Theoretical studies of the transport and removal processes of Sahara dust

The processes controlling the evolution of aerosol particles may be divided into dynamic processes concerned with the motions of air currents and microphysical processes concerned with the growth of the individual particles. The Ames planetary boundary layer model was modified to construct a subsynoptic scale aerosol model to study the long term fate of the Saharan dust. The transport model consists of a mixed layer, a convection layer, and free atmosphere. Conditions used for a preliminary test run and results obtained are described

Observational studies of urban heat island characteristics in different climatic zones

Thesis (Ph.D. in Science)--University of Tsukuba, (B), no. 763, 1992.3.2

Reinstated episodic context guides sampling-based decisions for reward.

How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free reinforcement learning; however, samples can vary from trial to trial, causing decisions to vary. Here we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of reinforcement learning. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event. This effect is mediated by fMRI measures of context retrieval on each trial, suggesting a mechanism whereby cues trigger retrieval of context, which then triggers retrieval of other decisions from that context. This result establishes a new avenue by which experience can guide choice and, as such, has broad implications for the study of decisions

Adipocyte-Specific Hypoxia-Inducible Factor 2α Deficiency Exacerbates Obesity-Induced Brown Adipose Tissue Dysfunction and Metabolic Dysregulation

Angiogenesis is a central regulator for white (WAT) and brown (BAT) adipose tissue adaptation in the course of obesity. Here we show that deletion of hypoxia-inducible factor 2α (HIF2α) in adipocytes (by using Fabp4-Cre transgenic mice) but not in myeloid or endothelial cells negatively impacted WAT angiogenesis and promoted WAT inflammation, WAT dysfunction, hepatosteatosis, and systemic insulin resistance in obesity. Importantly, adipocyte HIF2α regulated vascular endothelial growth factor (VEGF) expression and angiogenesis of obese BAT as well as its thermogenic function. Consistently, obese adipocyte-specific HIF2α-deficient mice displayed BAT dysregulation, associated with reduced levels of uncoupling protein 1 (UCP1) and a dysfunctional thermogenic response to cold exposure. VEGF administration reversed WAT and BAT inflammation and BAT dysfunction in adipocyte HIF2α-deficient mice. Together, our findings show that adipocyte HIF2α is protective against maladaptation to obesity and metabolic dysregulation by promoting angiogenesis in both WAT and BAT and by counteracting obesity-mediated BAT dysfunction

PickBlue: Seismic Phase Picking for Ocean Bottom Seismometers With Deep Learning

Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data, machine learning methods have already found widespread adoption. However, deep learning approaches are not yet commonly applied to ocean bottom data due to a lack of appropriate training data and models. Here, we compiled an extensive and labeled ocean bottom seismometer (OBS) data set from 15 deployments in different tectonic settings, comprising ∼90,000 P and ∼63,000 S manual picks from 13,190 events and 355 stations. We propose PickBlue, an adaptation of the two popular deep learning networks EQTransformer and PhaseNet. PickBlue joint processes three seismometer recordings in conjunction with a hydrophone component and is trained with the waveforms in the new database. The performance is enhanced by employing transfer learning, where initial weights are derived from models trained with land earthquake data. PickBlue significantly outperforms neural networks trained with land stations and models trained without hydrophone data. The model achieves a mean absolute deviation of 0.05 s for P-waves and 0.12 s for S-waves, and we apply the picker on the Hikurangi Ocean Bottom Tremor and Slow Slip OBS deployment offshore New Zealand. We integrate our data set and trained models into SeisBench to enable an easy and direct application in future deployments

One-Year Risk of Stroke after Transient Ischemic Attack or Minor Stroke

BACKGROUND Previous studies conducted between 1997 and 2003 estimated that the risk of stroke or an acute coronary syndrome was 12 to 20% during the first 3 months after a transient ischemic attack (TIA) or minor stroke. The TIAregistry.org project was designed to describe the contemporary profile, etiologic factors, and outcomes in patients with a TIA or minor ischemic stroke who receive care in health systems that now offer urgent evaluation by stroke specialists. METHODS We recruited patients who had had a TIA or minor stroke within the previous 7 days. Sites were selected if they had systems dedicated to urgent evaluation of patients with TIA. We estimated the 1-year risk of stroke and of the composite outcome of stroke, an acute coronary syndrome, or death from cardiovascular causes. We also examined the association of the ABCD2 score for the risk of stroke (range, 0 [lowest risk] to 7 [highest risk]), findings on brain imaging, and cause of TIA or minor stroke with the risk of recurrent stroke over a period of 1 year. RESULTS From 2009 through 2011, we enrolled 4789 patients at 61 sites in 21 countries. A total of 78.4% of the patients were evaluated by stroke specialists within 24 hours after symptom onset. A total of 33.4% of the patients had an acute brain infarction, 23.2% had at least one extracranial or intracranial stenosis of 50% or more, and 10.4% had atrial fibrillation. The Kaplan–Meier estimate of the 1-year event rate of the composite cardiovascular outcome was 6.2% (95% confidence interval, 5.5 to 7.0). Kaplan–Meier estimates of the stroke rate at days 2, 7, 30, 90, and 365 were 1.5%, 2.1%, 2.8%, 3.7%, and 5.1%, respectively. In multivariable analyses, multiple infarctions on brain imaging, large-artery atherosclerosis, and an ABCD2 score of 6 or 7 were each associated with more than a doubling of the risk of stroke. CONCLUSIONS We observed a lower risk of cardiovascular events after TIA than previously reported. The ABCD2 score, findings on brain imaging, and status with respect to large-artery atherosclerosis helped stratify the risk of recurrent stroke within 1 year after a TIA or minor stroke. (Funded by Sanofi and Bristol-Myers Squibb.)Supported by an unrestricted grant from Sanofi and Bristol-Myers Squibb

Excludability: A laboratory study on forced ranking in team production

Exclusion has long been employed as a common disciplinary measure against defectors, both at work and in social life. In this paper, we study the effect of excludability - exclusion of the lowest contributor - on contributions in three different team production settings. We demonstrate theoretically and experimentally that excludability increases contributions. Excludability is particularly effective in production settings where the average or maximum effort determines team production. In these settings, we observe almost immediate convergence to full contribution. In settings where the minimum effort determines team production, excludability leads to a large increase in contributions only if the value of the excluded individual's contribution to the public good is redistributed among the included individuals

Seeing two faces together: preference formation in humans and rhesus macaques

Humans, great apes and old world monkeys show selective attention to faces depending on conspecificity, familiarity, and social status supporting the view that primates share similar face processing mechanisms. Although many studies have been done on face scanning strategy in monkeys and humans, the mechanisms influencing viewing preference have received little attention. To determine how face categories influence viewing preference in humans and rhesus macaques (Macaca mulatta), we performed two eye-tracking experiments using a visual preference task whereby pairs of faces from different species were presented simultaneously. The results indicated that viewing time was significantly influenced by the pairing of the face categories. Humans showed a strong bias towards an own-race face in an Asian–Caucasian condition. Rhesus macaques directed more attention towards non-human primate faces when they were paired with human faces, regardless of the species. When rhesus faces were paired with faces from Barbary macaques (Macaca sylvanus) or chimpanzees (Pan troglodytes), the novel species’ faces attracted more attention. These results indicate that monkeys’ viewing preferences, as assessed by a visual preference task, are modulated by several factors, species and dominance being the most influential