGTF status. We explored the associations between SARS-CoV-2 infection with and without lineage B.1.1.7 and admission to a critical care unit (CCU), 28-day mortality, and 28-day mortality following CCU admission. We used Royston-Parmar models adjusted for age, sex, geographical region, other sociodemographic factors (deprivation index, ethnicity, household housing category, and smoking status for the primary care cohort; and ethnicity, body-mass index, deprivation index, and dependency before admission to acute hospital for the CCU cohort), and comorbidities (asthma, chronic obstructive pulmonary disease, type 1 and 2 diabetes, and hypertension for the primary care cohort; and cardiovascular disease, respiratory disease, metastatic disease, and immunocompromised conditions for the CCU cohort). We reported information on types and duration of organ support for the B.1.1.7 and non-B.1.1.7 groups.
Findings
The primary care cohort included 198 420 patients with SARS-CoV-2 infection. Of these, 117 926 (59·4%) had lineage B.1.1.7, 836 (0·4%) were admitted to CCU, and 899 (0·4%) died within 28 days. The critical care cohort included 4272 patients admitted to CCU. Of these, 2685 (62·8%) had lineage B.1.1.7 and 662 (15·5%) died at the end of critical care. In the primary care cohort, we estimated adjusted hazard ratios (HRs) of 2·15 (95% CI 1·75–2·65) for CCU admission and 1·65 (1·36–2·01) for 28-day mortality for patients with lineage B.1.1.7 compared with the non-B.1.1.7 group. The adjusted HR for mortality in critical care, estimated with the critical care cohort, was 0·91 (0·76–1·09) for patients with lineage B.1.1.7 compared with those with non-B.1.1.7 infection.
Interpretation
Patients with lineage B.1.1.7 were at increased risk of CCU admission and 28-day mortality compared with patients with non-B.1.1.7 SARS-CoV-2. For patients receiving critical care, mortality appeared to be independent of virus strain. Our findings emphasise the importance of measures to control exposure to and infection with COVID-19.
Funding
Wellcome Trust, National Institute for Health Research Oxford Biomedical Research Centre, and the Medical Sciences Division of the University of Oxford
The representation of winter Northern Hemisphere atmospheric blocking in the ECMWF seasonal prediction systems
No full textThe simulation and prediction of winter Northern Hemisphere atmospheric blocking in the seasonal prediction systems from the European Centre for Medium‐Range Weather Forecasts (ECMWF) is analysed. Blocking statistics from the operational November‐initialised seasonal hindcasts are evaluated in three generations of models: System3, System4, and System5 (SEAS5). Improvements in the climatological representation of blocking are observed in the most recent model configurations, with reduced bias over North Pacific and Greenland. Minor progress is seen over the European sector, where SEAS5 still underestimates the observed blocking frequency. SEAS5 blocking interannual variability is underestimated too and is proportional to the climatological frequency, highlighting that a negative bias in the blocking frequency implies an underestimation of the interannual variance. SEAS5 predictive skill and signal‐to‐noise ratio remain low, but interesting positive results are found over Western and Central Europe. Improved forecasts with reduced ensemble spread are obtained during El Niño years, especially at low latitudes. Complementary experiments show that the statistics of blocking are improved following atmospheric and oceanic resolution increase. Conversely, they remain largely insensitive to coupled model sea‐surface temperature (SST) errors. On the other hand, the implementation of stochastic parameterisations tends to displace blocking activity equatorward. Finally, by comparing seasonal hindcasts with climate runs using the same model, we highlight that the largest contributors to the chronic underestimation of blocking are persistent errors in the atmospheric model. It is also shown that SST errors have a larger impact on blocking bias in climate runs than in seasonal runs, and that increased ocean model resolution contributes to improved blocking more effectively in climate runs. Seasonal forecasts can thus be considered a suitable test‐bed for model development targeting blocking improvement in climate models
Collective Reflective Equilibrium in Practice (CREP) and controversial novel technologies
No full textIn this paper, we investigate how data about public preferences may be used to inform policy around the use of controversial novel technologies, using public preferences about autonomous vehicles (AVs) as a case study. We first summarize the recent ‘Moral Machine’ study, which generated preference data from millions of people regarding how they think AVs should respond to emergency situations. We argue that while such preferences cannot be used to directly inform policy, they should not be disregarded. We defend an approach that we call ‘Collective Reflective Equilibrium in Practice’ (CREP). In CREP, data on public attitudes function as an input into a deliberative process that looks for coherence between attitudes, behaviours and competing ethical principles. We argue that in cases of reasonable moral disagreement, data on public attitudes should play a much greater role in shaping policies than in areas of ethical consensus. We apply CREP to some of the global preferences about AVs uncovered by the Moral Machines study. We intend this discussion both as a substantive contribution to the debate about the programming of ethical AVs, and as an illustration of how CREP works. We argue that CREP provides a principled way of using some public preferences as an input for policy, while justifiably disregarding others
Using Point of Care Testing to estimate influenza vaccine effectiveness in the English primary care sentinel surveillance network
No full textIntroduction
Rapid Point of Care Testing (POCT) for influenza could be used to provide information on influenza vaccine effectiveness (IVE) as well as influencing clinical decision-making in primary care.
Methods
We undertook a test negative case control study to estimate the overall and age-specific (6 months-17 years, 18–64 years, ≥65 years old) IVE against medically attended POCT-confirmed influenza. The study took place over the winter of 2019–2020 and was nested within twelve general practices that are part of the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), the English sentinel surveillance network.
Results
648 POCT were conducted. 193 (29.7%) of those who were swabbed had received the seasonal influenza vaccine. The crude unadjusted overall IVE was 46.1% (95% CI: 13.9–66.3). After adjusting for confounders the overall IVE was 26.0% (95% CI: 0–65.5). In total 211 patients were prescribed an antimicrobial after swab testing. Given a positive influenza POCT result, the odds ratio (OR) of receiving an antiviral was 21.1 (95%CI: 2.4–182.2, p = <0.01) and the OR of being prescribed an antibiotic was 0.6 (95%CI: 0.4–0.9, p = <0.01).
Discussion
Using influenza POCT in a primary care sentinel surveillance network to estimate IVE is feasible and provides comparable results to published IVE estimates. A further advantage is that near patient testing of influenza is associated with improvements in appropriate antiviral and antibiotic use. Larger, randomised studies are needed in primary care to see if these trends are still present and to explore their impact on outcomes
Heightened resistance to host type 1 interferons characterizes HIV-1 at transmission and after antiretroviral therapy interruption
No full textType 1 interferons (IFN-I) are potent innate antiviral effectors that constrain HIV-1 transmission. However, harnessing these cytokines for HIV-1 cure strategies has been hampered by an incomplete understanding of their antiviral activities at later stages of infection. Here, we characterized the IFN-I sensitivity of 500 clonally derived HIV-1 isolates from the plasma and CD4+ T cells of 26 individuals sampled longitudinally after transmission or after antiretroviral therapy (ART) and analytical treatment interruption. We determined the concentration of IFNα2 and IFNβ that reduced viral replication in vitro by 50% (IC50) and found consistent changes in the sensitivity of HIV-1 to IFN-I inhibition both across individuals and over time. Resistance of HIV-1 isolates to IFN-I was uniformly high during acute infection, decreased in all individuals in the first year after infection, was reacquired concomitant with CD4+ T cell loss, and remained elevated in individuals with accelerated disease. HIV-1 isolates obtained by viral outgrowth during suppressive ART were relatively IFN-I sensitive, resembling viruses circulating just before ART initiation. However, viruses that rebounded after treatment interruption displayed the highest degree of IFNα2 and IFNβ resistance observed at any time during the infection course. These findings indicate a dynamic interplay between host innate responses and the evolving HIV-1 quasispecies, with the relative contribution of IFN-I to HIV-1 control affected by both ART and analytical treatment interruption. Although elevated at transmission, host innate pressures are the highest during viral rebound, limiting the viruses that successfully become reactivated from latency to those that are IFN-I resistant
Multiple spatial behaviours govern social network positions in a wild ungulate
No full textThe structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals’ observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43‐year dataset detailing a wild red deer population to investigate how individuals’ spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi‐matrix animal models, we demonstrate that social network positions are shaped by two‐dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual‐level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality
Frequency modulation of entorhinal cortex neuronal activity drives distinct frequency-dependent states of brain-wide dynamics
No full textHuman neuroimaging studies have shown that, during cognitive processing, the brain undergoes dynamic transitions between multiple, frequency-tuned states of activity. Although different states may emerge from distinct sources of neural activity, it remains unclear whether single-area neuronal spiking can also drive multiple dynamic states. In mice, we ask whether frequency modulation of the entorhinal cortex activity causes dynamic states to emerge and whether these states respond to distinct stimulation frequencies. Using hidden Markov modeling, we perform unsupervised detection of transient states in mouse brain-wide fMRI fluctuations induced via optogenetic frequency modulation of excitatory neurons. We unveil the existence of multiple, frequency-dependent dynamic states, invisible through standard static fMRI analyses. These states are linked to different anatomical circuits and disrupted in a frequency-dependent fashion in a transgenic model of cognitive disease directly related to entorhinal cortex dysfunction. These findings provide cross-scale insight into basic neuronal mechanisms that may underpin flexibility in brain-wide dynamics