This paper presents ACROMUSE, a novel genetic algorithm (GA) which adapts crossover, mutation, and selection parameters. ACROMUSEs objective is to create and maintain a diverse population of ...highly-fit (healthy) individuals, capable of adapting quickly to fitness landscape change and well-suited to the efficient optimization of multimodal fitness landscapes. A new methodology is introduced for determining standard population diversity (SPD) and an original measure of healthy population diversity (HPD) is proposed. The SPD measure is employed to adapt crossover and mutation, while selection pressure is controlled by adapting tournament size according to HPD. In addition to selection pressure control, ACROMUSE tournament selection selects individuals according to healthy diversity contribution rather than fitness. This proposed selection mechanism simultaneously promotes diversity and fitness within the population. The performance of ACROMUSE is evaluated using various multimodal benchmark functions. Statistically significant results are presented comparing ACROMUSEs fitness and diversity performance to that of several other GAs. By maintaining a diverse population of healthy individuals, ACROMUSE responds to fitness landscape change by restoring better fitness scores faster than other GAs. Analysis of the adaptive operators illustrates that the key benefit of ACROMUSE is the synergy of the operators working together to achieve an effective balance between exploration and exploitation.
Drug utilization under Medicare Part D varies significantly by geographic region. This study examined the extent to which geographic variation in Part D plan characteristics contributes to the ...variation in choice of initial endocrine therapy agent among women with incident breast cancer.
Two-stage multivariate regression analyses were applied to the 16,541 women identified from Medicare claims as having incident breast cancer in 2006-2007. The first stage determined the effect of state of residence on the probability of having an aromatase inhibitor (AI), as opposed to tamoxifen, as initial endocrine therapy. The second stage provided estimates of the impact of state-specific Part D plan characteristics on variation in choice of initial therapy.
There was substantial residual geographic variation in the likelihood of using an AI as initial endocrine therapy, despite controlling for socioeconomic status, breast cancer treatment, and other factors. Regression-adjusted probabilities of starting an AI ranged from 57.3% in Wyoming to 92.6% in the District of Columbia. Results from the second stage revealed that variation in characteristics of Part D plans across states explained approximately one-third (30%) of the state-level variability in endocrine therapy. A higher number of plans with cost-sharing above the mean, greater spread in deductibles, and a greater spread in monthly drug premiums were associated with lower adjusted state probabilities of initiating an AI. In contrast, a higher number of drug plans with monthly premiums above the state mean and higher mean cost-sharing (in dollars) were both positively associated with likelihood of starting on an AI.
Study findings suggest that variation in benefit design of Part D plans accounts for an important share of the large and persisting variability in use of AIs-the preferred oral therapy for breast cancer.
Purpose
The high expense of newer, more effective adjuvant endocrine therapy agents (aromatase inhibitors AIs) for postmenopausal breast cancer contributes to socioeconomic disparities in breast ...cancer outcomes. This study compares endocrine therapy costs for breast cancer patients during the first five years of Medicare Part D implementation, and when generic alternatives became available.
Methods
The out of pocket patient costs for AIs and tamoxifen under Medicare Part D drug plans were determined for 2006–2011 from the CMS Website for the 50 US states and District of Columbia.
Results
Between 2006 and 2010, the mean annual patient drug cost under Medicare Part D in the median state rose 19% for tamoxifen, 113% for anastrozole, 89% for exemestane, and 129% for letrozole, resulting in median annual out of pocket costs in 2010 of $701, $3050, $2804, and $3664 respectively. However, the 2011 availability of generic AI preparations led to median annual costs in 2011 of $804, $872, $1837, and $2217 respectively. Not included in the reported patient costs, the mean monthly drug premiums in the median state increased 58% in 2011 compared to 2007.
Conclusions
The more effective AI agents became considerably more expensive during the first several years of the Medicare Part D program. Cost decreased with the introduction of generic agents, an intervention that was independent of the Part D program. It is unlikely that the Part D program ameliorated existing socioeconomic disparities in survival among breast cancer patients, but the availability of generic agents may do so.
High-resolution (3 km) time-lagged (initialized every 3 h) multimodel ensembles were produced in support of the Hydrometeorological Testbed (HMT)-West-2006 campaign in northern California, covering ...the American River basin (ARB). Multiple mesoscale models were used, including the Weather Research and Forecasting (WRF) model, Regional Atmospheric Modeling System (RAMS), and fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Short-range (6 h) quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) were compared to the 4-km NCEP stage IV precipitation analyses for archived intensive operation periods (IOPs). The two sets of ensemble runs (operational and rerun forecasts) were examined to evaluate the quality of high-resolution QPFs produced by time-lagged multimodel ensembles and to investigate the impacts of ensemble configurations on forecast skill. Uncertainties in precipitation forecasts were associated with different models, model physics, and initial and boundary conditions. The diabatic initialization by the Local Analysis and Prediction System (LAPS) helped precipitation forecasts, while the selection of microphysics was critical in ensemble design. Probability biases in the ensemble products were addressed by calibrating PQPFs. Using artificial neural network (ANN) and linear regression (LR) methods, the bias correction of PQPFs and a cross-validation procedure were applied to three operational IOPs and four rerun IOPs. Both the ANN and LR methods effectively improved PQPFs, especially for lower thresholds. The LR method outperformed the ANN method in bias correction, in particular for a smaller training data size. More training data (e.g., one-season forecasts) are desirable to test the robustness of both calibration methods.
IMPROVING QPE AND VERY SHORT TERM QPF Vasiloff, Steven V.; Seo, Dong-Jun; Howard, Kenneth W. ...
Bulletin of the American Meteorological Society,
12/2007, Letnik:
88, Številka:
12
Journal Article
Recenzirano
Odprti dostop
Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and ...water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.
Abstract
Short-range quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) are investigated for a time-lagged multimodel ensemble forecast system. One of the advantages of such ...an ensemble forecast system is its low-cost generation of ensemble members. In conjunction with a frequently cycling data assimilation system using a diabatic initialization such as the Local Analysis and Prediction System (LAPS), the time-lagged multimodel ensemble system offers a particularly appealing approach for QPF and PQPF applications. Using the NCEP stage IV precipitation analyses for verification, 6-h QPFs and PQPFs from this system are assessed during the period of March–May 2005 over the west-central United States. The ensemble system was initialized by hourly LAPS runs at a horizontal resolution of 12 km using two mesoscale models, including the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecast (WRF) model with the Advanced Research WRF (ARW) dynamic core. The 6-h PQPFs from this system provide better performance than the NCEP operational North American Mesoscale (NAM) deterministic runs at 12-km resolution, even though individual members of the MM5 or WRF models perform comparatively worse than the NAM forecasts at higher thresholds and longer lead times. Recalibration was conducted to reduce the intensity errors in time-lagged members. In spite of large biases and spatial displacement errors in the MM5 and WRF forecasts, statistical verification of QPFs and PQPFs shows more skill at longer lead times by adding more members from earlier initialized forecast cycles. Combing the two models only reduced the forecast biases. The results suggest that further studies on time-lagged multimodel ensembles for operational forecasts are needed.
Future optical materials promise to do for photonics what semiconductors did for electronics, but the challenge has long been in creating the structure they require-a regular, three-dimensional array ...of transparent microspheres arranged like the atoms in a diamond crystal. Here we demonstrate a simple approach for spontaneously growing double-diamond (or B32) crystals that contain a suitable diamond structure, using DNA to direct the self-assembly process. While diamond symmetry crystals have been grown from much smaller nanoparticles, none of those previous methods suffice for the larger particles needed for photonic applications, whose size must be comparable to the wavelength of visible light. Intriguingly, the crystals we observe do not readily form in previously validated simulations; nor have they been predicted theoretically. This finding suggests that other unexpected microstructures may be accessible using this approach and bodes well for future efforts to inexpensively mass-produce metamaterials for an array of photonic applications.
See Josephs (doi:10.1093/brain/awx367) for a scientific commentary on this article.
Mutations in the MAPT gene on chromosome 17 are associated with frontotemporal lobar degeneration (FTLD). ...Mutation-associated cases are currently classified separately from sporadic cases with tau inclusions, as FTDP-17, but Forrest et al. provide evidence that these cases should in fact be considered familial forms of FTLD-tau subtypes.
Abstract
See Josephs (doi:10.1093/brain/awx367) for a scientific commentary on this article.
In many neurodegenerative disorders, familial forms have provided important insights into the pathogenesis of their corresponding sporadic forms. The first mutations associated with frontotemporal lobar degeneration (FTLD) were found in the microtubule-associated protein tau (MAPT) gene on chromosome 17 in families with frontotemporal degeneration and parkinsonism (FTDP-17). However, it was soon discovered that 50% of these families had a nearby mutation in progranulin. Regardless, the original FTDP-17 nomenclature has been retained for patients with MAPT mutations, with such patients currently classified independently from the different sporadic forms of FTLD with tau-immunoreactive inclusions (FTLD-tau). The separate classification of familial FTLD with MAPT mutations implies that familial forms cannot inform on the pathogenesis of the different sporadic forms of FTLD-tau. To test this assumption, this study pathologically assessed all FTLD-tau cases with a known MAPT mutation held by the Sydney and Cambridge Brain Banks, and compared them to four cases of four subtypes of sporadic FTLD-tau, in addition to published case reports. Ten FTLD-tau cases with a MAPT mutation (K257T, S305S, P301L, IVS10+16, R406W) were screened for the core differentiating neuropathological features used to diagnose the different sporadic FTLD-tau subtypes to determine whether the categorical separation of MAPT mutations from sporadic FTLD-tau is valid. Compared with sporadic cases, FTLD-tau cases with MAPT mutations had similar mean disease duration but were younger at age of symptom onset (55 ± 4 years versus 70 ± 6 years). Interestingly, FTLD-tau cases with MAPT mutations had similar patterns and severity of neuropathological features to sporadic FTLD-tau subtypes and could be classified into: Pick's disease (K257T), corticobasal degeneration (S305S, IVS10+16, R406W), progressive supranuclear palsy (S305S) or globular glial tauopathy (P301L, IVS10+16). The finding that the S305S mutation could be classified into two tauopathies suggests additional modifying factors. Assessment of our cases and previous reports suggests that distinct MAPT mutations result in particular FTLD-tau subtypes, supporting the concept that they are likely to inform on the varied cellular mechanisms involved in distinctive forms of sporadic FTLD-tau. As such, FTLD-tau cases with MAPT mutations should be considered familial forms of FTLD-tau subtypes rather than a separate FTDP-17 category, and continued research on the effects of different mutations more focused on modelling their impact to produce the very different sporadic FTLD-tau pathologies in animal and cellular models.
A high-resolution (9-km) diabatic data assimilation system—the Local Analysis and Prediction System (LAPS), has been developed and used to initialize the real-time fifth-generation Pennsylvania State ...University—National Center for Atmospheric Research Mesoscale Model (MM5) at the Central Weather Bureau in Taiwan. During 2003, the more extensive network of four high quality Doppler radars and the access to satellite data from the Geostationary Operational Environmental Satellite (GOES-9) provided an excellent opportunity for advancing the short-range precipitation forecasts over the Taiwan area. The parallel forecasts of four tropical cyclones (Tropical Storm Morakot and Vamco, Typhoon Dujuan, and Tropical Storm Melor) that affected Taiwan in 2003 are performed, both with and without the inclusion of the LAPS cloud analysis scheme. Except for the inclusion of the LAPS cloud field, the model integrations are identical in all other respects. Forecast results demonstrate that using LAPS to diabatically initialize MM5 leads to an improved prediction of tropical cyclones in terms of the storm’s track, intensity, cloud pattern, and movement of rainbands in the early portion ofmodel prediction. During the first 6-h of the forecast, the heavy rainfall prediction associated with the cases studied was improved when the LAPS cloud analysis scheme was included. The assimilation of data from Doppler radars, and GOES-9 satellite, played an important role in the improvement of storm hydrometeorological features in the model initial condition and thus had a beneficial impact on reducing the model spin-up time. However, further studies are needed to clarify the reasons for the poor performance in simulating the typhoon eyewall. This paper represents a major step toward building a short-range mesoscale modeling system that predicts more realistic storm structures and rainfall distribution over the Taiwan area in real time. The overall results suggest that the impact ofthe LAPS/MM5 system can be significant for short-range, high spatial-resolution, rainfall prediction associated with a tropical cyclone, especially for the heavy rainfall occurring during the early hours of the model integration.
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