bluuebunny/crossref_metadata_2025_split huggingface dataset:
A classification for community discovery methods in complex networks
Authors: Coscia Michele , Giannotti Fosca , Pedreschi Dino 
Published: September 2011

AbstractMany real‐world networks are intimately organized according to a community structure. Much research effort has been devoted to develop methods and algorithms that can efficiently highlight this hidden structure of a network, yielding a vast literature on what is called todaycommunity detection. Since network representation can be very complex and can contain different variants in the traditional graph model, each algorithm in the literature focuses on some of these properties and establishes, explicitly or implicitly, its own definition of community. According to this definition, each proposed algorithm then extracts the communities, which typically reflect only part of the features of real communities. The aim of this survey is to provide a ‘user manual’ for the community discovery problem. Given a meta definition of what a community in a social network is, our aim is to organize the main categories of community discovery methods based on the definition of community they adopt. Given a desired definition of community and the features of a problem (size of network, direction of edges, multidimensionality, and so on) this review paper is designed to provide a set of approaches that researchers could focus on. The proposed classification of community discovery methods is also useful for putting into perspective the many open directions for further research. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 512–546, 2011
Confidence sets for network structure
Authors: Airoldi Edoardo M. , Choi David S. , Wolfe Patrick J. 
Published: September 2011

AbstractLatent variable models are frequently used to identify structure in dichotomous network data, in part, because they give rise to a Bernoulli product likelihood that is both well understood and consistent with the notion of exchangeable random graphs. In this article, we propose conservative confidence sets that hold with respect to these underlying Bernoulli parameters as a function of any given partition of network nodes, enabling us to assess estimates of residual network structure, that is, structure that cannot be explained by known covariates and thus cannot be easily verified by manual inspection. We demonstrate the proposed methodology by analyzing student friendship networks from the National Longitudinal Survey of Adolescent Health that include race, gender, and school year as covariates. We employ a stochastic expectation‐maximization algorithm to fit a logistic regression model that includes these explanatory variables as well as a latent stochastic blockmodel component and additional node‐specific effects. Although maximum‐likelihood estimates do not appear consistent in this context, we are able to evaluate confidence sets as a function of different blockmodel partitions, which enables us to qualitatively assess the significance of estimated residual network structure relative to a baseline, which models covariates but lacks block structure. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 461–469, 2011
Combining a Nanowire SERRS Sensor and a Target Recycling Reaction for Ultrasensitive and Multiplex Identification of Pathogenic Fungi
Authors: Yoo Seung Min , Kang Taejoon , Kang Hyungchang , Lee Hyoban , Kang Mijeong , Lee Sang Yup , Kim Bongsoo 
Published: September 2011

AbstractDevelopment of a rapid, sensitive, and multiplex pathogen DNA sensor enables early diagnosis and, subsequently, the proper treatment of infectious diseases, increasing the possibility to save the lives of infected patients. Here, the development of an ultrasensitive and multiplex pathogen DNA detection method that combines a patterned Au nanowire (NW)‐on‐film surface‐enhanced resonance Raman scattering (SERRS) sensor with an exonuclease III‐assisted target DNA recycling reaction is reported. Multiple probe DNAs are added to the target DNA solution, and among them, only the complementary probe DNA is selectively digested by exonuclease III, resulting in the decrease in its concentration. The digestion process is repeated by recycling of target DNAs. The decrease of the complementary probe DNA concentration is detected by SERRS. Combining the high sensitivity of the NW‐on‐film sensor and the target recycling reaction significantly improves DNA detection performance, resulting in the detection limit of 100 fM corresponding to 3 amole. By positioning Au NWs at specific addresses, multiple pathogen DNAs can be identified in a single step. Clinical sample tests with multiple genomic DNAs of pathogens show the potential of this sensor for practical diagnosis of infectious diseases.
Evaluation of system reliability for a cloud computing system with imperfect nodes
Authors: Lin Yi‐Kuei , Chang Ping‐Chen 
Published: September 2011

AbstractFrom the perspective of system design and quality of service (QoS), system reliability is one of the essential performance indicators to measure the probable reliability of a network. In terms of a practical cloud computing system (CCS), edges and nodes have various capacities or states due to failure, partial failure, or maintenance. Thus, the CCS is a typical capacitated‐flow network. To guarantee a good level of quality and reliability, the CCS should be maintained, so as not to fall into a failed state whereby it cannot provide sufficient capacity to satisfy demand. Thus, system reliability is developed in this paper to evaluate the capability of the CCS to send d units of data from the cloud to the client through two paths under both the maintenance budget and time constraints. An algorithm with an adjusting procedure based on the branch‐and‐bound approach is proposed to evaluate the system reliability. The relevant proof shows that the proposed algorithm is reasonable and appropriate for measuring the system reliability of the CCS. According to different maintenance budgets and corresponding system reliability, the system supervisor could determine a reasonable maintenance budget to maintain a good level of quality and reliability of the CCS. From the perspective of system design, the system supervisor could further conduct a sensitivity analysis to improve or investigate the most important part in a large CCS based on system reliability. © 2011 Wiley Periodicals, Inc.
Increased Aortic Stiffness Can Predict Perioperative Cardiovascular Outcomes in Patients Undergoing Noncardiac, Nonvascular Surgery
Authors: Biteker Murat , Duman Dursun , Dayan Akın , İlhan Erkan 
Published: September 2011

AbstractBackgroundAortic stiffness is an early marker of arteriosclerosis and associated with cardiovascular mortality. However, the impact of aortic stiffness on perioperative cardiovascular outcomes in patients undergoing noncardiac surgery is unknown.MethodsThe study population was composed of 660 consecutive adults aged 18 years and over (mean age = 65.3 ± 14 years) who underwent intermediate‐risk (nonvascular), noncardiac surgery between January 2010 and February 2011. Nonemergency, non‐day‐case, open surgical procedures were enrolled. Aortic stiffness indices were calculated from the aortic diameters measured by echocardiography. Electrocardiography and cardiac biomarkers were evaluated 1 day before surgery, and on days 1, 3, and 7 after surgery.ResultsEighty patients (12.1%) experienced perioperative cardiovascular events (PCE). Preoperative aortic distensibility (AD) (2 ± 1.3 vs. 2.9 ± 1.1 cm2/dyn/103, P < 0.001) and aortic strain (AS) (4.4 ± 2.4 vs. 6.4 ± 1.9, P < 0.001) of the patients with PCE were significantly lower than in patients without PCE. Univariate analysis showed a significant association between age, diabetes mellitus (DM), coronary artery disease, preoperative atrial fibrillation, American Society of Anesthesiologists (ASA) status, Revised Cardiac Risk Index, left ventricle ejection fraction (LVEF), AD, aortic strain, and in‐hospital PCE. However, on multivariate logistic regression analysis, only AD (OR: 1.94, 95% CI: 1.1–3.4; P = 0.02), AS (OR: 0.45, 95% CI: 0.3–0.6; P < 0.001), DM (OR: 2.28, 95% CI: 1.08–4.82; P = 0.03), and LVEF (OR: 0.96, 95% CI: 0.93–0.99; P = 0.03) remained as significant variables associated with PCE.ConclusionImpaired elastic properties of the aorta are associated with increased PCE rates in patients undergoing noncardiac, nonvascular surgery.
Electrospray Ionization Tandem Mass Spectrometry of Sodiated Adducts of Cholesteryl Esters
Authors: Bowden John A. , Shao Fei , Albert Carolyn J. , Lally John W. , Brown Robert J. , Procknow Jesse D. , Stephenson Alan H. , Ford David A. 
Published: September 2011

AbstractCholesteryl esters (CE) are important lipid storage molecules. The present study demonstrates that sodiated adducts of CE molecular species form positive ions that can be detected in both survey scan mode as well as by exploiting class‐specific fragmentation in MS/MS scan modes. A common neutral loss for CE is the loss of cholestane (NL 368.5), which can be used to specifically quantify tissue CE molecular species. Using this MS/MS technique, CE molecular species were quantified in mouse monocyte‐derived macrophages (J774 cells) incubated with either linoleic (18:2) or arachidonic acid (20:4). These studies revealed that arachidonic acid was not only incorporated into the CE pool, but also was elongated resulting in the accumulation of 22:4 and 24:4 CE molecular species in macrophages. Additionally, this technique was used to quantify CE molecular species present in crude lipid extracts from plasma of female mice fed a Western diet, which led to an enrichment in CE molecular species containing monounsaturated fatty acids compared to female mice fed a normal chow diet. Last, NL 368.5 spectra revealed the oxidation of the aliphatic fatty acid residues of CE molecular species containing polyunsaturated fatty acids. Taken together, these studies demonstrate the utility of using sodiated adducts of CE in conjunction with direct infusion electrospray ionization tandem mass spectrometry to rapidly quantify CE molecular species in biological samples.
The Influence of Growing Region on Fatty Acids and Sterol Composition of Iranian Olive Oils by Unsupervised Clustering Methods
Authors: Piravi‐Vanak Z. , Ghasemi Jahan B. , Ghavami M. , Ezzatpanah H. , Zolfonoun E. 
Published: September 2011

AbstractTwenty seven Iranian olive oil samples were collected from different provinces to evaluate fatty acids and sterol compositions. The samples were collected from different geographical locations that varied in altitude, temperature, humidity and rain fall. The sample collected from the northern part of Iran by the Caspian Sea had higher oleic acid [G2 sample (75.98%)] and lower linoleic acid [Go5 sample (6.5%)] and palmitic acid [G2 sample (10.78%)] concentrations than samples from the southern part of the country such as F1 whose contents of C16:0, C18:1 and C18:2 were 15.27, 62.73 and 16.09%, respectively, in the southern part, the climate is dry and the temperature variation is wider and the elevation is 1,488 m. The results indicated that oleic acid was the predominant fatty acid with 62.7% for F1 sample in the warmer climate at the south of Iran to 76.0% for G2 sample in the cooler climate in the north of Iran. According to the results, the highest content of β‐sitosterol was 87% related to samples G9 and Z3 from the north of Iran and the lowest content was 69.95% related to sample F1–24 from the south of Iran. Clustering techniques such as principal component analysis and hierarchical cluster analysis were carried out on olive composition data to show similarities and discrimination between samples as a function of the cultivation zone. The two methods applied clearly showed the effect of growing regions on the distribution of the olive oil samples in the high dimensional space created by fatty acid and sterol compositions.
Ethiopia's assessment of emergency obstetric and newborn care: Setting the gold standard for national facility‐based assessments
Authors: Keyes Emily B. , Haile‐Mariam Abonesh , Belayneh Neghist T. , Gobezie Wasihun A. , Pearson Luwei , Abdullah Muna , Kebede Henok 
Published: September 2011

AbstractObjectiveTo describe the methods used to implement Ethiopia's 2008 emergency obstetric and newborn care services (EmONC) assessment; highlight how the collaborative process contributed to immediate integration of results into national and subnational planning; and explain how the experience informed the development of a set of tools providing best practices and guidelines for other countries conducting similar assessments.MethodsA team of maternal and newborn health experts from the Federal Ministry of Health (FMOH), the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), and the United Nations Population Fund (UNFPA), together with representatives from the Ethiopian Society of Obstetricians and Gynecologists, provided technical guidance for the 18‐month process and facilitated demand for and use of the assessment results. Eighty‐four trained data collectors administered 9 data collection modules in 806 public and private facilities. Field work and data were managed by a private firm who, together with the core team, implemented a multi‐layered plan for data quality. Columbia University's Averting Maternal Death and Disability Program provided technical assistance.ResultsResults were published in national and regional reports and in 1‐page facility factsheets informing subnational planning activities. Assessment results—which have been published in journal articles—informed water infrastructure improvements, efforts to expand access to magnesium sulfate, and FMOH and UN planning documents. The assessment also established a permanent database for future monitoring of the health system, including geographic locations of surveyed facilities.ConclusionEthiopia's assessment was successful largely because of active local leadership, a collaborative process, ample financial and technical support, and rapid integration of results into health system planning.
Indicators for availability, utilization, and quality of emergency obstetric care in Ethiopia, 2008
Authors: Admasu Keseteberhan , Haile‐Mariam Abonesh , Bailey Patricia 
Published: September 2011

AbstractObjectiveTo report on the availability and quality of emergency obstetric and newborn care (EmONC) in Ethiopia.MethodsAll licensed hospitals and health centers were visited and standard questionnaires were administered. In addition, a nonrandom systematic sample was taken of recent cesarean deliveries, partographs, and maternal deaths—and these cases were systematically reviewed. Health facilities were geocoded using geographic positioning system devices.ResultsToo few facilities provided EmONC to meet the UN standards of 5 per 500 000 population, both nationally and in all but 2 regions. Only 7% of deliveries took place in institutions of any type, and only 3% in facilities that routinely provided all the signal functions. Only 6% of women with obstetric complications were treated in any health facility, half of whom were treated in fully functional EmONC facilities. Nationwide, 0.6% of expected deliveries were by cesarean. The mortality rate for women with serious obstetric complications (case fatality rate) was 2%. The cause of death was unknown in 10% of cases, and 21% were due to indirect causes (primarily malaria, anemia, and HIV‐related).ConclusionNone of the indicators met UN standards. Ethiopia faces many challenges—not least geography—with regard to improving EmONC. Nevertheless, the government places high priority on improvement and has taken (and will continue to take) action to achieve Millennium Development Goals 4 and 5. This comprehensive survey serves both as a road map for planning strategies for improvement and as a baseline for measuring the impact of interventions.
Late glacial and holocene landscapes of central Beringia
Authors: Lozhkin Anatoly V. , Anderson Patricia , Eisner Wendy R. , Solomatkina Tatiana B. 
Published: September 2011

AbstractNew palynological and sedimentological data from St. Lawrence Island present a rare view into late-glacial and Holocene environments of the central Bering Land Bridge. The late glaciation was a time of dynamic landscape changes in south-central Beringia, with active thermokarst processes, including the formation and drainage of thaw lakes. The presence of such a wet, unstable substrate, if widespread, probably would have had an adverse impact on food sources and mobility for many of the large mammal populations. The establishment ofBetulashrub tundra on the island suggests late-glacial summers that were warmer than present, consistent with regional paleoclimatic interpretations. However, the increasing proximity to the Bering Sea, as postglacial sea levels rose, modified the intensity of warming and prevented the establishment of deciduous forest as found in other areas of Beringia at this time. The mid- to late Holocene is marked by more stable land surfaces and development ofSphagnumand Cyperaceae peat deposits. The accumulation of organic deposits, decline of shrubBetula, and decrease in thermokarst disturbance suggest that conditions were cooler than the previous. A recent decline in peat accumulation at the study sites may relate to local geomorphology, but similar decreases have been noted for other arctic regions.
Formation of rhythmic sorted bed forms on the continental shelf: an idealised model
Authors: Van Oyen Tomas , de Swart Huib , Blondeaux Paolo 
Published: September 2011

AbstractAn idealised model is presented to study the formation of sorted bed forms generated by a wind-driven along-shore current. The study employs a linear stability analysis to describe the time development of perturbations of both bottom composition and bed elevation, superimposed on a flat bed composed of a sediment mixture homogeneously distributed in space. The model considers both bed and suspended loads and takes into account the averaged influence of waves on the flow field and the transport of sediment. The results show that the positive coupling between waves, along-shore current and the erodible heterogeneous bed leads to the amplification of two modes, which exhibit distinct characteristics. A first mode is found to be dominant when moderate hydrodynamic conditions are considered and is primarily amplified by the convergence of sediment transport induced by the changes in the bed elevation. This mode has wavelengths of the order of hundred metres and has coarse (fine) sediments in its troughs (crests). By increasing the height of the waves and/or the strength of the steady current, the second mode can become dominant. This mode is characterised by shorter wavelengths and results from the interaction between the convergence of sediment transport related to changes in the bottom composition and that induced by perturbations of the bed elevation. These bed features can have an up-current or a down-current shift between the centre of the coarse-grained bands and the trough of the bottom wave. Typical growth times of the amplified features are of the order of hundreds of days and the migration rates, in the direction of the along-shore current, range between 0.1 and 10 m per day. A qualitative comparison of the model results with field observations indicates that the generation of two distinct modes provides a possible explanation for the broad range of characteristics of the natural bed features.
GENERALIZED IMPLICIT INCLUSION PROBLEMS ON NONCOMPACT SETS WITH APPLICATIONS
Authors: WANG SAN-HUA , HUANG NAN-JING 
Published: September 2011

AbstractIn this paper, a class of generalized implicit inclusion problems is introduced, which can be regarded as a generalization of variational inequality problems, equilibrium problems, optimization problems and inclusion problems. Some existence results of solutions for such problems are obtained on noncompact subsets of Hausdorff topological vector spaces using the famous FKKM theorem. As applications, some existence results for vector equilibrium problems and vector variational inequalities on noncompact sets of Hausdorff topological vector spaces are given.
ANALYSIS OF FACTORS THAT DETERMINE TEA PRODUCTIVITY IN NORTHEASTERN INDIA: A COMBINED STATISTICAL AND MODELLING APPROACH
Authors: DUTTA RISHIRAJ , SMALING ERIC M. A. , BHAGAT RAJIV MOHAN , TOLPEKIN VALENTYNE A. , STEIN ALFRED 
Published: September 2011

SUMMARYThis study analyses the factors affecting tea productivity in Northeast India using a combined statistical and modelling approach. The effects of a number of genotypic, environmental and management factors on tea yield are quantified and modelled, using a three-year (2007–2009) field trial in Assam, Northeast India. Simulations of the potential tea yield are obtained using the Cranfield University Plantation Productivity Analysis (CUPPA) Tea model to find out how well the predicted and observed values for tea production match. This combined approach shows that plantation age has a significant negative (R2 = 0.77) effect on tea yield. Monthly rainfall had a significant positive effect on monthly yields (R2 = 0.43). Rainfall was more strongly associated with tea yield when rainfall in month x was related to the tea yield in month x + 1 (R2 = 0.49). When repeating the analysis for a hypothetical situation that the fields are fully planted, the correlation between monthly rainfall in month x and tea yield for month x + 1 increases (R2 = 0.58). Adjusted yields show a higher correlation than actual yields. The results obtained show a close correspondence between predicted and observed yields, indicating that the model could be used on contrasting soil types, genotypes and also on daily, weekly and monthly weather data. It can be further calibrated and validated for Northeast Indian conditions if more required input parameters are collected in a series of plantations. Tea research might benefit from developing new versions of the CUPPA Tea model for the major clonal tea cultivars, with a more flexible module for fertiliser application as is currently the case.
Ostracods from freshwater and brackish environments of the Carboniferous of the Midland Valley of Scotland: the early colonization of terrestrial water bodies
Authors: BENNETT C. E. , SIVETER D. J. , DAVIES S. J. , WILLIAMS M. , WILKINSON I. P. , BROWNE M. , MILLER C. G. 
Published: September 2011

AbstractThe Mississippian Strathclyde Group of the Midland Valley of Scotland yields some of the earliest non-marine ostracods. The succession records shallow marine, deltaic, estuarine, lagoonal, lacustrine, fluvial and swamp environments representing a series of staging-posts between fully marine and limnetic settings. Macrofossils and ostracods are assigned to marine, marginal marine, brackish and freshwater environments based on their faunal assemblage patterns. Key brackish to freshwater ostracods are Geisina arcuata, Paraparchites circularis n. sp., Shemonaella ornata n. sp. and Silenites sp. A, associated with the bivalves Anthraconaia, Carbonicola, Cardiopteridium, Curvirimula, Naiadites, the microconchid ‘Spirorbis’, Spinicaudata and fish. Many Platycopina and Paraparchiticopina ostracods are interpreted as euryhaline, which corresponds with their occurrence in marine to coastal plain water bodies, and supports the ‘estuary effect’ hypothesis of non-marine colonization. The success of non-marine colonization by ostracods was dependent on the intrinsic adaptations of ostracod species to lower salinities, such as new reproductive strategies and the timing of extrinsic mechanisms to drive non-marine colonization, such as sea-level change. The genus Carbonita is the oldest and most common freshwater ostracod, and went on to dominate freshwater environments in the Late Palaeozoic.