An MRI-Derived Definition of MCI-to-AD Conversion for Long-Term, Automati c Prognosis of MCI Patients

Alzheimer's disease (AD) and mild cognitive impairment (MCI), continue to be widely studied. While there is no consensus on whether MCIs actually "convert" to AD, the more important question is not whether MCIs convert, but what is the best such definition. We focus on automatic prognostication, nominally using only a baseline image brain scan, of whether an MCI individual will convert to AD within a multi-year period following the initial clinical visit. This is in fact not a traditional supervised learning problem since, in ADNI, there are no definitive labeled examples of MCI conversion. Prior works have defined MCI subclasses based on whether or not clinical/cognitive scores such as CDR significantly change from baseline. There are concerns with these definitions, however, since e.g. most MCIs (and ADs) do not change from a baseline CDR=0.5, even while physiological changes may be occurring. These works ignore rich phenotypical information in an MCI patient's brain scan and labeled AD and Control examples, in defining conversion. We propose an innovative conversion definition, wherein an MCI patient is declared to be a converter if any of the patient's brain scans (at follow-up visits) are classified "AD" by an (accurately-designed) Control-AD classifier. This novel definition bootstraps the design of a second classifier, specifically trained to predict whether or not MCIs will convert. This second classifier thus predicts whether an AD-Control classifier will predict that a patient has AD. Our results demonstrate this new definition leads not only to much higher prognostic accuracy than by-CDR conversion, but also to subpopulations much more consistent with known AD brain region biomarkers. We also identify key prognostic region biomarkers, essential for accurately discriminating the converter and nonconverter groups

Distributed k-core view materialization and maintenance for large dynamic graphs

Cataloged from PDF version of article.In graph theory, k-core is a key metric used to identify subgraphs of high cohesion, also known as the ‘dense’ regions of a graph. As the real world graphs such as social network graphs grow in size, the contents get richer and the topologies change dynamically, we are challenged not only to materialize k-core subgraphs for one time but also to maintain them in order to keep up with continuous updates. Adding to the challenge is that real world data sets are outgrowing the capacity of a single server and its main memory. These challenges inspired us to propose a new set of distributed algorithms for k-core view construction and maintenance on a horizontally scaling storage and computing platform. Our algorithms execute against the partitioned graph data in parallel and take advantage of k-core properties to aggressively prune unnecessary computation. Experimental evaluation results demonstrated orders of magnitude speedup and advantages of maintaining k-core incrementally and in batch windows over complete reconstruction. Our algorithms thus enable practitioners to create and maintain many k-core views on different topics in rich social network content simultaneously

Derivation of Del180 from sediment core log data\u27 Implications for millennial-scale climate change in the Labrador Sea

Sediment core logs from six sediment cores in the Labrador Sea show millennial-scale climate variability during the last glacial by recording all Heinrich events and several major Dansgaard-Oeschger cycles. The same millennial-scale climate change is documented for surface water δ18O records of Neogloboquadrina pachyderma (left coiled); hence the surface water δ18O record can be derived from sediment core logging by means of multiple linear regression, providing a paleoclimate proxy record at very high temporal resolution (70 years). For the Labrador Sea, sediment core logs contain important information about deepwater current velocities and also reflect the variable input of ice-rafted debris from different sources as inferred from grain-size analysis, the relation of density and P wave velocity, and magnetic susceptibility. For the last glacial, faster deepwater currents, which correspond to highs in sediment physical properties, occurred during iceberg discharge and lasted from several centuries to a few millennia. Those enhanced currents might have contributed to increased production of intermediate waters during times of reduced production of North Atlantic Deep Water. Hudson Strait might have acted as a major supplier of detrital carbonate only during lowered sea level (greater ice extent). During coldest atmospheric temperatures over Greenland, deepwater currents increased during iceberg discharge in the Labrador Sea, then surface water freshened shortly thereafter, while the abrupt atmospheric temperature rise happened after a larger time lag of ≥ 1 kyr. The correlation implies a strong link and common forcing for atmosphere, sea surface, and deep water during the last glacial at millennial timescales but decoupling at orbital timescales

Efficient community identification and maintenance at multiple resolutions on distributed datastores

The topic of network community identification at multiple resolutions is of great interest in practice to learn high cohesive subnetworks about different subjects in a network. For instance, one might examine the interconnections among web pages, blogs and social content to identify pockets of influencers on subjects like 'Big Data', 'smart phone' or 'global warming'. With dynamic changes to its graph representation and content, the incremental maintenance of a community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. In this paper, we first formalize this problem using the k-core metric projected at multiple k-values, so that multiple community resolutions are represented with multiple k-core graphs. Recognizing that large graphs and their even larger attributed content cannot be stored and managed by a single server, we then propose distributed algorithms to construct and maintain a multi-k-core graph, implemented on the scalable Big Data platform Apache HBase. Our experimental evaluation results demonstrate orders of magnitude speedup by maintaining multi-k-core incrementally over complete reconstruction. Our algorithms thus enable practitioners to create and maintain communities at multiple resolutions on multiple subjects in rich network content simultaneously. © 2015 Elsevier B.V. All rights reserved

Multi-resolution social network community identification and maintenance on big data platform

Community identification in social networks is of great interest and with dynamic changes to its graph representation and content, the incremental maintenance of community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. In this paper, we first formalize this problem using the k-core metric projected at multiple k values, so that multiple community resolutions are represented with multiple k-core graphs. We then present distributed algorithms to construct and maintain a multi-k-core graph, implemented on the scalable big-data platform Apache HBase. Our experimental evaluation results demonstrate orders of magnitude speedup by maintaining multi-k-core incrementally over complete reconstruction. Our algorithms thus enable practitioners to create and maintain communities at multiple resolutions on different topics in rich social network content simultaneously. © 2013 IEEE

Silica material variation for the Mn_xO_y-Na₂WO₄/SiO₂

The oxidative coupling of methane (OCM) is one of the best methods for the direct conversion of methane.Among the known OCM catalysts, MnxOy-Na2WO4/SiO2 is a promising candidate for an industrial appli-cation, showing a high methane conversion and C2 selectivity, with a good stability during long-termcatalytic activity tests. In the present study, some results have been already published and discussedbriefly in our previous short communication. However, we herein investigated comprehensively theinfluence of various silica support materials on the performance of the MnxOy-Na2WO4/SiO2 systemin the OCM by means of ex situ and in situ XRD, BET, SEM and TEM characterization methods andshowed new results to reveal possible support effects on the catalyst. The catalytic performance of most MnxOy-Na2WO4/SiO2 catalysts supported by different silica support materials did not differ substan-tially. However, the performance of the SBA-15 supported catalyst was outstanding and the methaneconversion was nearly twofold higher in comparison to the other silica supported catalysts at similar C2 selectivity as shown before in the communication. The reason of this substantial increase in performancecould be the ordered mesoporous structure of the SBA-15 support material, homogeneous dispersion ofactive components and high number of active sites responsible for the OCM

Graph aware caching policy for distributed graph stores

Graph stores are becoming increasingly popular among NOSQL applications seeking flexibility and heterogeneity in managing linked data. Conceptually and in practice, applications ranging from social networks, knowledge representations to Internet of things benefit from graph data stores built on a combination of relational and non-relational technologies aimed at desired performance characteristics. The most common data access pattern in querying graph stores is to traverse from a node to its neighboring nodes. This paper studies the impact of such traversal pattern to common data caching policies in a partitioned data environment where a big graph is distributed across servers in a cluster. We propose and evaluate a new graph aware caching policy designed to keep and evict nodes, edges and their metadata optimized for query traversal pattern. The algorithm distinguishes the topology of the graph as well as the latency of access to the graph nodes and neighbors. We implemented graph aware caching on a distributed data store Apache HBase in the Hadoop family. Performance evaluations showed up to 15x speedup on the benchmark datasets preferring our new graph aware policy over non-aware policies. We also show how to improve the performance of existing caching algorithms for distributed graphs by exploiting the topology information. © 2015 IEEE

A novel approach for preventing esophageal stricture formation: olmesartan prevented apoptosis

Accidentally ingested corrosive substances can cause functional and structural damage to the esophageal tissue resulting in stricture formation. It has been reported that the administration of olmesartan (OLM) can have anti-inflammatory, antifibrotic and antiapoptotic effects on injured tissue. The aim of our study was to check if OLM could prevent formation of scars in the corrosive esophageal burn model. Fifty-one Wistar Albino rats were divided into six groups: Control, Sham, OLM, Sham + OLM, Burn, and Burn + OLM. Olmesartan (5 mg/kg) was given by gavage once per day for 21 consecutive days after injury. The morphology of the esophagus was assessed after Masson trichrome staining, and apoptosis was evaluated using the terminal deoxynucleotidyl transferased UTP nick end labeling (TUNEL) method. The serum nucleosomes (as an indicator of apoptosis), serum p53 protein, and esophageal tissue p53 protein levels of each group were measured by immunoassays. Muscularis mucosa damage, submucosal collagen deposition, and tunica muscularis injury in the Burn + OLM group decreased significantly compared with the Burn group (p < 0.05). Similarly, the number of apoptotic cells in the Burn + OLM group decreased compared with the Burn group (p < 0.05). Serum levels of nucleosomes and p53 and tissue of p53 protein did not differ between the groups. Exogenously administered OLM can effectively prevent the occurrence of esophageal strictures caused by corrosive esophageal burns. (Folia Histochemica et Cytobiologica 2014, Vol. 52, No. 1, 29–35

Evaluation of Fescue (Festuca arundinacea Schreb. and Festuca rubra L.) Populations Grown under Aegean Region Conditions

Ege Bölgesine uyumlu tür ve populasyonları belirlemek için kamışsı yumak (Festuca arundinacea Schreb.) ve kırmızı yumak (Festuca rubra L.) türlerine ait toplam 43 adet populasyon 2002 ve 2004 yılları arasında Ege Tarımsal Araştırma Enstitiüsü (ETAE) deneme tarlasında gözlemlendi. Populasyonlar 2001 yılında multipodlarda çimlendirildikten sonar 2002 yılının ilkbaharında 1m x1 m aralıkla tarlaya aktarıldı. İncelenen özellikler; kardeşlenme, ilkbahar büyüme hızı, yüzde elli başaklanma, başaklanma durumu, başaklanmada bitki gelişim özelliği, bitki boyu, biçimden sonra büyüme hızı, kuru madde ve tohum verimi olmuştur. İncelenen karakterler açısından populasyonlar arasında önemli farklılıklar gözlenmiştir. Kamışsı yumak populasyonlarından daha fazla kuru madde verimi alınmıştır. İlkbahar gelişim hızları açısından populasyonlar arası önemli farklılıklar tespit edilmiştir. Kamışsı yumak populasyonları daha yüksek ilkbahar gelişme hızı göstermişlerdir. Yüzde elli başaklanma türler ve populasyonlar arsında erkenciden geççiye kadar değişim göstermiştir. Genel olarak kırmızı yumak populasyonları daha erkenci başaklanma özelliğine ve daha yüksek başaklanma potansiyeline sahip olmuşlardır. Biçim sonrası büyüme açısından da populasyonlar arasında önemli farklılıklar bulunmuştur. Kamışsı yumak populasyonları daha yüksek büyüme potansiyeli göstermiştir. Kamışsı ve kırmızı yumak türlerinin bu çalışma ile Ege Bölgesinde farklı amaçlar için kullanılabileceği tesbit edilmiştir.A total of 43 materials of tall fescue (Festuca arundinacea Schreb.) and red fescue (Festuca rubra L.) were examined at experimental fields of Aegean Agricultural Research Institute (AARI) in the years of 2002 and 2004 in order to determine adaptation of species, populations and high yielding cultivars adapting to Aegean region. Populations were sown in multipods in 2001 and transferred to field with 1x1 m spacing in the spring of 2002. Characteristics observed were tillering, spring growth rate, time of 50 % inflorescence, abundance of inflorence, vegetative growth habit at inflorence, plant height, growth rate after cutting, dry matter yield and seed yield. Significant differences were observed between populations in terms of characters investigated. Dry matter yield was higher in tall fescue. There were significant differences between the populations in terms of spring growth. Tall fescue populations had higher spring growth rates. Flowering time of 50 % inflorescence of species and populations varied from early to late. In general, populations of red fescue had early 50% inflorescence time and also higher potential for abundance of inflorence. Significant differences were also found between populations in terms of their growth rate after cutting. Tall fescue populations showed higher growth potential. It was found that tall fescue and red fescue could be used with various purposes at Aegean Region