University of Hawaii at Manoa

About: University of Hawaii at Manoa is a education organization based out in Honolulu, Hawaii, United States. It is known for research contribution in the topics: Population & Sea surface temperature. The organization has 13693 authors who have published 25161 publications receiving 1023924 citations.

Ovarian cancer and smoking: individual participant meta-analysis including 28 114 women with ovarian cancer from 51 epidemiological studies

Abstract: Background Smoking has been linked to mucinous ovarian cancer, but its effects on other ovarian cancer subtypes and on overall ovarian cancer risk are unclear, and the findings from most studies with relevant data are unpublished To assess these associations, we review the published and unpublished evidence Methods Eligible epidemiological studies were identified by electronic searches, review articles, and discussions with colleagues Individual participant data for 28 114 women with and 94 942 without ovarian cancer from 51 epidemiological studies were analysed centrally, yielding adjusted relative risks (RRs) of ovarian cancer in smokers compared with never smokers Findings After exclusion of studies with hospital controls, in which smoking could have affected recruitment, overall ovarian cancer incidence was only slightly increased in current smokers compared with women who had never smoked (RR 106, 95% CI 101-111, p=001) Of 17 641 epithelial cancers with specified histology, 2314 (13%) were mucinous, 2360 (13%) endometrioid, 969 (5%) clear-cell, and 9086 (52%) serous Smoking-related risks varied substantially across these subtypes (p(heterogeneity)<00001) For mucinous cancers, incidence was increased in current versus never smokers (179, 95% CI 160-200, p<00001), but the increase was mainly in borderline malignant rather than in fully malignant tumours (225, 95% CI 191-265 vs 149, 128-173; p(heterogeneity)=001; almost half the mucinous tumours were only borderline malignant) Both endometrioid (081, 95% CI 072-092, p=0001) and clear-cell ovarian cancer risks (080, 95% CI 065-097, p=003) were reduced in current smokers, and there was no significant association for serous ovarian cancers (099, 95% CI 093-106, p=08) These associations did not vary significantly by 13 sociodemographic and personal characteristics of women including their body-mass index, parity, and use of alcohol, oral contraceptives, and menopausal hormone therapy Interpretation The excess of mucinous ovarian cancers in smokers, which is mainly of tumours of borderline malignancy, is roughly counterbalanced by the deficit of endometrioid and clear-cell ovarian cancers The substantial variation in smoking-related risks by tumour subtype is important for understanding ovarian carcinogenesis

An agent-based framework for building decision support systems

Abstract: This paper proposes a framework for building decision support systems using software agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous information systems. Intelligent agents have offered tremendous potential in supporting well-defined tasks such as information filtering, data mining and data conversion. However, the use of intelligent agents to support decisions has not been explored and merits serious consideration. This paper proposes a taxonomy of agent characteristics that can be used to help identify agents to support different types of decision tasks. We advocate a goal-directed, behavior-based architecture for building cooperative decision support using agents. We look at the development of agent-based DSS as being a process of putting together a coordinated workflow of collaborating agents that is able to support a problem-solving process. The methodology is illustrated by a selection of intelligent agents to support Crisis Action Procedures in a large organization.

Bimodal representation of the tropical intraseasonal oscillation

Abstract: The tropical intraseasonal oscillation (ISO) shows distinct variability centers and propagation patterns between boreal winter and summer. To accurately represent the state of the ISO at any particular time of a year, a bimodal ISO index was developed. It consists of Madden-Julian Oscillation (MJO) mode with predominant eastward propagation along the equator and Boreal Summer ISO (BSISO) mode with prominent northward propagation and large variability in off-equatorial monsoon trough regions. The spatial–temporal patterns of the MJO and BSISO modes are identified with the extended empirical orthogonal function analysis of 31 years (1979–2009) OLR data for the December–February and June–August period, respectively. The dominant mode of the ISO at any given time can be judged by the proportions of the OLR anomalies projected onto the two modes. The bimodal ISO index provides objective and quantitative measures on the annual and interannual variations of the predominant ISO modes. It is shown that from December to April the MJO mode dominates while from June to October the BSISO mode dominates. May and November are transitional months when the predominant mode changes from one to the other. It is also shown that the fractional variance reconstructed based on the bimodal index is significantly higher than the counterpart reconstructed based on the Wheeler and Hendon’s index. The bimodal ISO index provides a reliable real time monitoring skill, too. The method and results provide critical information in assessing models’ performance to reproduce the ISO and developing further research on predictability of the ISO and are also useful for a variety of scientific and practical purposes.

Late Pleistocene climate drivers of early human migration

Abstract: On the basis of fossil and archaeological data it has been hypothesized that the exodus of Homo sapiens out of Africa and into Eurasia between ~50-120 thousand years ago occurred in several orbitally paced migration episodes. Crossing vegetated pluvial corridors from northeastern Africa into the Arabian Peninsula and the Levant and expanding further into Eurasia, Australia and the Americas, early H. sapiens experienced massive time-varying climate and sea level conditions on a variety of timescales. Hitherto it has remained difficult to quantify the effect of glacial- and millennial-scale climate variability on early human dispersal and evolution. Here we present results from a numerical human dispersal model, which is forced by spatiotemporal estimates of climate and sea level changes over the past 125 thousand years. The model simulates the overall dispersal of H. sapiens in close agreement with archaeological and fossil data and features prominent glacial migration waves across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. The findings document that orbital-scale global climate swings played a key role in shaping Late Pleistocene global population distributions, whereas millennial-scale abrupt climate changes, associated with Dansgaard-Oeschger events, had a more limited regional effect.

Evolution and forcing mechanisms of El Niño over the past 21,000 years

Abstract: A simulation of the evolution of El Nino Southern Oscillation in the past 21,000 years in a state-of-the-art climate model shows the complex response mechanisms of El Nino to external climate forcings and poses further challenges to our understanding and projection of El Nino in the future. Palaeoclimate evidence has suggested that the El Nino Southern Oscillation (ENSO) — the most important driver of interannual climate variability — has swung from periods of intense variability to relative quiescence. Zhengyu Liu and colleagues use a series of climate simulations to show that since the Last Glacial Maximum, consistent with palaeoclimate data interpretations, orbital changes have tended to strengthen the ENSO. Variations in ocean circulation, increasing CO2, and retreating ice sheets all influenced ENSO, but at different times and sometimes in offsetting directions. For example, increasing CO2 tended to weaken ENSO, but this influence was opposed by ENSO-enhancing effects from retreating ice. The simulations demonstrate that the ENSO state at any one time reflects the net impact of a series of different climate forcings. The El Nino Southern Oscillation (ENSO) is Earth’s dominant source of interannual climate variability, but its response to global warming remains highly uncertain1. To improve our understanding of ENSO’s sensitivity to external climate forcing, it is paramount to determine its past behaviour by using palaeoclimate data and model simulations. Palaeoclimate records show that ENSO has varied considerably since the Last Glacial Maximum (21,000 years ago)2,3,4,5,6,7,8,9, and some data sets suggest a gradual intensification of ENSO over the past ∼6,000 years2,5,7,8. Previous attempts to simulate the transient evolution of ENSO have relied on simplified models10 or snapshot11,12,13 experiments. Here we analyse a series of transient Coupled General Circulation Model simulations forced by changes in greenhouse gasses, orbital forcing, the meltwater discharge and the ice-sheet history throughout the past 21,000 years. Consistent with most palaeo-ENSO reconstructions, our model simulates an orbitally induced strengthening of ENSO during the Holocene epoch, which is caused by increasing positive ocean–atmosphere feedbacks. During the early deglaciation, ENSO characteristics change drastically in response to meltwater discharges and the resulting changes in the Atlantic Meridional Overturning Circulation and equatorial annual cycle. Increasing deglacial atmospheric CO2 concentrations tend to weaken ENSO, whereas retreating glacial ice sheets intensify ENSO. The complex evolution of forcings and ENSO feedbacks and the uncertainties in the reconstruction further highlight the challenge and opportunity for constraining future ENSO responses.