Efficient and Scalable Listing of Four-Vertex Subgraph

Identifying four-vertex subgraphs has long been recognized as a fundamental technique in bioinformatics and social networks. However, listing these structures is a challenging task, especially for graphs that do not fit in RAM. To address this problem, we build a set of algorithms, models, and implementations that can handle massive graphs on commodity hardware. Our technique achieves 4 – 5 orders of magnitude speedup compared to the best prior methods on graphs with billions of edges, with external-memory operation equally efficient

Air-sea heat flux climatologies in the Mediterranean Sea : surface energy balance and its consistency with ocean heat storage Authors

Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 122 (2017): 4068–4087, doi:10.1002/2016JC012254.This study provides an analysis of the Mediterranean Sea surface energy budget using nine surface heat flux climatologies. The ensemble mean estimation shows that the net downward shortwave radiation (192 ± 19 W m−2) is balanced by latent heat flux (−98 ± 10 W m−2), followed by net longwave radiation (−78 ± 13 W m−2) and sensible heat flux (−13 ± 4 W m−2). The resulting net heat budget (Qnet) is 2 ± 12 W m−2 into the ocean, which appears to be warm biased. The annual-mean Qnet should be −5.6 ± 1.6 W m−2 when estimated from the observed net transport through the Strait of Gibraltar. To diagnose the uncertainty in nine Qnet climatologies, we constructed Qnet from the heat budget equation by using historic hydrological observations to determine the heat content changes and advective heat flux. We also used the Qnet from a data-assimilated global ocean state estimation as an additional reference. By comparing with the two reference Qnet estimates, we found that seven products (NCEP 1, NCEP 2, CFSR, ERA-Interim, MERRA, NOCSv2.0, and OAFlux+ISCCP) overestimate Qnet, with magnitude ranging from 6 to 27 W m−2, while two products underestimate Qnet by −6 W m−2 (JRA55) and −14 W m−2 (CORE.2). Together with the previous warm pool work of Song and Yu (2013), we show that CFSR, MERRA, NOCSv2.0, and OAFlux+ISCCP are warm-biased not only in the western Pacific warm pool but also in the Mediterranean Sea, while CORE.2 is cold-biased in both regions. The NCEP 1, 2, and ERA-Interim are cold-biased over the warm pool but warm-biased in the Mediterranean Sea.National Natural Science Foundation of China (NSFC) Grant Number: 41306003 and 41430963; Fundamental Research Funds for the Central Universities Grant Number: 0905-841313038, 1100-841262028, and 0905-201462003; China Postdoctoral Science Foundation Grant Number: 2013M531647; Natural Science Foundation of Shandong Grant Number: BS2013HZ015; Qingdao National Laboratory for Marine Science and Technology2017-11-1

High-latitude contribution to global variability of air–sea sensible heat flux

Author Posting. © American Meteorological Society, 2012. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 25 (2012): 3515–3531, doi:10.1175/JCLI-D-11-00028.1.The study examined global variability of air–sea sensible heat flux (SHF) from 1980 to 2009 and the large-scale atmospheric and ocean circulations that gave rise to this variability. The contribution of high-latitude wintertime SHF was identified, and the relative importance of the effect of the sea–air temperature difference versus the effect of wind on decadal SHF variability was analyzed using an empirical orthogonal function (EOF) approach. The study showed that global SHF anomalies are strongly modulated by SHF at high latitudes (poleward of 45°) during winter seasons. Decadal variability of global wintertime SHF can be reasonably represented by the sum of two leading EOF modes, namely, the boreal wintertime SHF in the northern oceans and the austral wintertime SHF in the southern oceans. The study also showed that global wintertime SHF is modulated by the prominent modes of the large-scale atmospheric circulation at high latitudes. The increase of global SHF in the 1990s is attributable to the strengthening of the Southern Hemisphere annular mode index, while the decrease of global SHF after 2000 is due primarily to the downward trend of the Arctic Oscillation index. This study identified the important effects of wind direction and speed on SHF variability. Changes in winds modify the sea–air temperature gradient by advecting cold and dry air from continents and by imposing changes in wind-driven oceanic processes that affect sea surface temperature (SST). The pattern of air temperature anomalies dominates over the pattern of SST anomalies and dictates the pattern of decadal SHF variability.The study is supported by the NOAA Office of Climate Observations (OCO) and the WHOI Arctic Climate Initiative. X. Song acknowledges the support from the China Scholarship Council, National Natural Science Foundation of China (NSFC) (40930844, 40976004, and 40921004) and the Ministry of Education’s 111 Project (B07036).2012-11-1

A Cost-sensitive Intelligent Prediction Model for Outsourced Software Project Risk

Outsourced software project is one of the main ways of software development, which is of high failure rate. Intelligent risk prediction model can help identify high risk project in time. However, the existing models are mostly based on such a hypothesis that all the cost of misclassification is equal, which is not consistent with the reality that in the domain of software project risk prediction, the cost of predicting a fail-prone project as a success-prone project is different from predicting a success-prone project as a fail-prone project. To the best of our knowledge, the cost-sensitive learning method has not yet been applied in the domain of outsourced software project risk management though it has been widely used in a variety of fields. Based on this situation, we selected five classifiers, and introduced cost-sensitive learning method to build intelligent prediction models respectively. This paper totally collected 292 real data of outsourced software project for modeling. Experiment results showed that, under cost-sensitive scenario, the polynomial kernel support vector machine is the best classifier for outsourced software project risk prediction among the five classifiers due to its high prediction accuracy, stability and low cost

Efficient and Scalable Listing of Four-Vertex Subgraph

Identifying four-vertex subgraphs has long been recognized as a fundamental technique in bioinformatics and social networks. However, listing these structures is a challenging task, especially for graphs that do not fit in RAM. To address this problem, we build a set of algorithms, models, and implementations that can handle massive graphs on commodity hardware. Our technique achieves 4 – 5 orders of magnitude speedup compared to the best prior methods on graphs with billions of edges, with external-memory operation equally efficient

Early warning research on enterprise carbon emission reduction credit risk based on deep learning model under unbalanced data

To enhance the precision of predicting enterprise credit risk related to carbon emission reduction, this study focuses on publicly traded companies. It introduces a risk early warning model grounded in MLP deep learning. Primarily, this research employs the FA-TOPSIS fusion model to comprehensively assess the credit risk associated with carbon emission reduction in enterprises. Subsequently, it employs K-means clustering to compute enterprise similarities, which forms the basis for supervised learning in the MLP model to assign credit risk grade labels. Furthermore, the study tackles the challenge of imbalanced enterprise grade distribution using the ADASYN over-sampling algorithm. Ultimately, the effectiveness of the model proposed herein is confirmed through a series of multi-model comparison experiments. The results show that: First, carbon emission reduction indicators exhibit differing degrees of influence on enterprises at various credit risk levels. Notably, the most influential indicator is carbon emission intensity, while the development capacity indicator exerts the least influence. Second, the adoption of the XGBoost algorithm for screening carbon emission reduction indicators significantly enhances the prediction accuracy of the early warning model by 4.27%. Third, compared to other models, the MLP model achieves an impressive prediction accuracy of 99.48%, representing an average improvement of 15.24%. These results underscore the model’s feasibility and its potential to provide technical support for financial institutions and government entities in conducting credit ratings for enterprise carbon emission reduction

Soft liver phantom with a hollow biliary system

Einleitung: Die flexible Endoskopie bietet eine ständig wachsende Zahl innovativer diagnostischer und therapeutischer Möglichkeiten bei hepatobiliären Erkrankungen. Diese fortschrittlichen Verfahren, die mitunter komplex und gar nicht so selten mit relevanten Komplikationen verbunden sind, erfordern spezielle technische Fertigkeiten, ein profundes anatomisches Wissen und eine lange Lernkurve, die praktisch trainiert werden muss. Für ein patientenunabhängiges Training endoskopischer und endosonographischer Eingriffe sollte ein weiches, naturgetreues und langlebiges Leberorganmodell mit detaillierter Morphologie zur Verfügung stehen. In dieser Arbeit wird ein praktikables und kostengünstiges selbst hergestelltes weiches Lebermodell mit anatomisch korrektem Gallensystem vorgestellt. Methode: Mit Hilfe von 3D-Druck- und Weichstoffformungstechnologien wurde ein nahezu realistisches Lebermodell mit einem komplexen, hohlen Gallensystem hergestellt. Die Anatomie des Lebermodells wurde mittels Computertomographie (CT), Ultraschall und Endoskopie validiert. Nach Aufbereitung und Auswertung der Bildgebung wurden interventionelle transhepatische Eingriffe eingeleitet. Zur Validierung der Trainingseffekte und der individuellen Kompetenz wurde ein genaues Bewertungssystem für den transhepatischen Zugang etabliert. Ergebnisse: Ein realistisches Lebermodell wurde erfolgreich entwickelt und hergestellt. Die CT-Ergebnisse zeigen, dass das Lebermodell die detaillierte Anatomie wiedergibt, mit einem räumlichen Root Mean Square Error (RMSE) von 0,9 ± 0,2 mm und 1,7 ± 0,7 mm für die äußere Form bzw. den Gallengang. Das endosonographische Bild des Modells ist realistisch und die Dimension der Gallengänge ist konsistent. Die transhepatische Punktion der Gallengänge war durchführbar und ein elektronisches Abtastsystem zur quantitativen Lokalisierung der transhepatischen Nadel in Echtzeit war erfolgreich möglich. Schlussfolgerung: Das vorgestellte künstliche Lebermodell für das endoskopische und endosonografische Training kommt der Realität einer normalen Leber sehr nahe, ist kostengünstig, einfach zu reproduzieren und für die Serienproduktion geeignet. Mit dem elektronischen Sensormodul lässt sich der Trainingserfolg objektiv kontrollieren. Neben der transhepatischen Punktion könnten an diesem Modell weitere Eingriffe trainiert werden, wie z. B. endoskpischen retrograden Cholangiopankreatographie (ERCP), perkutane transhepatische Cholangiographie oder choliangiographische Drainage (PTC/PTCD), perkutane holedochofiberoskopie (POC), endoskopische ultraschallgeführte biliäre Drainage (EUS-BD)

Distinct DNA Replication Programs in Tetrahymena Thermophila

DNA replication is a vital process to duplicate genetic material for inheritance. A conventional mitotic cell cycle is composed of G1, S, G2 and M phases, and DNA is replicated during S phase. Besides the conventional cell cycle, there are other distinct replication programs. Here in my dissertation, I used the organism Tetrahymena thermophila to study DNA replication because it employs alternative DNA replication programs, such as genome-wide endoreplication, locus-specific gene amplification and an unprecedented DNA replication program in cells that are recovered from hydroxyurea (HU) induced replication stress. In my dissertation research, I determined that ribosomal DNA (rDNA) minichromosome amplification occurs when non-rDNA chromosomes are undergoing endoreplication during Tetrahymena development, and that both programs are shut down simultaneously. I found that rDNA amplification is then switched to endoreplication upon refeeding when the levels of the initiation proteins, the origin recognition complex (ORC) and the minichromosome maintenance protein complex (MCM2-7) are dramatically reduced. During this stage, the rDNA origin is not utilized, and a higher origin density was observed on a genome-wide scale. These data indicate that origin utilization is altered for endoreplication and suggest an ORC-independent initiation mechanism. More importantly, rDNA replication intermediates that are accumulated in both wild type endoreplication and vegetative S phase of a histone monomethyltransferase defective strain TXR1Δ share the same signature, suggesting epigenetic modifications may be involved in replication initiation and elongation during endoreplication. As part of my dissertation research, I studied a DNA replication program that occurs after ORC and MCM proteins are degraded in hydroxyurea treated cells. I found that replication forks are arrested rather than slowed down upon HU treatment, when the protein levels of ORC and MCMs are degraded. I detected new origin firing on a genome-wide scale upon HU removal, before the protein levels of ORC and MCMs are restored. Moreover, the rDNA origin that is used for vegetative S phase is not utilized in this specialized replication program. The collective data suggest that an ORC-independent initiation is utilized. In summary, my research has led to new discoveries of distinct DNA replication initiation and elongation mechanisms in eukaryotes

Evaluation of iron transport from ferrous glycinate liposomes using Caco-2 cell model

Background: Iron fortification of foods is currently a strategy employed to fight iron deficiency in countries. Liposomes were assumed to be a potential carrier of iron supplements.Objective: The objective of this study was to investigate the iron transport from ferrous glycinate liposomes, and to estimate the effects of liposomal carriers, phytic acid, zinc and particle size on iron transport using Caco-2 cell models.Methods: Caco-2 cells were cultured and seeded in DMEM medium. Minimum essential medium was added to the basolateral side. Iron liposome suspensions were added to the apical side of the transwell.Results: The iron transport from ferrous glycinate liposomes was significantly higher than that from ferrous glycinate. In the presence of phytic acid or zinc ion, iron transport from ferrous glycinate liposomes and ferrous glycinate was evidently inhibited, and iron transport decreased with increasing phytic acid concentration. Iron transport was decreased with increase of particle size increasing of ferrous glycinate liposome.Conclusion: Liposomes could behave as more than a simple carrier, and iron transport from liposomes could be implemented via a mechanism different from the regulated non-heme iron pathway.Keywords: Ferrous glycinate liposomes, iron transport, phytic acid, particle siz

A Stabilizer Formalism for Infinitely Many Qubits

The study of infinite dimensional quantum systems has been an active area of discussion in quantum information theory, particularly in settings where certain properties are shown to be not attainable by any finite dimensional system (such as nonlocal correlations). Similarly, the notion of stabilizer states has yielded interesting developments in areas like error correction, efficient simulation of quantum systems and its relation to graph states. However, the commonly used model of tensor products of finite dimensional Hilbert spaces is not sufficiently general to capture infinite dimensional stabilizer states. A more general framework quantum mechanical systems using C*-algebras has been instrumental in studying systems with an infinite number of discrete systems in quantum statistical mechanics and quantum field theory. We propose a framework in the C*-algebra model (specifically, the CAR algebra) for the stabilizer formalism that extends to infinitely many qubits. Importantly, the stabilizer states on the CAR algebra form a class of states that can attain unbounded entanglement and yet has a simple characterization through the group structure of its stabilizer. In this framework, we develop a theory for the states, operations and measurements needed to study open questions in quantum information