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We have completed a second-generation linkage map that incorporates sequence-based positional information. This new map, the Rutgers Map v.2, includes 28,121 polymorphic markers with physical positions corroborated by recombination-based data. Sex-averaged and sex-specific linkage map distances, along with confidence intervals, have been estimated for all map intervals. In addition, a regression-based smoothed map is provided that facilitates interpolation of positions of unmapped markers on this map. With nearly twice as many markers as our first-generation map, the Rutgers Map continues to be a unique and comprehensive resource for obtaining genetic map information for large sets of polymorphic markers.

Large-scale environmental sensing, e.g., understanding microbial processes in an aquatic ecosystem, requires coordination across a multidisciplinary team of experts working closely with a robotic sensing and sampling system. We describe a human-robot team that conducted an aquatic sampling campaign in Lake Fulmor, San Jacinto Mountains Reserve, California during three consecutive site visits (May 9–11, June 19–22, and August 28–31, 2006). The goal of the campaign was to study the behavior of phytoplankton in the lake and their relationship to the underlying physical, chemical, and biological parameters. Phytoplankton form the largest source of oxygen and the foundation of the food web in most aquatic ecosystems. The reported campaign consisted of three system deployments spanning four months. The robotic system consisted of two subsystems—NAMOS (networked aquatic microbial observing systems) comprised of a robotic boat and static buoys, and NIMS-RD (rapidly deployable networked infomechanical systems) comprised of an infrastructure-supported tethered robotic system capable of high-resolution sampling in a two-dimensional cross section (vertical plane) of the lake. The multidisciplinary human team consisted of 25 investigators from robotics, computer science, engineering, biology, and statistics.We describe the lake profiling campaign requirements, the robotic systems assisted by a human team to perform high fidelity sampling, and the sensing devices used during the campaign to observe several environmental parameters. We discuss measures taken to ensure system robustness and quality of the collected data. Finally, we present an analysis of the data collected by iteratively adapting our experiment design to the observations in the sampled environment. We conclude with the plans for future deployments.

Using a new data set, we estimate the magnitude of the incumbency advantage in direct primary elections between 1912 and 2005. We find that the incumbency advantage, as estimated by the sophomore surge, was above 4 percentage points in primary elections even in the first decades of the twentieth century. The sophomore surge in primary elections grew to approximately 14 percentage points by the end of 1990s. The growth of the sophomore surge in primary elections occurred at least a decade prior to the growth of the sophomore surge in the general elections. We find some evidence that the structure of intra-party competition may affect the incumbency advantage. Specifically, examining southern and border states, we find that the sophomore surge was significantly smaller in states with persistent intra-party factions.

Harvesting the benefits of a sensor-rich world presents many data management challenges. Recent advances in research and industry aim to address these challenges. With the rapidly increasing number of large-scale sensor network deployments, the vision of a worldwide sensor Web is close to becoming a reality.

INTRODUCTION The Patient-Reported Outcomes Measurement Information System (PROMIS) Smoking Initiative has developed item banks for assessing six smoking behaviors and biopsychosocial correlates of smoking among adult cigarette smokers. The goal of this study is to evaluate the performance of the Spanish version of the PROMIS smoking item banks as compared to the original banks developed in English. METHODS The six PROMIS banks for daily smokers were translated into Spanish and administered to a sample of Spanish-speaking adult daily smokers in the United States (N = 302). We first evaluated the unidimensionality of each bank using confirmatory factor analysis. We then conducted a two-group item response theory calibration, including an item response theory-based Differential Item Functioning (DIF) analysis by language of administration (Spanish vs. English). Finally, we generated full bank and short form scores for the translated banks and evaluated their psychometric performance. RESULTS Unidimensionality of the Spanish smoking item banks was supported by confirmatory factor analysis results. Out of a total of 109 items that were evaluated for language DIF, seven items in three of the six banks were identified as having levels of DIF that exceeded an established criterion. The psychometric performance of the Spanish daily smoker banks is largely comparable to that of the English versions. CONCLUSIONS The Spanish PROMIS smoking item banks are highly similar, but not entirely equivalent, to the original English versions. The parameters from these two-group calibrations can be used to generate comparable bank scores across the two language versions. IMPLICATIONS In this study, we developed a Spanish version of the PROMIS smoking toolkit, which was originally designed and developed for English speakers. With the growing Spanish-speaking population, it is important to make the toolkit more accessible by translating the items and calibrating the Spanish version to be comparable with English-language scores. This study provided the translated item banks and short forms, comparable unbiased scores for Spanish speakers and evaluations of the psychometric properties of the new Spanish toolkit.

Airlines and Air Navigation Service Providers are united in their goal to reduce fuel consumption. While changes to flight operations and technology investments are the focus of a number of studies, our study is among the first to investigate an untapped source of aviation fuel consumption: excess contingency fuel loading. Given the downside risk of fuel exhaustion of diverting to an alternate airport, airline dispatchers may load excess fuel onto an aircraft. Such conservatism comes at a cost of consuming excess fuel, as fuel consumed is a function of, among other factors, aircraft weight. The aim of this paper is to quantify, on a per-flight basis, the fuel burned due to carrying fuel beyond what is needed for foreseeable contingencies, and thereby motivate research, federal guidance, and investments that allow airline dispatchers to reduce fuel uplift while maintaining near zero risks of fuel exhaustion. We merge large publicly available aviation and weather databases with a detailed dataset from a major US airline. Upon estimating factors that capture the quantity fuel consumed due to carrying a pound of weight for a range of aircraft types, we calculate the cost and greenhouse gas emissions from carrying unused fuel on arrival and additional contingency fuel above a conservative buffer for foreseeable contingencies. We establish that the major US carrier does indeed load fuel conservatively. We find that 4.48% of the fuel consumed by an average flight is due to carrying unused fuel and 1.04% of the fuel consumed by an average flight is due to carrying additional contingency fuel above a reasonable buffer. We find that simple changes in flight dispatching that maintain a statistically minimal risk of fuel exhaustion could result in yearly savings of 338 million lbs of CO2, the equivalent to the fuel consumed from 4760 flights on midsized commercial aircraft. Moreover, policy changes regarding maximum fuel loads or investments that reduce uncertainty or increase the ability to plan flights under uncertainty could yield far greater benefits.

Four hurricanes battered the state of Florida during 2004, the most affecting any state since Texas endured four in 1884. Each of the storms changed the coast differently. Average shoreline change within the right front quadrant of hurricane force winds varied from 1 m of shoreline advance to 20 m of retreat, whereas average sand volume change varied from 11 to 66 m3 m−1 of net loss (erosion). These changes did not scale simply with hurricane intensity as described by the Saffir-Simpson Hurricane Scale. The strongest storm of the season, category 4 Hurricane Charley, had the least shoreline retreat. This was likely because of other factors like the storm's rapid forward speed and small size that generated a lower storm surge than expected. Two of the storms, Hurricanes Frances and Jeanne, affected nearly the same area on the Florida east coast just 3 wk apart. The first storm, Frances, although weaker than the second, caused greater shoreline retreat and sand volume erosion. As a consequence, Hurricane Frances may have stripped away protective beach and exposed dunes to direct wave attack during Jeanne, although there was significant dune erosion during both storms. The maximum shoreline change for all four hurricanes occurred during Ivan on the coasts of eastern Alabama and the Florida Panhandle. The net volume change across a barrier island within the Ivan impact zone approached zero because of massive overwash that approximately balanced erosion of the beach. These data from the 2004 hurricane season will prove useful in developing new ways to scale and predict coastal-change effects during hurricanes.

In this paper, we build an aggregate demand model for air passenger traffic in a hub-and-spoke network. This model considers the roles of airline service variables such as service frequency, aircraft size, ticket price, flight distance, and number of spokes in the network. It also takes into account the influence of local passengers and social-economic and demographic conditions in the spoke and hub metropolitan areas. The hub airport capacity, which has a significant impact on service quality in the hub airport and in the whole hub-and-spoke network, is also taken into consideration. Our demand model reveals that airlines can attract more connecting passengers in a hub-and-spoke network by increasing service frequency than by increasing aircraft size in the same percentage. Our research confirms the importance of local service to connecting passengers, and finds that, interestingly, airlines’ services in the first flight leg are more important to attract passengers than those in the second flight segment. Based on data in this study, we also find that a 1% reduction of ticket price will bring about 0.9% more connecting passengers, and a 1% increase of airport acceptance rate can bring about 0.35% more connecting passengers in the network, with all else equal. These findings are helpful for airlines to understand the effects of changing their services, and also useful for us to quantify the benefits of hub airport expansion projects. At the end of this paper, we give an example as an application to demonstrate how the developed demand model could be used to valuate passengers’ direct benefit from airport capacity expansion.

Multivariate statistical analysis is used to estimate the impacts of a major capacity expansion at Dallas-Fort Worth International Airport. The model relates the Daily Flight Time Index (DFTI) to demand, weather, origin airport congestion, and the expansion itself. The effect of the capacity expansion on DFTI is found to depend strongly on visibility. On average, the index in the post-expansion period is 1.3 min less as a consequence of investment. This change includes a larger reduction in departure delay that is offset by an increase in taxi time. Moreover, the reduction caused by the expansion has been more than offset by increases in the DFTI resulting from other factors, notably increased demand and worse weather.

Simple visible‐light digital cameras offer a potential for expanded forms of plant ecological research. The moss Tortula princeps undergoes changes in reflected visible light during cycles of drying and hydrating in the field, and the MossCam project has collected digital images of T. princeps at least daily since 2003. Laboratory studies can be used to calibrate these images to indicate field physiological conditions. Drying the moss 6 d in the laboratory resulted in a decrease of net CO2 uptake to near 0; recovery after rewetting occurred within 10 min. The difference in reflectance between hydrated and dry T. princeps was maximal ca. 550 nm, and maximal net CO2 uptake was linearly related to the green:red ratio of laboratory images when net CO2 uptake was positive. Using the green:red ratio of field images and otherwise assuming ideal conditions, the total carbon gain for a 6‐d period around a 1.3‐mm rain event was ca. 208 mmol CO2 m−2, equivalent to 69 d of respiration under dry conditions. Using a vi...

Recent studies of the single-airport ground-holding problem use static or dynamic optimization to manage uncertainty about future airport capacities. Scenario trees of airport capacity profiles provide the basis for formulating multistage recourse problems. In this paper, methodologies are presented for generating scenario trees from empirical data, and the performance of scenario-based models is examined with the scenario trees. Most U.S. airports have capacity profiles that can be classified into some nominal scenarios, and for many airports, these scenarios can be naturally combined into scenario trees. The delay costs yielded from using dynamic optimization are consistently and considerably lower than from static optimization. The results illustrate the benefit of the wait-and-see strategy in a real-world setting and suggest the need for further research on implementing scenario-based dynamic strategies.

An econometric model of average daily delay is formulated and estimated to analyze flight delay in the U.S. domestic system. The model considers the effects of arrival queuing, volume, terminal weather, en route weather, seasonal effects, and secular effects. In particular, the time-of-day effects of arrival queuing, the effects of scheduled arrivals, and the interaction between scheduled arrivals and weather conditions are investigated. The estimation results suggest that ( a) queuing has a greater delay impact in the morning than in the afternoon or evening (one unit of morning queuing delay causes about three times as much average daily delay as one unit of evening queuing delay), ( b) scheduled arrivals–-both alone and in interaction with weather conditions–-significantly affect average delay, and ( c) 31% of the total delay increase between early 2004 and early 2005 can be attributed to traffic growth.

This paper explores the impact of unscheduled navigational and surveillance equipment outages on airport performance during visual flight rules and instrument flight rules at San Francisco International Airport and Phoenix Sky Harbor International Airport. The following most common unscheduled short outages, which occurred during January 2000-December 2002, are analyzed in detail: very high frequency omnidirectional range (VOR), approach lighting system type 2 (ALSF-2), the secondary radar Mode S, and air traffic control radio beacon system (ATCRBS). We explore the air traffic control procedures and responses to unscheduled outages, and develop a methodology to examine the effects of unscheduled outages on airport performance. Two Federal Aviation Administration databases, maintenance management system and aviation system performance metrics, are used to construct censored regression models (i.e., Tobit models) to assess the airport throughput performance during such unscheduled outages. It is found that airport arrival and departure throughputs do not deteriorate with VOR and ALSF-2 outages due to availability of air traffic procedures that allow alternative approaches into the airport. However, the unscheduled outages of secondary radar Mode S and ATCRBS do cause airport throughput degradations.

We build a nested logit model to study the roles of aircraft size, together with service frequency, seat availability and fare, in airlines’ market share and total demand in non-stop duopoly markets. We find that airlines can obtain higher returns in market share from increasing service frequency than from increasing aircraft size, and our study confirms an S -curve effect of service frequency on airlines’ market share. We find that the available capacity per flight––net of capacity absorbed by connecting passengers––affects market share in the same manner whether it is derived from a larger proportion of a smaller aircraft or smaller proportion of a larger one.

PurposeRituximab is an important therapeutic for Waldenström’s macroglobulinemia (WM). Polymorphisms in FcγRIIIA (CD16) receptor expression modulate human immunoglobulin G1 binding and antibody-dependent cell-mediated cytotoxicity, and may therefore influence responses to rituximab.Patients and MethodsSequence analysis of the entire coding region of FcγRIIIA was undertaken in 58 patients with WM whose outcomes after rituximab were known.ResultsVariations in five codons of FcγRIIIA were identified. Two were commonly observed (FcγRIIIA-48 and FcγRIIIA-158) and predicted for amino acid polymorphisms at FcγRIIIA-48: leucine/leucine (L/L), leucine/arginine (L/R), and leucine/histidine (L/H). Polymorphisms at FcγRIIIA-158 were phenylalanine/phenylalanine (F/F), phenylalanine/valine (F/V), and valine/valine (V/V). A clear linkage between these polymorphisms was detected and all patients with FcγRIIIA-158F/F were always FcγRIIIA-48L/L, and patients with either FcγRIIIA-L/R or -L/H always expressed at least one valine at FcγRIIIA-158 (P ≤ .001). The response trend was higher for patients with FcγRIIIA-48L/H (38.5%) versus -48L/R (25.0%) and LL (22.0%), and was significantly higher for patients with FcγRIIIA-158V/V (40.0%) and -V/F (35%) versus -158F/F (9.0%; P = .030). Responses for patients with FcγRIIIA-48L/L were higher when at least one valine was present at FcγRIIIA-158 (P = .057), thereby supporting a primary role for FcγRIIIA-158 polymorphisms in predicting rituximab responses. With a median follow-up of 13 months, no significant differences in the median time to progression and progression-free survival were observed when patients were grouped according to their FcγRIIIA-48 and -158 polymorphisms.ConclusionThe results of these studies therefore support a predictive role for FcγRIIIA-158 polymorphisms and responses to rituximab in WM.

The objective of this paper is to present the findings and a set of hypotheses that emerged in the initial steps of an assessment study of air traffic controllers’ adoption and adaptation of new technologies, with the user request evaluation tool (URET) as a case study. The hypotheses are the basis for further study on this topic. The importance of this investigation is to provide a better understanding of changes brought about by the use of decision support tools by sector controller teams. The main purpose of URET is to support sector team strategic planning and allow controllers to concentrate on more user-beneficial control actions. Actual improvements depend on the way controllers use the automation tools in their work. Three aspects were noted about URET usage: ( a) different sector teams use it in different ways, ( b) in many instances URET usage differs from what was intended, and ( c) usage varies across centers. Subject matter experts were interviewed to explore how controllers have adopted and adapted URET across the mentioned variations. The goal of this research is to draw lessons from the experience with URET that can inform technology deployments in the future.

Genetic Analysis Workshop 14 (GAW14) was held September 7–10, 2005, in Noordwijkerhout, The Netherlands. The overarching theme was the comparison of microsatellite and single-nucleotide polymorphism (SNP) markers for genome-wide scans, and the statistical methods that can best exploit the information provided in such scans for linkage and association studies. The 183 contributions submitted to GAW14 were organized into 18 presentation groups of 7–15 papers each. GAW14 participants had the choice of two data sets to analyze. COGA generously donated extensive family data on alcoholism, related phenotypes, pertinent covariates, and a set of previously analyzed genomescan microsatellite marker genotypes. The simulated data were designed to have similarities to the real data set. Extensive new SNP genotyping was performed on DNA provided by COGA for the previously genotyped families. Illumina, Affymetrix, and the Center for Inherited Disease Research performed this work and donated these data to GAW14 and to COGA. The group summary papers collected in this issue present the major findings from GAW14. Genet. Epidemiol. 29(Suppl. 1):S1–S6, 2005. Published 2005 Wiley-Liss, Inc.

FAA regulates the safety of the aviation industry through the safety oversight system, which is a system of rulemaking, standard-setting, certification, accident investigation, rule enforcement, and surveillance activities. Federal programs, including those of FAA, use performance indicators to measure the achievement of program goals. As part of a broader program of developing risk management methodologies, FAA is researching performance indicators that can be used to measure the performance of the safety oversight system. One of its goals is to create performance indicators that can describe the safety oversight system's influence on safety outcomes such as fatalities. Creating performance measures that link activities to safety outcomes is challenging because it is difficult to establish the causation between oversight activities and these safety outcomes. This challenge is not unique to FAA, and external reviewers such as the Government Accountability Office have recommended that other high-reliability sectors, including rail, develop such indicators. In addition to safety outcomes, other aspects of safety oversight system performance can be described with meaningful metrics. The background and motivation for oversight evaluation in the aviation industry and in general are discussed, as well as the challenges, some generic and some unique, of evaluating aviation safety oversight activities. Research is also presented on how safety oversight evaluation is conducted outside aviation.

The current demand management policy at LaGuardia Airport (LGA) New York, must be changed in 2007 under the provision of the Wendell H. Ford Aviation Investment and Reform Act for the 21st Century of April 2000 (AIR-21). As a preliminary step for developing a new policy, this study considered how past policies, along with other factors, have affected operational performance at LGA. The interaction between LGA and the rest of the aviation system was also investigated by estimating simultaneous equations of average delay for LGA and the National Airspace System (NAS) by using two-stage least squares. The results demonstrate that the arrival delay impact of AIR-21 on LGA was in the form of Increased Ground Delay Program holding and that although delay increased markedly under AIR-21, there were also observable improvements in the ability of LGA to handle traffic. Furthermore, on the basis of the simultaneous equations analysis, it was found that 1 min of arrival delay at LGA causes about 2 min of delay elsewhere in the NAS, suggesting that demand management at LGA is a national rather than a local issue.

The recent increase in flight delays in the U.S. domestic system is analyzed by estimating an econometric model of average daily delay that incorporates the effects of arrival queuing, convective weather, terminal weather conditions, seasonal effects, and secular effects (trends in delays not accounted for by other variables). From the estimation results it was possible to quantify some sources of higher delays in late 2003 and early 2004 and track changes in delays that are not attributable to major causal factors. Results suggest that when these factors are controlled for, delays decreased steadily from 2000 through early 2003, but that the trend reversed thereafter. Of the total delay increase between early 2003 and early 2004, half to two-thirds can be attributed to specific sources.

Passenger flow is an important planning factor in an air transportation system. However, forecasting segment (link) and airport flows becomes more complicated in a hub-and-spoke system since segment flows are the aggregations of route flows, and the number of routes increases with hubbing activities. This research develops an equilibrium model considering certain important characteristics of an air transportation system such as distance, airport delay, airline competition, and networks to predict segment and airport passenger flows from the viewpoint of the whole system. The major features of the model include ( a) treatment of segment flows and airport delays as endogenous by considering the feedback of assigned segment flows and their impacts on airports; ( b) reflecting the flexibility of air networks, a start with all links between all airports as the potential network and determination of the predicted network according to the equilibrium flows on segments; and ( c) connection of key elements of the system so that it can evaluate the system impacts of some element changes. The model is demonstrated by applying it to the National Airspace System of the United States. Several characteristics of the model are also investigated. In addition, a policy experiment shows that improvement of an airport not only affects the airport itself but also changes the flows and performance of other airports–-the model can be a tool for evaluating systemwide effects. Finally, the model's limitations and possible remedies are discussed.

We have developed a highly informative set of single-nucleotide polymorphism (SNP) assays designed for linkage mapping of the human genome. These assays were developed on a robust multiplexed assay system to provide a combination of very high accuracy and data completeness with high throughput for linkage studies. The linkage panel is comprised of approximately 4,700 SNPs with 0.39 average minor allele frequency and 624-kb average spacing. Based on almost 2 million genotypes, data quality was shown to be extremely high, with a 99.94% call rate, >99.99% reproducibility and 99.995% genotypes consistent with mendelian inheritance. We constructed a genetic map with an average 1.5-cM resolution using series of 28 CEPH pedigrees. The relative information content of this panel was higher than those of commonly used STR marker panels. The potent combination of this SNP linkage panel with the multiplexed assay system provides a previously unattainable level of performance for linkage studies.

New statistical methods for assessing airport capacity and delay, especially during rare events and after infrastructure upgrades, are developed and demonstrated in this article. Models of airport throughput are estimated with the new methods and the developed models are checked against the opening of a new runway in Detroit. Simulated delays match actual delays effectively, though the articles states limits for the model. The author suggests introducing autocorrelation into censored regression models to compensate for model limits. More generally, the author's study allows the Federal Aviation Administration (FAA) to control for changes in demand and weather that would otherwise confound before-and-after, with/without studies of host factors that affect NAS performance.

The throughput effect of Traffic Management Advisor (TMA) metering for Los Angeles International Airport was estimated with censored regression. Under TMA metering, traffic management coordinators receive advisories about when individual flights should be scheduled to enter the terminal area, accounting for the unimpeded time and constraints related to separation requirements and capacity constraints. Tests of TMA metering at Los Angeles began in spring 2002; mandatory use during the morning peak period started in November 2002. This analysis focuses on observed counts during periods when metering is and is not in effect and takes into account other relevant factors such as weather, visibility, and demand. Demand is used as a censoring variable that places an upper limit on the observed count. A significant increase in achievable arrival throughput under instrument conditions was found in the morning peak period, but a significant decrease was observed under visual conditions. These results are consistent with field reports, which suggest that under visual meteorological conditions, TMA was assigning unnecessary metering delays. The success of the censored regression methodology in capturing these effects suggests that it would be useful for various other applications in which the effect of some event on airport capacity must be ascertained.

This article considers models that describe how people browse the Web. We restrict our attention to navigation patterns within a single site, and base our study on standard Web server access logs. Given a visitor's previous activities on the site, we propose models that predict their next page request. If the prediction is reasonably accurate, we might consider “prefetching” the page before the visitor requests it. A more conservative use for such predictions would be to simply update the freshness records in a proxy or network cache, eliminating unnecessary If-Modified-Since requests. Using data from the Web site for the Computing and Mathematical Sciences Research Division of Lucent Technologies (cm.bell-labs.com) we first evaluate the predictive performance of low-order Markov models. We next consider mixtures of first-order Markov models, achieving a kind of clustering of Web pages in the site. This approach is shown to perform well, while significantly reducing the space required to store the model. ...

Explored are the benefits of integrating User Request Evaluation Tool (URET) and Controller-Pilot Data Link Communications (CPDLC). Controller-pilot voice-communication messages and aircraft traffic flows and conflicts are analyzed in great detail in one representative, URET-operating en route sector. On the basis of the mapped URET data and the real-world communication messages, a base case and two alternative scenarios were analyzed to estimate the number of clearances that are given to pilots to resolve aircraft conflicts a sufficient time before the start of the conflict, and to determine the reduction in frequency congestion possible if such messages were sent via data link. It was found that the highest frequency use, which corresponded to the first traffic peak, was reduced 27% after the second-scenario messages were removed from the base-case scenario. After removing the non-time-critical conflict-resolution messages, the total reduction was 59%. Frequency use during the highest number of aircraft conflicts was reduced 65% after all messages from the second and the third scenario were removed. Thus, the benefits of integrating CPDLC and URET are significant. If non-time-critical conflict messages were transmitted via data link in the integrated CPDLC and URET environment, they could considerably improve the frequency congestion. More important, the largest benefits would be experienced in situations involving a large number of aircraft conflicts, or during busy periods of traffic. These improvements could further help to reduce the number of communication errors (and the consequent air traffic control workload), as well as the number of operational errors.

Rabies is a highly fatal, viral, zoonotic disease caused by a Lyssa virus. It is acquired through the bite of an infected animal, mostly dogs. Estimated annual global human mortalities from rabies is 61,000, over 99% of which are from developing countries where about US$583.5 million is spent on its control. Rabies is enzootic in Ghana. Vaccinating about 70% of the dog population leads to a reduction in rabies transmission to humans; however, percentage dog anti-rabies vaccination coverage in Ghana is unknown. This study therefore investigated the magnitude of rabies in dogs and humans in the Greater-Accra region, and assessed annual percentage dog anti-rabies vaccination coverage from 2007-2011. Secondary data on rabies vaccination, post mortem and dog quarantine records for all ten districts in the region, and human rabies records were analysed. Means and percentages were calculated, graphs drawn and trends analysed. The number of animal samples which tested positive out of 309, was 283. Predictive value positive was 91.6%. Of the positive cases, 97.5% (276/283) had no previous vaccination history, and 96.1% (272/283) were from dogs. Fifty-five out of 174 (31.6%) samples were from dogs which bit more than one person. Human exposures to dog and other animal bites are not differentiated. Average annual number of outbreaks was 31, whereas percentage dog vaccination ranged from 10.26-17.56. Current annual percentage dog anti-rabies vaccination coverage is very low, whereas the incidence of dog rabies in the region is high. The number of humans affected may be underestimated. Government should immediately facilitate annual mass vaccination of pets.

The present paper focuses on the crisis management following the Asiana Crash at San Francisco Internation Airport in July 2013. The crash led to a large number of domestic and international flight diversions to many airports, such as Oakland, San Jose, Los Angeles, but also Denver, Seattle, Calgary, for instance. Thousands of passengers found themselves struggling to reach their original destination. Passenger reaccommodation varied greatly from airline to airline and airport to airport. The contributions of this paper are twofold. First a passenger-centric reaccommodation scheme is developed to balance costs and delays, for each diversion airport. Second, assuming better information sharing and collaborative decision making, we show that there was enough capacity at the neighboring airports, Oakland and San Jose, to accommodate most of the diverted flights and reoptimize the allocation of flight diversions to the Bay Area airports.

Regular scoring of a dairy herd in terms of various physical metrics such as Body Condition Score (BCS), mobility and weight are essential for maintaining high animal welfare. This paper presents preliminary results of an automated system capable of nonintrusively measuring BCS automatically as the cow walks uninhibited beneath a 3D camera. The system uses a ’rolling ball’ algorithm on the depth map which simulates how well a ball of a set radius fits the surface. In this way a measure of angularity is generated which is shown to be inversely related to BCS on 95 cows. The measurements are shown to be highly repeatable with 14 out of 15 cows being scored within one quarter BCS score repeatedly and seven of those being scored within an eighth of a BCS score.

This paper describes a computing environment called S-wafers that is tailored for the analysis of spatial data collected during semiconductor manufacturing processes. At the core of S-wafers lies a new statistical methodology that systematically exploits the basic spatial nature of these data. The S-wafers environment builds on the experience of Lucent Technologies' Microelectronics engineers and Bell Labs researchers who have noticed that patterns in mapped wafer data can provide “signatures,” which can be used to help identify and correct process problems. The S-wafers environment provides the means to formalize these observations into implementable strategies by furnishing extensive tools for data visualization; identification of groups of similarly patterned wafers; spatial analysis of designed experiments; assessment of the impact of particle contamination; and much more. In addition to supporting statistical research into problems of process improvement in this area, the S-wafers environment has been used for more than two years by various groups in Microelectronics. Extensions to both the software environment and the underlying statistical methodology continue at a rapid pace.

Searching the Web on a mobile device such as a cell phone poses unique problems for the user that cannot be easily overcome through the interface. Given the restricted display of current wireless devices, users cannot efficiently examine search results when they are presented as a long list. In our system, Hyponym, we organize search results into topics and allow the user to explore relevant resources within each topic. The data to support this kind of analysis are drawn from sequences of Web pages that users have visited while searching. We have found that queries that lead users to request similar pages tend to be topically related. From this simple observation, we form clusters or groups of queries that are used to structure the search display. Hyponym can be thought of as a collaborative filtering application that takes as its input navigation data from previous Web-searching tasks. Because of this, the lists that we return within each topic or query group tend to be much more accurate than those recommended by standard search engines. In fact, Hyponym can significantly cut the number of pages a user visits while searching the Web. We are currently extending the Hyponym framework to support personalization and location-specific information.3

We analyze runway delay externalities at Los Angeles International Airport (LAX) using a deterministic queuing model. The model allows us to estimate the delay impact of each specific arriving flight on each other specific arriving flight. We find that, despite being only moderately congested (average queuing delay only 4 min per arriving flight), individual flights can generate as much as 3 aircraft-hours of external delay impact on other flights, with an average impact of 26 aircraft-minutes and 3400 seat-minutes. About 90 percent of this impact is external to the airline as well as the flight, a consequence of the lack of a dominant airline at LAX. We then compare the delay impact of each individual flight to its contribution to schedule convenience by determining the amount of “schedule delay” that would result if the flight were eliminated and its passengers forced to use the previous flight flown by the same airline from the same origin. We find that a number of commuter flights serving high density, short-haul segments generate much more queuing delay than they save in schedule delay, with the ratio exceeding 10 in several cases. We argue that social welfare would increase if such flights were eliminated, upsizing others as necessary to accommodate the displaced loads.

Free Flight Phase 1 (FFP1) is an FAA program for improving the performance of the National Airspace System (NAS) through the deployment of advanced technologies for air traffic management. In addition to the deployment activities, FFP1 includes a significant evaluation component, which faces a significant hurdle. A plethora of factors—weather, demand, enhancements to the NAS infrastructure not related to FFP1, facility outages, and so on—may also cause changes in NAS performance. It is necessary to normalize for these factors in order to determine the effect of FFP1. Normalization procedures to isolate the impact of the implementation of an FFP1 technology—the Terminal Area Traffic Management Advisor (T-TMA)—are documented at the Southern California TRACON, where it is used for controlling traffic into Los Angeles International Airport. Two examples of normalization are presented. One examines the effect of T-TMA on airport arrival capacity, and the other looks at arrival delay. The results, although preliminary given the short time since implementation, are consistent: it appears that capacities have increased and delays decreased as a result of the deployment of the tool. Moreover, the magnitudes of the delay reductions and capacity increases are consistent.

INTRODUCTION Smoking behavior is influenced by social motivations such as the expected social benefits of smoking and the social cues that induce craving. This paper describes development of the PROMIS Social Motivations for Smoking item banks, which will serve to standardize assessment of these social motivations among daily and nondaily smokers. METHODS Daily (N = 4,201) and nondaily (N =1,183) smokers completed an online survey. Item factor analyses, item response theory analyses, and differential item functioning analyses were conducted to identify a unidimensional set of items for each group. Short forms (SFs) and computer adaptive tests (CATs) were evaluated as tools for more efficiently assessing this construct. RESULTS A total of 15 items were included in the item banks (9 items common to daily and nondaily smokers, 3 unique to daily, 3 unique to nondaily). Scores based on full item banks are highly reliable (reliability = 0.90-0.91). Additionally, the item banks are strongly unidimensional and perform similarly across gender, age, and race/ethnicity groups. A fixed SF for use with both daily and nondaily smokers consists of 4 items (reliability = 0.80). Results from simulated CATs showed that, on average, fewer than 5 items are needed to assess this construct with adequate precision using the item banks. CONCLUSIONS A new set of items has been identified for assessing the social motivations for smoking in a reliable, standardized manner for daily and nondaily smokers. In addition to using the full item banks, efficient assessment can be achieved by using SFs, employing CATs, or selecting items tailored to specific research or clinical purposes.

Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full-information test statistics such as Pearson's X2 and the likelihood ratio statistic G2 suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited-information fit statistics such as Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M2 have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu-Olivares and Joe's (2006, Psychometrika, 71, 713) M2 statistic to diagnostic classification models. Through a series of simulation studies, we found that M2 is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q-matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M2 was largely insensitive to misspecifications in the distribution of higher-order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M2 , we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic XLD2 for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The XLD2 statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful in pinpointing the sources of misfit. Patterns of local dependence arising due to specific model misspecifications are illustrated. Finally, we used the M2 and XLD2 statistics to evaluate a diagnostic model fit to data from the Trends in Mathematics and Science Study, drawing upon analyses previously conducted by Lee et al., (2011, IJT, 11, 144).

This article reviews the principle of minimum description length (MDL) for problems of model selection. By viewing statistical modeling as a means of generating descriptions of observed data, the MDL framework discriminates between competing models based on the complexity of each description. This approach began with Kolmogorov's theory of algorithmic complexity, matured in the literature on information theory, and has recently received renewed attention within the statistics community. Here we review both the practical and the theoretical aspects of MDL as a tool for model selection, emphasizing the rich connections between information theory and statistics. At the boundary between these two disciplines we find many interesting interpretations of popular frequentist and Bayesian procedures. As we show, MDL provides an objective umbrella under which rather disparate approaches to statistical modeling can coexist and be compared. We illustrate the MDL principle by considering problems in regression, nonpar...

The relationship between the performance of the US National Airspace System (NAS) and airline costs is examined by estimating airline cost functions that include NAS performance metrics as arguments, using quarterly data for 10 US domestic airlines. Performance metrics that vary by airline and quarter are developed by applying principal component analysis to seven underlying variables, including average delay, delay variance, and the proportion of flights that is cancelled. This analysis reveals that variation in the seven variables can be adequately captured by three or fewer factors, which we term NAS performance factors. If three factors are used, they can be interpretted as “delay”, “variability”, and “disruption”, the latter two of which are merged into a single “irregularity” factor in the two-factor model. Cost function estimation results confirm the anticipated link between NAS performance and airline cost. In the cost models with two and three performance factors, the irregularity and disruption factors are found to have the strongest cost impacts. These results challenge the prevailing assumption that delay reduction is the most important benefit from NAS enhancements. Using the estimated cost models, we predict airline cost savings from substantially improved NAS performance in the range $1–4 billion annually.

The paper describes a scientific experiment about a contentious policy issue: What costs and disruptions might arise if U.S. domestic airlines adopted positive passenger bag-match (PPBM), an antiterrorist measure aimed at preventing baggage unaccompanied by passengers from traveling in aircraft luggage compartments? The heart of the effort was a two-week live test of domestic bag-match that involved 11 airlines, 8,000 flights, and nearly 750,000 passengers. Working with the Federal Aviation Administration, the authors played a major role in designing, monitoring, and analyzing the live test. However, the live test provided "raw materials" for an assessment of PPBM rather than the assessment itself. As we discuss, there are difficulties in extrapolating from a short experiment involving 4% of domestic flights to the steady-state consequences of systemwide bag-match.Our findings challenge the widely held industry view that PPBM would have grave impacts on domestic operations. We ultimately estimated that, under usual operating conditions, PPBM would delay domestic departures by an average of approximately 1 minute per flight. (Approximately one-seventh of flights would suffer bag-match departure delays, which would average about 7 minutes apiece.) Implementing bag-match would cost the airlines roughly 40 cents per passenger enplanement, and would require virtually no reduction in the number of flights performed. Restricting bag-match to 5% of passengers chosen under a security profile would cut these delays by about 75% and these dollar costs by about 50%.

It has been common for airport traffic forecasts to assume a continuing increase in average aircraft size in the future so that the anticipated growth in passenger demand will not result in a proportional increase in aircraft operations. However, to understand the likely future trends in average aircraft size, as well as strategies that an airport might pursue to encourage airlines to use larger equipment, it is necessary to understand the competitive dynamics of the various markets served by the airport and the factors that determine the size of equipment that airlines will use in those markets. Recent trends in average aircraft size at a major U.S. West Coast airport and the influence of market characteristics on the size of aircraft used in different markets are examined. The changes in the past decade in selected short- and medium-haul markets are analyzed, and the results are presented of a cross-sectional model that estimates the influence of various market characteristics, including air traffic delay levels, on the average size of aircraft deployed in a wide variety of markets throughout the United States. The prospects for airport capacity constraints to influence airlines to make use of larger aircraft are discussed, and the implications for airport strategies to encourage the use of larger aircraft are examined.

Statistical concepts and methods have played a critical role in speeding the pace of industrial development over the last century. In return, industrial applications have provided statisticians with incredible opportunities for methodological research. The richness and variety of these applications have had a major influence on the development of statistics as a discipline; consider, for example, the extensive research in statistical process control (SPC) and changepoint detection, dating back to the pioneering work of Shewhart in the 1920s, and developments in automatic process control, design of experiments, sequential analysis, reliability, and so on. Recent efforts by manufacturers to adopt sustained quality and productivity improvement programs have generated a renewed interest in and appreciation for statistics in industry. In fact, fundamental statistical concepts such as understanding and managing variation form the backbone of popular quality management paradigms and practices. Many of the traditional SPC concepts and techniques grew in response to the manufacturing environments prevalent several decades ago. Current advanced manufacturing and high-technology industries, however, operate under a much more complex and diverse set of conditions. These changes have important implications for research directions in industrial statistics, not only in terms of identifying new problems and developing new methods, but also in reevaluating the paradigms that inspired earlier approaches. In this vignette we use applications from automotive and semiconductor manufacturing to illustrate various issues and to discuss future research needs and directions. The discussion is limited to a few selected topics and is inevitably slanted toward our own experiences.

The manner in which changes in the performance of the U.S. National Airspace System (NAS) affect carrier costs is examined. The methodology includes estimation of airline cost functions that contain NAS performance metrics as arguments, using quarterly data for 10 U.S. domestic airlines. The primary interest is in the impact of delay on cost performance, and performance metrics that vary by airline and quarter are developed. The potentially large number of metrics are reduced by applying factor analysis to seven underlying variables, including average delay, delay variance, and the proportion of flights that are cancelled. The analysis reveals that variations in the seven variables can be adequately captured by three or fewer factors. The three factors used correspond to “delay,” “variability,” and “disruption,” the last two of which are merged into a single “irregularity” factor in the two-factor model. When used as arguments in an airline cost function, the “disruption” factor is found to be a significant contributor to airline costs in the three-factor model, as is the “irregularity” factor in the two-factor model. No significant effect is found for the delay factor in the multifactor models. These results challenge the prevailing assumption that delay reduction is the most important benefit from investments in NAS capital and operations rules. The carrier cost savings that would result from improved NAS performance levels are estimated, and these are compared with previously published estimates.