bluuebunny/crossref_metadata_2025_split huggingface dataset:
LokVaani
Authors: Gabale Vijay , Raman Bhaskaran , Chebrolu Kameswari , Kulkarni Purushottam 
Published: October 2012

In this work, we consider the goal of enabling effective voice communication in a TDMA, multi-hop mesh network, using low cost and low power platforms. We consider two primary usage scenarios: (1) enabling a local voice communication within a village-like setting, in developing regions (2) supporting an on-site local communication among a team of users e.g. during emergency response systems.
While there is plentiful literature on the use of TDMA for multi-hop wireless mesh networks, a practical multi-hop TDMA system remains elusive. Our contributions in this regard are three-fold. (1) We demonstrate the working of an 802.15.4-based low-cost, low-power, local communication system (referred as Lo3) using custom made handsets and off-the-shelf platforms. (2) We show the practicability of LiT: a full-fledged TDMA-based multi-hop, multi-channel MAC protocol for real-time applications; especially on resource constrained platforms, (3) We present implementation-based evaluations results of LiT and show that our protocol achieves practical synchronization, and robust operation in the face of wireless packet errors. As the part of the demo, we showcase LokVaani: an interactive voice application for local communication with the help of Lo3 prototype.
Human-aware task planning
Authors: Cirillo Marcello , Karlsson Lars , Saffiotti Alessandro 
Published: October 2012

Consider a house cleaning robot planning its activities for the day. Assume that the robot expects the human inhabitant to first dress, then have breakfast, and finally go out. Then, it should plan not to clean the bedroom while the human is dressing, and to clean the kitchen after the human has had breakfast. In general, robots operating in inhabited environments, like households and future factory floors, should plan their behavior taking into account the actions that will be performed by the humans sharing the same environment. This would improve human-robot cohabitation, for example, by avoiding undesired situations for the human. Unfortunately, current task planners only consider the robot's actions and unexpected external events in the planning process, and cannot accommodate expectations about the actions of the humans.
In this article, we present a human-aware planner able to address this problem. Our planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. Our planner has been tested both as a stand-alone component and within a full framework for human-robot interaction in a real environment.
Submodularity and its applications in optimized information gathering
Authors: Krause Andreas , Guestrin Carlos 
Published: October 2012

Where should we place sensors to efficiently monitor natural drinking water resources for contamination? Which blogs should we read to learn about the biggest stories on the Web? These problems share a fundamental challenge: How can we obtain the most useful information about the state of the world, at minimum cost?
Such information gathering, or active learning, problems are typically NP-hard, and were commonly addressed using heuristics without theoretical guarantees about the solution quality. In this article, we describe algorithms which efficiently find provably near-optimal solutions to large, complex information gathering problems. Our algorithms exploit submodularity, an intuitive notion of diminishing returns common to many sensing problems: the more sensors we have already deployed, the less we learn by placing another sensor. In addition to identifying the most informative sensing locations, our algorithms can handle more challenging settings, where sensors need to be able to reliably communicate over lossy links, where mobile robots are used for collecting data, or where solutions need to be robust against adversaries and sensor failures.
We also present results applying our algorithms to several real-world sensing tasks, including environmental monitoring using robotic sensors, activity recognition using a built sensing chair, a sensor placement challenge, and deciding which blogs to read on the Web.
Sustainable biomass power plant location in the Italian Emilia-Romagna region
Authors: Cattafi Massimiliano , Gavanelli Marco , Milano Michela , Cagnoli Paolo 
Published: October 2012

Biomass power plants are very promising for reducing carbon oxides emissions, because they provide energy with a carbon-neutral process. Biomass comes from trees and vegetables, so they provide a renewable type of energy. However, biomass plants location, along with their provisioning basins, are heavily regulated by economical aspects, often without careful consideration of their environmental footprint. For example, some Italian biomass plants import from overseas palm-tree oil that is economically convenient. However, the energy consumed for the oil transportation is definitely greater than the energy produced by the palm-tree oil burning. In this way biomass power plants turn out to be environmentally inefficient, even if they produce renewable energy.
We propose an Integer Linear Programming approach for defining the energy and cost-efficient biomass plant location along with the corresponding provisioning basin. In addition, the model enables to evaluate existing plants and their energy and cost efficiency. Our study is based on real data gathered in the Emilia-Romagna region of Italy.
Finally, this optimization tool is just a small part of a wider perspective that is aimed to define decision support tools for the improvement of regional planning and its precise strategic environmental assessment.
RECYCLE
Authors: Haigh Karen Zita , Yaman Fusun 
Published: October 2012

A
workflow
is a model of a process that systematically describes patterns of activity. Workflows capture a sequence of operations, their enablement conditions, and data flow dependencies among them. It is hard to design a complete and correct workflow from scratch, while it is much easier for humans to demonstrate the solution than to state the solution declaratively.

This article presents RECYCLE, our approach to learning workflow models from example demonstration traces. RECYCLE captures control flow, data flow, and enablement conditions of an underlying workflow process. Unlike prior work from workflow mining and AI planning literature, (1) RECYCLE can learn from a single demonstration trace with loops, (2) RECYCLE learns both loop and conditional branch structure, and (3) RECYCLE handles data flow among actions.
In this article, we describe the phases of RECYCLE's learning algorithm: substructure analysis and node abstraction. To ground the discussion, we present a simplified flight reservation system with some of the important characteristics of the real domains we worked with. We present some results from a patient transport domain.
Cross-Lingual Adaptation Using Structural Correspondence Learning
Authors: Prettenhofer Peter , Stein Benno 
Published: October 2012

Cross-lingual adaptation is a special case of domain adaptation and refers to the transfer of classification knowledge between two languages. In this article we describe an extension of Structural Correspondence Learning (SCL), a recently proposed algorithm for domain adaptation, for cross-lingual adaptation in the context of text classification. The proposed method uses unlabeled documents from both languages, along with a word translation oracle, to induce a cross-lingual representation that enables the transfer of classification knowledge from the source to the target language. The main advantages of this method over existing methods are resource efficiency and task specificity.
We conduct experiments in the area of cross-language topic and sentiment classification involving English as source language and German, French, and Japanese as target languages. The results show a significant improvement of the proposed method over a machine translation baseline, reducing the relative error due to cross-lingual adaptation by an average of 30% (topic classification) and 59% (sentiment classification). We further report on empirical analyses that reveal insights into the use of unlabeled data, the sensitivity with respect to important hyperparameters, and the nature of the induced cross-lingual word correspondences.
Surface Sulfur Detection via Remote Sensing and Onboard Classification
Authors: Mandrake Lukas , Rebbapragada Umaa , Wagstaff Kiri L. , Thompson David , Chien Steve , Tran Daniel , Pappalardo Robert T. , Gleeson Damhnait , Castaño Rebecca 
Published: October 2012

Orbital remote sensing provides a powerful way to efficiently survey targets such as the Earth and other planets and moons for features of interest. One such feature of astrobiological relevance is the presence of surface sulfur deposits. These deposits have been observed to be associated with microbial activity at the Borup Fiord glacial springs in Canada, a location that may provide an analogue to other icy environments such as Europa.
This article evaluates automated classifiers for detecting sulfur in remote sensing observations by the hyperion spectrometer on the EO-1 spacecraft. We determined that a data-driven machine learning solution was needed because the sulfur could not be detected by simply matching observations to sulfur lab spectra. We also evaluated several methods (manual and automated) for identifying the most relevant attributes (spectral wavelengths) needed for successful sulfur detection. Our findings include (1) the Borup Fiord sulfur deposits were best modeled as containing two sub-populations: sulfur on ice and sulfur on rock; (2) as expected, classifiers using Gaussian kernels outperformed those based on linear kernels, and should be adopted when onboard computational constraints permit; and (3) Recursive Feature Elimination selected sensible and effective features for use in the computationally constrained environment onboard EO-1. This study helped guide the selection of algorithm parameters and configuration for the classification system currently operational on EO-1. Finally, we discuss implications for a similar onboard classification system for a future Europa orbiter.
Regulatory T Cells Move in When Gliomas Say “I DO”
Authors: Choi Bryan D. , Fecci Peter E. , Sampson John H. 
Published: October 2012

Abstract
Indoleamine 2,3-dioxygenase (IDO) is an enzyme with known immunosuppressive and tolerogenic effects in cancer. Mounting evidence has associated IDO expression with the induction of regulatory T cells (Treg) and malignant progression. IDO inhibition may therefore provide a promising therapeutic approach for glioblastoma, where the need for novel treatment is great. Clin Cancer Res; 18(22); 6086–8. ©2012 AACR.
Real-time Pathology to Guide Breast Surgery: Seeing Alone Is Not Believing
Authors: Bigio Irving J. 
Published: October 2012

Abstract
Tissue diagnostic techniques based on optical spectroscopy, in various incarnations, are approaching clinical reality for intraoperative guidance of surgical procedures. Examination of tissue properties by elastic light-scattering spectroscopy may constitute a preferable alternative to frozen-section pathology or touch imprint cytology for intraoperative assessment of resection margins during breast-conserving surgery. Clin Cancer Res; 18(22); 6083–5. ©2012 AACR.
A Phase III Skin Cancer Chemoprevention Study of DFMO: Long-term Follow-up of Skin Cancer Events and Toxicity
Authors: Kreul Sarah M. , Havighurst Tom , Kim KyungMann , Mendonça Eneida A. , Wood Gary S. , Snow Stephen , Borich Abbey , Verma Ajit , Bailey Howard H. 
Published: October 2012

Abstract
Decreasing the incidence of nonmelanoma skin cancer (NMSC) is of great importance in regards to future healthcare services. Given the previously reported preventive effects of α-difluoromethylornithine (DFMO) in skin and colon cancer trials, we determined appropriate cause to update the clinical data on the subjects from the recently reported randomized, double-blind, placebo-controlled phase III skin cancer prevention study of DFMO. Our intention was to retrospectively assess the further incidence of skin cancer, other malignancies, and adverse events of patients accrued to our phase III skin cancer prevention study of DFMO. Clinical records of 209 University of Wisconsin (UW) Health subjects were reviewed, and 2,092.7 person years of on study (884.3 person years) and poststudy (1,208.4 person years) follow-up for these patients were assessed for new NMSC events and recurrence rates from the on study period, the poststudy period, and the two study periods combined. No evidence of increased significant diagnoses or serious adverse events was observed in the DFMO participants. The initially observed, marginally significant reduction (P = 0.069) in NMSC rates for DFMO subjects relative to placebo continued without evidence of rebound. Event rates after discontinuation from study for total NMSCs (DFMO 0.236 NMSC/person/year, placebo 0.297, P = 0.48) or the subtypes of basal cell carcinomas (BCC; DFMO 0.179 BCC/person/year, placebo 0.190, P = 0.77) and squamous cell carcinomas (SCC; DFMO 0.057 SCC/person/year, placebo 0.107, P = 0.43) are listed. Follow-up data revealed a persistent but insignificant reduction in new NMSCs occurring in DFMO subjects without evidence of latent or cumulative toxicity relative to placebo subjects. Cancer Prev Res; 5(12); 1368–74. ©2012 AACR.
Prognostic Impact of Hyperglycemia in Nondiabetic and Diabetic Patients With ST-Elevation Myocardial Infarction
Authors: Eitel Ingo , Hintze Stefan , Waha Suzanne de , Fuernau Georg , Lurz Philipp , Desch Steffen , Schuler Gerhard , Thiele Holger 
Published: October 2012

Background—
Hyperglycemia on admission is associated with increased mortality rates in patients with ST-elevation myocardial infarction (STEMI). However, data regarding the relationship between hyperglycemia and myocardial damage in STEMI are scarce. The aim of this study was to determine the relationship of diabetes mellitus status and hyperglycemia on myocardial damage assessed by cardiovascular magnetic resonance imaging and to evaluate the long-term prognostic significance of hyperglycemia in a high-risk STEMI population.

Methods and Results—

Glucose levels were determined on admission in 411 consecutive STEMI patients reperfused by primary angioplasty. Patients were categorized on the basis of diabetes mellitus status and admission glucose level. Magnetic resonance imaging was performed for assessment of infarct size and microvascular obstruction. The primary clinical end point was the occurrence of major adverse cardiovascular events at long-term follow-up. STEMI patients with pre-existing diabetes mellitus were at greater risk for major adverse cardiovascular events (32% versus 11%;
P
<0.001) despite having similar infarct sizes and extent of reperfusion injury than nondiabetic patients. Glycemic status on admission was associated with greater myocardial damage and an increased risk for major adverse cardiovascular events (
P
<0.001). In nondiabetic patients, the risk of severe myocardial injury started to rise once admission glucose exceeded 7.8 mmol/L, whereas the threshold was higher among patients with diabetes mellitus (≥11.1 mmol/L).

Conclusions—
The higher mortality rate in diabetic versus nondiabetic STEMI patients is not explained by more pronounced myocardial damage. Hyperglycemia on admission is associated with greater myocardial injury and an increased risk of major adverse cardiovascular events at long-term follow-up. However, hyperglycemia has a stronger relationship to myocardial injury in nondiabetic compared with diabetic patients.
Transcatheter Aortic Valve Replacement for Degenerative Bioprosthetic Surgical Valves
Authors: Dvir Danny , Webb John , Brecker Stephen , Bleiziffer Sabine , Hildick-Smith David , Colombo Antonio , Descoutures Fleur , Hengstenberg Christian , Moat Neil E. , Bekeredjian Raffi , Napodano Massimo , Testa Luca , Lefevre Thierry , Guetta Victor , Nissen Henrik , Hernández José-María , Roy David , Teles Rui C. , Segev Amit , Dumonteil Nicolas , Fiorina Claudia , Gotzmann Michael , Tchetche Didier , Abdel-Wahab Mohamed , De Marco Federico , Baumbach Andreas , Laborde Jean-Claude , Kornowski Ran 
Published: October 2012

Background—
Transcatheter aortic valve-in-valve implantation is an emerging therapeutic alternative for patients with a failed surgical bioprosthesis and may obviate the need for reoperation. We evaluated the clinical results of this technique using a large, worldwide registry.

Methods and Results—
The Global Valve-in-Valve Registry included 202 patients with degenerated bioprosthetic valves (aged 77.7±10.4 years; 52.5% men) from 38 cardiac centers. Bioprosthesis mode of failure was stenosis (n=85; 42%), regurgitation (n=68; 34%), or combined stenosis and regurgitation (n=49; 24%). Implanted devices included CoreValve (n=124) and Edwards SAPIEN (n=78). Procedural success was achieved in 93.1% of cases. Adverse procedural outcomes included initial device malposition in 15.3% of cases and ostial coronary obstruction in 3.5%. After the procedure, valve maximum/mean gradients were 28.4±14.1/15.9±8.6 mm Hg, and 95% of patients had ≤+1 degree of aortic regurgitation. At 30-day follow-up, all-cause mortality was 8.4%, and 84.1% of patients were at New York Heart Association functional class I/II. One-year follow-up was obtained in 87 patients, with 85.8% survival of treated patients.

Conclusions—
The valve-in-valve procedure is clinically effective in the vast majority of patients with degenerated bioprosthetic valves. Safety and efficacy concerns include device malposition, ostial coronary obstruction, and high gradients after the procedure.
Resource Extraction Contracts Under Threat of Expropriation: Theory and Evidence
Authors: Stroebel Johannes , van Benthem Arthur 
Published: October 2012

Abstract
We use fiscal data on 2,468 oil extraction agreements in 38 countries to study tax contracts between resource-rich countries and independent oil companies. We analyze why expropriations occur and what determines the degree of oil price exposure of host countries. With asymmetric information about a country's expropriation cost, even optimal contracts feature expropriations. Near linearity in the oil price of real-world hydrocarbon contracts also helps to explain expropriations. We show theoretically and verify empirically that oil price insurance provided by tax contracts is increasing in a country's cost of expropriation and decreasing in its production expertise. The timing of actual expropriations is consistent with our model.
Temporal and Spatial Aspects of Velocity Variance in the Urban Surface Roughness Layer
Authors: Hicks Bruce B. , Novakovskaia Elena , Dobosy Ronald J. , Pendergrass William R. , Callahan William J. 
Published: October 2012

AbstractData from six urban areas in a nationwide network of sites within the surface roughness layer are examined. It is found that the average velocity variances in time, derived by averaging the conventional variances from a network of n stations, are nearly equal to the velocity variances in space, derived as the variances among the n average velocities. This similarity is modified during sunlit hours, when convection appears to elevate the former. The data show little dependence of the ratio of these two variances on wind speed. It is concluded that the average state of the surface roughness layer in urban and suburban areas like those considered here tends toward an approximate equality of these two measures of variance, much as has been observed elsewhere for the case of forests.
The Properties and Formation of Cirrus Clouds over the Tibetan Plateau Based on Summertime Lidar Measurements
Authors: He Q. S. , Li C. C. , Ma J. Z. , Wang H. Q. , Shi G. M. , Liang Z. R. , Luan Q. , Geng F. H. , Zhou X. W. 
Published: October 2012

Abstract
As part of the Tibet Ozone, Aerosol and Radiation (TOAR) project, a micropulse lidar was operated in Naqu (31.5°N, 92.1°E; 4508 m MSL) on the Tibetan Plateau to observe cirrus clouds continuously from 19 July to 26 August 2011. During the experiment, the time coverage of ice clouds only was 15% in the upper troposphere (above 9.5 km MSL). The cirrus top/bottom altitudes (mean values of 15.6/14.7 km) are comparable to those measured previously at tropical sites but relatively higher than those measured at midlatitude sites. The majority of the cloud layers yielded a lidar ratio between 10 and 40 sr, with a mean value of 28 ± 15 sr, characterized by a bimodal frequency distribution. Subvisible, thin, and opaque cirrus formation was observed in 16%, 34%, and 50% of all cirrus cases, respectively. A mean cirrus optical depth of 0.33 was observed over the Tibetan Plateau, slightly higher than those in the subtropics and tropics. With decreasing temperature, the lidar ratio increased slightly, whereas the mean extinction coefficient decreased significantly. The occurrence of clouds is highly correlated with the outgoing longwave radiation and the strong cold perturbations in the upper troposphere. Deep convective activity and Rossby waves are important dynamical processes that control cirrus variations over the Tibetan Plateau, where both anvil cirrus outflowing from convective cumulonimbus clouds and large-scale strong cold perturbations in the upper troposphere should play an important role in cirrus formation.
Impact of Enthalpy-Based Ensemble Filtering Sea Ice Data Assimilation on Decadal Predictions: Simulation with a Conceptual Pycnocline Prediction Model
Authors: Zhang S. , Winton M. , Rosati A. , Delworth T. , Huang B. 
Published: October 2012

AbstractThe non-Gaussian probability distribution of sea ice concentration makes it difficult to directly assimilate sea ice observations into a climate model. Because of the strong impact of the atmospheric and oceanic forcing on the sea ice state, any direct assimilation adjustment on sea ice states is easily overridden by model physics. A new approach implements sea ice data assimilation in enthalpy space where a sea ice model represents a nonlinear function that transforms a positive-definite space into the sea ice concentration subspace. Results from observation–assimilation experiments using a conceptual pycnocline prediction model that characterizes the influences of sea ice on the decadal variability of the climate system show that the new scheme efficiently assimilates “sea ice observations” into the model: while improving sea ice variability itself, it consistently improves the estimates of all “climate” components. The resulted coupled initialization that is physically consistent among all coupled components significantly improves decadal-scale predictability of the coupled model.