Coverage, Matching, and Beyond: New Results on Budgeted Mechanism Design

We study a type of reverse (procurement) auction problems in the presence of budget constraints. The general algorithmic problem is to purchase a set of resources, which come at a cost, so as not to exceed a given budget and at the same time maximize a given valuation function. This framework captures the budgeted version of several well known optimization problems, and when the resources are owned by strategic agents the goal is to design truthful and budget feasible mechanisms, i.e. elicit the true cost of the resources and ensure the payments of the mechanism do not exceed the budget. Budget feasibility introduces more challenges in mechanism design, and we study instantiations of this problem for certain classes of submodular and XOS valuation functions. We first obtain mechanisms with an improved approximation ratio for weighted coverage valuations, a special class of submodular functions that has already attracted attention in previous works. We then provide a general scheme for designing randomized and deterministic polynomial time mechanisms for a class of XOS problems. This class contains problems whose feasible set forms an independence system (a more general structure than matroids), and some representative problems include, among others, finding maximum weighted matchings, maximum weighted matroid members, and maximum weighted 3D-matchings. For most of these problems, only randomized mechanisms with very high approximation ratios were known prior to our results

On Budget-Feasible Mechanism Design for Symmetric Submodular Objectives

We study a class of procurement auctions with a budget constraint, where an auctioneer is interested in buying resources or services from a set of agents. Ideally, the auctioneer would like to select a subset of the resources so as to maximize his valuation function, without exceeding a given budget. As the resources are owned by strategic agents however, our overall goal is to design mechanisms that are truthful, budget-feasible, and obtain a good approximation to the optimal value. Budget-feasibility creates additional challenges, making several approaches inapplicable in this setting. Previous results on budget-feasible mechanisms have considered mostly monotone valuation functions. In this work, we mainly focus on symmetric submodular valuations, a prominent class of non-monotone submodular functions that includes cut functions. We begin first with a purely algorithmic result, obtaining a $\frac{2e}{e-1}$-approximation for maximizing symmetric submodular functions under a budget constraint. We view this as a standalone result of independent interest, as it is the best known factor achieved by a deterministic algorithm. We then proceed to propose truthful, budget feasible mechanisms (both deterministic and randomized), paying particular attention on the Budgeted Max Cut problem. Our results significantly improve the known approximation ratios for these objectives, while establishing polynomial running time for cases where only exponential mechanisms were known. At the heart of our approach lies an appropriate combination of local search algorithms with results for monotone submodular valuations, applied to the derived local optima.Comment: A conference version appears in WINE 201

Quantifying Methane Emissions in the Uintah Basin During Wintertime Stagnation Episodes

This study presents a meteorologically-based methodology for quantifying basin-scale methane (CH4) emissions in Utah’s Uintah Basin, which is home to over 9,000 active and producing oil and natural gas wells. Previous studies in oil and gas producing regions have often relied on intensive aircraft campaigns to estimate methane emissions. However, the high cost of airborne campaigns prevents their frequent undertaking, thus providing only daytime snapshots of emissions rather than more temporally-representative estimates over multiple days. Providing estimates of CH4 emissions from oil and natural gas production regions across the United States is important to inform leakage rates and emission mitigation efforts in order to curb the potential impacts of these emissions on global climate change and local air quality assessments. Here we introduce the Basin-constrained Emissions Estimate (BEE) method, which utilizes the confining topography of a basin and known depth of a pollution layer during multi-day wintertime cold-air pool episodes to relate point observations of CH4 to basin-scale CH4 emission rates. This study utilizes ground-based CH4 observations from three fixed sites to calculate daily increases in CH4, a laser ceilometer to estimate pollution layer depth, and a Lagrangian transport model to assess the spatial representativity of surface observations. BEE was applied to two cold-air pool episodes during the winter of 2015–2016 and yielded CH4 emission estimates between 44.60 +/– 9.66 × 103 and 61.82 +/– 19.76 × 103 kg CH4 hr–1, which are similar to the estimates proposed by previous studies performed in the Uintah Basin. The techniques used in this study could potentially be utilized in other deep basins worldwide

Birth characteristics and childhood carcinomas

BACKGROUND: Carcinomas in children are rare and have not been well studied. METHODS: We conducted a population-based case–control study and examined associations between birth characteristics and childhood carcinomas diagnosed from 28 days to 14 years during 1980–2004 using pooled data from five states (NY, WA, MN, TX, and CA) that linked their birth and cancer registries. The pooled data set contained 57 966 controls and 475 carcinoma cases, including 159 thyroid and 126 malignant melanoma cases. We used unconditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: White compared with ‘other' race was positively associated with melanoma (OR=3.22, 95% CI 1.33–8.33). Older maternal age increased the risk for melanoma (OR(per 5-year age increase)=1.20, 95% CI 1.00–1.44), whereas paternal age increased the risk for any carcinoma (OR=1.10(per 5-year age increase), 95% CI 1.01–1.20) and thyroid carcinoma (OR(per 5-year age increase)=1.16, 95% CI 1.01–1.33). Gestational age <37 vs 37–42 weeks increased the risk for thyroid carcinoma (OR=1.87, 95% CI 1.07–3.27). Plurality, birth weight, and birth order were not significantly associated with childhood carcinomas. CONCLUSION: This exploratory study indicates that some birth characteristics including older parental age and low gestational age may be related to childhood carcinoma aetiology

Onset and End of the Rainy Season in South America in Observations and the ECHAM 4.5 Atmospheric General Circulation Model

Rainfall in South America as simulated by a 24-ensemble member of the ECHAM 4.5 atmospheric general circulation model is compared and contrasted with observations (in areas in which data are available) for the period 1976–2001. Emphasis is placed on determining the onset and end of the rainy season, from which its length and rain rate are determined. It is shown that over large parts of the domain the onset and ending dates are well simulated by the model, with biases of less than 10 days. There is a tendency for model onset to occur early and ending to occur late, resulting in a simulated rainy season that is on average too long in many areas. The model wet season rain rate also tends to be larger than observed. To estimate the relative importance of errors in wet season length and rain rate in determining biases in the annual total, adjusted totals are computed by substituting both the observed climatological wet season length and rate for those of the model. Problems in the rain rate generally are more important than problems in the length. The wet season length and rain rate also contribute substantially to interannual variations in the annual total. These quantities are almost independent, and it is argued that they are each associated with different mechanisms. The observed onset dates almost always lie within the range of onset of the ensemble members, even in the areas with a large model onset bias. In some areas, though, the model does not perform well. In southern Brazil the model ensemble average onset always occurs in summer, whereas the observations show that winter is often the wettest period. Individual members, however, do occasionally show a winter rainfall peak. In southern Northeast Brazil the model has a more distinct rainy season than is observed. In the northwest Amazon the model annual cycle is shifted relative to that observed, resulting in a model bias. No interannual relationship between model and observed onset dates is expected unless onset in the model and observations has a mutual relationship with SST anomalies. In part of the near-equatorial Amazon, there does exist an interannual relationship between onset dates. Previous studies have shown that in this area there is a relationship between SST anomalies and variations in seasonal total rainfall

Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981–2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile–quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.This work has received funding from the MULTI-SDM project (MINECO/FEDER, CGL2015-66583-R). The authors are grateful to SENAMHI for the observational data, which are publicly available from http://www.senamhi.gob.pe/?p=data-historica, and to the European Center for Medium-Range Weather Forecast (ECMWF), for the access to the System4 seasonal forecasting hindcast

Pacific climate variability and the possible impact on global surface CO2 flux

<p>Abstract</p> <p>Background</p> <p>Climate variability modifies both oceanic and terrestrial surface CO2 flux. Using observed/assimilated data sets, earlier studies have shown that tropical oceanic climate variability has strong impacts on the land surface temperature and soil moisture, and that there is a negative correlation between the oceanic and terrestrial CO2 fluxes. However, these data sets only cover less than the most recent 20 years and are insufficient for identifying decadal and longer periodic variabilities. To investigate possible impacts of interannual to interdecadal climate variability on CO2 flux exchange, the last 125 years of an earth system model (ESM) control run are examined.</p> <p>Results</p> <p>Global integration of the terrestrial CO2 flux anomaly shows variation much greater in amplitude and longer in periodic timescale than the oceanic flux. The terrestrial CO2 flux anomaly correlates negatively with the oceanic flux in some periods, but positively in others, as the periodic timescale is different between the two variables. To determine the spatial pattern of the variability, a series of composite analyses are performed. The results show that the oceanic CO2 flux variability peaks when the eastern tropical Pacific has a large sea surface temperature anomaly (SSTA). By contrast, the terrestrial CO2 flux variability peaks when the SSTA appears in the central tropical Pacific. The former pattern of variability resembles the ENSO-mode and the latter the ENSO-modoki¹.</p> <p>Conclusions</p> <p>Our results imply that the oceanic and terrestrial CO2 flux anomalies may correlate either positively or negatively depending on the relative phase of these two modes in the tropical Pacific.</p

Late Holocene climate: Natural or anthropogenic?

For more than a decade, scientists have argued about the warmth of the current interglaciation. Was the warmth of the preindustrial late Holocene natural in origin, the result of orbital changes that had not yet driven the system into a new glacial state? Or was it in considerable degree the result of humans intervening in the climate system through greenhouse gas emissions from early agriculture? Here we summarize new evidence that moves this debate forward by testing both hypotheses. By comparing late Holocene responses to those that occurred during previous interglaciations (in section 2), we assess whether the late Holocene responses look different (and thus anthropogenic) or similar (and thus natural). This comparison reveals anomalous (anthropogenic) signals. In section 3, we review paleoecological and archaeological syntheses that provide ground truth evidence on early anthropogenic releases of greenhouse gases. The available data document large early anthropogenic emissions consistent with the anthropogenic ice core anomalies, but more information is needed to constrain their size. A final section compares natural and anthropogenic interpretations of the δ13C trend in ice core CO2