Equation of motion approach to the Hubbard model in infinite dimensions

We consider the Hubbard model on the infinite-dimensional Bethe lattice and construct a systematic series of self-consistent approximations to the one-particle Green's function, $G^{(n)}(\omega),\ n=2,3,\dots\$ . The first $n-1$ equations of motion are exactly fullfilled by $G^{(n)}(\omega)$ and the $n$'th equation of motion is decoupled following a simple set of decoupling rules. $G^{(2)}(\omega)$ corresponds to the Hubbard-III approximation. We present analytic and numerical results for the Mott-Hubbard transition at half filling for $n=2,3,4$.Comment: 10pager, REVTEX, 8-figures not available in postscript, manuscript may be understood without figure

Change Mining in Adaptive Process Management Systems

The wide-spread adoption of process-aware information systems has resulted in a bulk of computerized information about real-world processes. This data can be utilized for process performance analysis as well as for process improvement. In this context process mining offers promising perspectives. So far, existing mining techniques have been applied to operational processes, i.e., knowledge is extracted from execution logs (process discovery), or execution logs are compared with some a-priori process model (conformance checking). However, execution logs only constitute one kind of data gathered during process enactment. In particular, adaptive processes provide additional information about process changes (e.g., ad-hoc changes of single process instances) which can be used to enable organizational learning. In this paper we present an approach for mining change logs in adaptive process management systems. The change process discovered through process mining provides an aggregated overview of all changes that happened so far. This, in turn, can serve as basis for all kinds of process improvement actions, e.g., it may trigger process redesign or better control mechanisms

Initial spare parts assortment decision making for rolling stock maintenance: a structured approach

Design for maintenance and maintenance operations become increasingly important in recent years. In the capital-intensive industry, maintenance expenditures can add up to several times the initial investment. In order to be competitive in their business, owners and users of these capital goods have to take into account the total life cycle cost at investment (the lifespan of a train is about 30 years), the renewal decisions for their installations and the logistic management of the spare parts. Erroneous or unstructured initial spare parts assortment decision-making part of the logistic management can lead to undesired downtime and increases the risk of obsolete or unavailable components. Decision making is further complicated by non- existent data in the early design phase and several information management problems. Based on a case study at NedTrain (the largest maintainer of rolling stock in the Netherlands) and literature review a Decision Support Model to structure and to improve the initial spare part assortment for the rolling stock maintenance is proposed

Integrative DNA methylome analysis of pan-cancer biomarkers in cancer discordant monozygotic twin-pairs

BACKGROUND: A key focus in cancer research is the discovery of biomarkers that accurately diagnose early lesions in non-invasive tissues. Several studies have identified malignancy-associated DNA methylation changes in blood, yet no general cancer biomarker has been identified to date. Here, we explore the potential of blood DNA methylation as a biomarker of pan-cancer (cancer of multiple different origins) in 41 female cancer discordant monozygotic (MZ) twin-pairs sampled before or after diagnosis using the Illumina HumanMethylation450 BeadChip. RESULTS: We analysed epigenome-wide DNA methylation profiles in 41 cancer discordant MZ twin-pairs with affected individuals diagnosed with tumours at different single primary sites: the breast, cervix, colon, endometrium, thyroid gland, skin (melanoma), ovary, and pancreas. No significant global differences in whole blood DNA methylation profiles were observed. Epigenome-wide analyses identified one novel pan-cancer differentially methylated position at false discovery rate (FDR) threshold of 10 % (cg02444695, P = 1.8 × 10(-7)) in an intergenic region 70 kb upstream of the SASH1 tumour suppressor gene, and three suggestive signals in COL11A2, AXL, and LINC00340. Replication of the four top-ranked signals in an independent sample of nine cancer-discordant MZ twin-pairs showed a similar direction of association at COL11A2, AXL, and LINC00340, and significantly greater methylation discordance at AXL compared to 480 healthy concordant MZ twin-pairs. The effects at cg02444695 (near SASH1), COL11A2, and LINC00340 were the most promising in biomarker potential because the DNA methylation differences were found to pre-exist in samples obtained prior to diagnosis and were limited to a 5-year period before diagnosis. Gene expression follow-up at the top-ranked signals in 283 healthy individuals showed correlation between blood methylation and gene expression in lymphoblastoid cell lines at PRL, and in the skin tissue at AXL. A significant enrichment of differential DNA methylation was observed in enhancer regions (P = 0.03). CONCLUSIONS: We identified DNA methylation signatures in blood associated with pan-cancer, at or near SASH1, COL11A2, AXL, and LINC00340. Three of these signals were present up to 5 years prior to cancer diagnosis, highlighting the potential clinical utility of whole blood DNA methylation analysis in cancer surveillance

Molecular oxygen as a signaling component in plant development

While traditionally hypoxia has been studied as a detrimental component of flooding stress, the last decade has flourished with studies reporting the involvement of molecular oxygen availability in plant developmental processes. Moreover, proliferating and undifferentiated cells from different plant tissues were found to reside in endogenously generated hypoxic niches. Thus, stress-associated acute hypoxia may be distinguished from constitutively generated chronic hypoxia. The Cys/Arg branch of the N-degron pathway assumes a central role in integrating oxygen levels resulting in proteolysis of transcriptional regulators that control different aspects of plant growth and development. As a target of this pathway, group VII of the Ethylene Response Factor (ERF-VII) family has emerged as a hub for the integration of oxygen dynamics in root development and during seedling establishment. Additionally, vegetative shoot meristem activity and reproductive transition were recently associated with oxygen availability via two novel substrates of the N-degron pathways: VERNALISATION 2 (VRN2) and LITTLE ZIPPER 2 (ZPR2). Together, these observations support roles for molecular oxygen as a signalling molecule in plant development, as well as in essential metabolic reactions. Here, we review recent findings regarding oxygen-regulated development, and discuss outstanding questions that spring from these discoveries

Charge-density-wave order parameter of the Falicov-Kimball model in infinite dimensions

In the large-U limit, the Falicov-Kimball model maps onto an effective Ising model, with an order parameter described by a BCS-like mean-field theory in infinite dimensions. In the small-U limit, van Dongen and Vollhardt showed that the order parameter assumes a strange non-BCS-like shape with a sharp reduction near T approx T_c/2. Here we numerically investigate the crossover between these two regimes and qualitatively determine the order parameter for a variety of different values of U. We find the overall behavior of the order parameter as a function of temperature to be quite anomalous.Comment: (5 pages, 3 figures, typeset with ReVTeX4

Integrating computer log files for process mining: a genetic algorithm inspired technique

Process mining techniques are applied to single computer log files. But many processes are supported by different software tools and are by consequence recorded into multiple log files. Therefore it would be interesting to find a way to automatically combine such a set of log files for one process. In this paper we describe a technique for merging log files based on a genetic algorithm. We show with a generated test case that this technique works and we give an extended overview of which research is needed to optimise and validate this technique