bluuebunny/crossref_metadata_2025 huggingface dataset:
Composing Effective and Efficient E-mails: A Primer for Pharmacy Practitioners
Authors: Summerfield Marc R. , Feemster Agnes Ann
Published: September 2015

This primer describes the purpose and importance of e-mail as a key communication medium in the workplace. It emphasizes clarity as a primary modality to enhance efficiency and effectiveness. Finally, the primer reviews elements of grammar, punctuation, and style that contribute to each e-mail's ability to meet language standards, enhance the writer's image, and successfully transmit information.
Secukinumab
Authors: Cada Dennis J. , Baker Danial E. , Panther Shannon G. , PharmD Kyle Ingram
Published: September 2015

Each month, subscribers to The Formulary Monograph Service receive 5 to 6 well-documented monographs on drugs that are newly released or are in late phase 3 trials. The monographs are targeted to Pharmacy & Therapeutics Committees. Subscribers also receive monthly 1-page summary monographs on agents that are useful for agendas and pharmacy/nursing in-services. A comprehensive target drug utilization evaluation/medication use evaluation (DUE/MUE) is also provided each month. With a subscription, the monographs are sent in print and are also available on-line. Monographs can be customized to meet the needs of a facility. A drug class review is now published monthly with The Formulary Monograph Service. Through the cooperation of The Formulary, Hospital Pharmacy publishes selected reviews in this column. For more information about The Formulary Monograph Service, call The Formulary at 800-322-4349. The September 2015 monograph topics are cangrelor, lumacaftor/ivacaftor, brexpiprazole, talimogene laherparepvec, and lesinurad. The Safety MUE is on cangrelor.
Bringing Home Participatory Health Care
Authors: Fox Brent I. , Felkey Bill G.
Published: September 2015

Following another hospital stay, we have new observations on what it means to address patient needs. Some efforts are founded in technology, while others focus on the process of care. As a member of the broader care team, pharmacy should be aware of and engaged in institutional efforts focused on the patient experience.
Correlative Light and Scanning Electron Microscopy for Observing the Three-Dimensional Ultrastructure of Membranous Cell Organelles in Relation to Their Molecular Components
Authors: Koga Daisuke , Kusumi Satoshi , Bochimoto Hiroki , Watanabe Tsuyoshi , Ushiki Tatsuo
Published: September 2015

Although the osmium maceration method has been used to observe three-dimensional (3D) structures of membranous cell organelles with scanning electron microscopy (SEM), the use of osmium tetroxide for membrane fixation and the removal of cytosolic soluble proteins largely impairs the antigenicity of molecules in the specimens. In the present study, we developed a novel method to combine cryosectioning with the maceration method for correlative immunocytochemical analysis. We first immunocytochemically stained a semi-thin cryosection cut from a pituitary tissue block with a cryo-ultramicrotome, according to the Tokuyasu method, before preparing an osmium-macerated specimen from the remaining tissue block. Correlative microscopy was performed by observing the same area between the immunostained section and the adjacent face of the tissue block. Using this correlative method, we could accurately identify the gonadotropes of pituitary glands in various experimental conditions with SEM. At 4 weeks after castration, dilated cisternae of rough endoplasmic reticulum (RER) were distributed throughout the cytoplasm. On the other hand, an extremely dilated cisterna of the RER occupied the large region of the cytoplasm at 12 weeks after castration. This novel method has the potential to analyze the relationship between the distribution of functional molecules and the 3D ultrastructure in different composite tissues.
Application of Fluorescence Based Molecular Assays for Improved Detection and Typing of Brucella Strains in Clinical Samples
Authors: Krstevski Kiril , Naletoski Ivancho , Mitrov Dine , Mrenoshki Slavcho , Cvetkovikj Iskra , Janevski Aleksandar , Dodovski Aleksandar , Djadjovski Igor
Published: September 2015

Bacteria from the genus Brucella are causative agents of brucellosis - a zoonotic disease which affects many wild and domestic animal species and humans. Taking into account the significant socio-economic and public health impact of brucellosis, its control is of great importance for endemic areas. The chosen control strategy could be successful only if adapted to the current epidemiological situation. This implies that a choice of appropriate diagnostic procedures for detection and typing of Brucella spp. strains are of essential importance. Significant advancement of molecular techniques and their advantages compared to classical methods, give strong arguments in promotion of these techniques as a powerful tool for comprehensive diagnostics of brucellosis. Considering this, the major tasks of the study were to select and implement molecular tests for detection and genotyping Brucella spp. and evaluate their performances using DNA from cultivated brucellae (islolates) and limited number of tissue samples from seropositive animals. The obtained results confirmed that implemented real time PCR for Brucella spp. detection, as well as MLVA-16 used for genotyping, have excellent analytical sensitivity (4.2 fg of Brucella DNA were successfully detected and genotyped). Furthermore, compared to bacteriological cultivation of Brucella spp., real time PCR and MLVA-16 protocols showed superior diagnostic sensitivity and detected Brucella DNA in tissues from which Brucella could not be cultivated. Based on the summarized study results, we propose a diagnostic algorithm for detection and genotyping of Brucella spp. bacteria. Routine use of proposed diagnostic algorithm will improve the effectiveness of infection confirmation and help for accurate evaluation of epidemiological situation.
Aggregate estimations over location based services
Authors: Liu Weimo , Rahman Md Farhadur , Thirumuruganathan Saravanan , Zhang Nan , Das Gautam
Published: September 2015

Location based services
(LBS) have become very popular in recent years. They range from map services (e.g., Google Maps) that store geographic locations of points of interests, to online social networks (e.g., WeChat, Sina Weibo, FourSquare) that leverage user geographic locations to enable various recommendation functions. The public query interfaces of these services may be abstractly modeled as a
k
NN interface over a database of two dimensional points on a plane: given an arbitrary query point, the system returns the
k
points in the database that are nearest to the query point. In this paper we consider the problem of obtaining
approximate estimates
of SUM and COUNT aggregates by only querying such databases via their restrictive public interfaces. We distinguish between interfaces that return location information of the returned tuples (e.g., Google Maps), and interfaces that do not return location information (e.g., Sina Weibo). For both types of interfaces, we develop aggregate estimation algorithms that are based on novel techniques for precisely computing or approximately estimating the Voronoi cell of tuples. We discuss a comprehensive set of real-world experiments for testing our algorithms, including experiments on Google Maps, WeChat, and Sina Weibo.
Principles of dataset versioning
Authors: Bhattacherjee Souvik , Chavan Amit , Huang Silu , Deshpande Amol , Parameswaran Aditya
Published: September 2015

The relative ease of collaborative data science and analysis has led to a proliferation of many thousands or millions of
versions
of the same datasets in many scientific and commercial domains, acquired or constructed at various stages of data analysis across many users, and often over long periods of time. Managing, storing, and recreating these dataset versions is a non-trivial task. The fundamental challenge here is the
storage-recreation trade-off
: the more storage we use, the faster it is to recreate or retrieve versions, while the less storage we use, the slower it is to recreate or retrieve versions. Despite the fundamental nature of this problem, there has been a surprisingly little amount of work on it. In this paper, we study this trade-off in a principled manner: we formulate six problems under various settings, trading off these quantities in various ways, demonstrate that most of the problems are intractable, and propose a suite of inexpensive heuristics drawing from techniques in delay-constrained scheduling, and spanning tree literature, to solve these problems. We have built a prototype version management system, that aims to serve as a foundation to our D
ata
H
ub
system for facilitating collaborative data science. We demonstrate, via extensive experiments, that our proposed heuristics provide efficient solutions in practical dataset versioning scenarios.
Stale view cleaning
Authors: Krishnan Sanjay , Wang Jiannan , Franklin Michael J. , Goldberg Ken , Kraska Tim
Published: September 2015

Materialized views (MVs), stored pre-computed results, are widely used to facilitate fast queries on large datasets. When new records arrive at a high rate, it is infeasible to continuously update (maintain) MVs and a common solution is to defer maintenance by batching updates together. Between batches the MVs become increasingly stale with incorrect, missing, and superfluous rows leading to increasingly inaccurate query results. We propose Stale View Cleaning (SVC) which addresses this problem from a data cleaning perspective. In SVC, we efficiently clean a sample of rows from a stale MV, and use the clean sample to estimate aggregate query results. While approximate, the estimated query results reflect the most recent data. As sampling can be sensitive to long-tailed distributions, we further explore an outlier indexing technique to give increased accuracy when the data distributions are skewed. SVC complements existing deferred maintenance approaches by giving accurate and bounded query answers between maintenance. We evaluate our method on a generated dataset from the TPC-D benchmark and a real video distribution application. Experiments confirm our theoretical results: (1) cleaning an MV sample is more efficient than full view maintenance, (2) the estimated results are more accurate than using the stale MV, and (3) SVC is applicable for a wide variety of MVs.
Take me to your leader!
Authors: Sharov Artyom , Shraer Alexander , Merchant Arif , Stokely Murray
Published: September 2015

The configuration of a distributed storage system typically includes, among other parameters, the set of servers and their roles in the replication protocol. Although mechanisms for changing the configuration at runtime exist, it is usually left to system administrators to manually determine the "best" configuration and periodically reconfigure the system, often by trial and error. This paper describes a new workload-driven optimization framework that dynamically determines the optimal configuration at run-time. We focus on optimizing leader and quorum based replication schemes and divide the framework into three optimization tiers, dynamically optimizing different configuration aspects: 1) leader placement, 2) roles of different servers in the replication protocol, and 3) replica locations. We showcase our optimization framework by applying it to a large-scale distributed storage system used internally in Google and demonstrate that most client applications significantly benefit from using our framework, reducing average operation latency by up to 94%.
Extracting logical hierarchical structure of HTML documents based on headings
Authors: Manabe Tomohiro , Tajima Keishi
Published: September 2015

We propose a method for extracting logical hierarchical structure of HTML documents. Because mark-up structure in HTML documents does not necessarily coincide with logical hierarchical structure, it is not trivial how to extract logical structure of HTML documents. Human readers, however, easily understand their logical structure. The key information used by them is headings in the documents. Human readers exploit the following properties of headings: (1) headings appear at the beginning of the corresponding blocks, (2) headings are given prominent visual styles, (3) headings of the same level share the same visual style, and (4) headings of higher levels are given more prominent visual styles. Our method also exploits these properties for extracting hierarchical headings and their associated blocks. Our experiment shows that our method outperforms existing methods. In addition, our method extracts not only hierarchical blocks but also their associated headings.
Permutation search methods are efficient, yet faster search is possible
Authors: Naidan Bilegsaikhan , Boytsov Leonid , Nyberg Eric
Published: September 2015

We survey permutation-based methods for approximate
k
-nearest neighbor search. In these methods, every data point is represented by a ranked list of pivots sorted by the distance to this point. Such ranked lists are called
permutations.
The underpinning assumption is that, for both metric and non-metric spaces, the distance between permutations is a good proxy for the distance between original points. Thus, it should be possible to efficiently retrieve most true nearest neighbors by examining only a tiny subset of data points whose permutations are similar to the permutation of a query. We further test this assumption by carrying out an extensive experimental evaluation where permutation methods are pitted against state-of-the art benchmarks (the multi-probe LSH, the VP-tree, and proximity-graph based retrieval) on a variety of realistically large data set from the image and textual domain. The focus is on the high-accuracy retrieval methods for generic spaces. Additionally, we assume that both data and indices are stored in main memory. We find permutation methods to be reasonably efficient and describe a setup where these methods are most useful. To ease reproducibility, we make our software and data sets publicly available.
Building a replicated logging system with Apache Kafka
Authors: Wang Guozhang , Koshy Joel , Subramanian Sriram , Paramasivam Kartik , Zadeh Mammad , Narkhede Neha , Rao Jun , Kreps Jay , Stein Joe
Published: September 2015

Apache Kafka is a scalable publish-subscribe messaging system with its core architecture as a distributed commit log. It was originally built at LinkedIn as its centralized event pipelining platform for online data integration tasks. Over the past years developing and operating Kafka, we extend its log-structured architecture as a replicated logging backbone for much wider application scopes in the distributed environment. In this abstract, we will talk about our design and engineering experience to replicate Kafka logs for various distributed data-driven systems at LinkedIn, including source-of-truth data storage and stream processing.
Indexing and selecting hierarchical business logic
Authors: Loro Alessandra , Gruenheid Anja , Kossmann Donald , Profeta Damien , Beaudequin Philippe
Published: September 2015

Business rule management is the task of storing and maintaining company-specific decision rules and business logic that is queried frequently by application users. These rules can impede efficient query processing when they require the business rule engine to resolve semantic hierarchies. To address this problem, this work discusses hierarchical indexes that are performance and storage-conscious. In the first part of this work, we develop a tree-based hierarchical structure that represents client-defined semantic hierarchies as well as two variants of this structure that improve performance and main memory allocation. The second part of our work focuses on selecting the top rules out of those retrieved from the index. We formally define a priority score-based decision scheme that allows for a conflict-free rule system and efficient rule ranking. Additionally, we introduce a weight-based lazy merging technique for rule selection. All of these techniques are evaluated with real world and synthetic data sets.
Towards scalable real-time analytics
Authors: Goel Anil K. , Pound Jeffrey , Auch Nathan , Bumbulis Peter , MacLean Scott , Färber Franz , Gropengiesser Francis , Mathis Christian , Bodner Thomas , Lehner Wolfgang
Published: September 2015

We present an overview of our work on the SAP HANA Scale-out Extension, a novel distributed database architecture designed to support large scale analytics over real-time data. This platform permits high performance OLAP with massive scale-out capabilities, while concurrently allowing OLTP workloads. This dual capability enables analytics over real-time changing data and allows fine grained user-specified service level agreements (SLAs) on data freshness. We advocate the decoupling of core database components such as query processing, concurrency control, and persistence, a design choice made possible by advances in high-throughput low-latency networks and storage devices. We provide full ACID guarantees and build on a logical timestamp mechanism to provide MVCC-based snapshot isolation, while not requiring synchronous updates of replicas. Instead, we use asynchronous update propagation guaranteeing consistency with timestamp validation.

We provide a view into the design and development of a large scale data management platform for real-time analytics, driven by the needs of modern enterprise customers.
Scaling spark in the real world
Authors: Armbrust Michael , Das Tathagata , Davidson Aaron , Ghodsi Ali , Or Andrew , Rosen Josh , Stoica Ion , Wendell Patrick , Xin Reynold , Zaharia Matei
Published: September 2015

Apache Spark is one of the most widely used open source processing engines for big data, with rich language-integrated APIs and a wide range of libraries. Over the past two years, our group has worked to deploy Spark to a wide range of organizations through consulting relationships as well as our hosted service, Databricks. We describe the main challenges and requirements that appeared in taking Spark to a wide set of users, and usability and performance improvements we have made to the engine in response.
StarDB
Authors: Sahli Majed , Mansour Essam , Kalnis Panos
Published: September 2015

Strings and applications using them are proliferating in science and business. Currently, strings are stored in file systems and processed using ad-hoc procedural code. Existing techniques are not flexible and cannot efficiently handle complex queries or large datasets. In this paper, we demonstrate StarDB, a distributed database system for analytics on strings. StarDB hides data and system complexities and allows users to focus on analytics. It uses a comprehensive set of parallel string operations and provides a declarative query language to solve complex queries. StarDB automatically tunes itself and runs with over 90% efficiency on supercomputers, public clouds, clusters, and workstations. We test StarDB using real datasets that are 2 orders of magnitude larger than the datasets reported by previous works.
Evaluating SPARQL queries on massive RDF datasets
Authors: Harbi Razen , Abdelaziz Ibrahim , Kalnis Panos , Mamoulis Nikos
Published: September 2015

Distributed RDF systems partition data across multiple computer nodes. Partitioning is typically based on heuristics that minimize inter-node communication and it is performed in an initial, data pre-processing phase. Therefore, the resulting partitions are static and do not adapt to changes in the query workload; as a result, existing systems are unable to consistently avoid communication for queries that are not favored by the initial data partitioning. Furthermore, for very large RDF knowledge bases, the partitioning phase becomes prohibitively expensive, leading to high startup costs.

In this paper, we propose AdHash, a distributed RDF system which addresses the shortcomings of previous work. First, AdHash initially applies lightweight hash partitioning, which drastically minimizes the startup cost, while favoring the parallel processing of join patterns on subjects, without any data communication. Using a locality-aware planner, queries that cannot be processed in parallel are evaluated with minimal communication. Second, AdHash monitors the data access patterns and adapts dynamically to the query load by incrementally redistributing and replicating frequently accessed data. As a result, the communication cost for future queries is drastically reduced or even eliminated. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds. In this demonstration, audience can use a graphical interface of AdHash to verify its performance superiority compared to state-of-the-art distributed RDF systems.
SPARTex
Authors: Abdelaziz Ibrahim , Harbi Razen , Salihoglu Semih , Kalnis Panos , Mamoulis Nikos
Published: September 2015

A growing number of applications require combining SPARQL queries with generic graph search on RDF data. However, the lack of procedural capabilities in SPARQL makes it inappropriate for graph analytics. Moreover, RDF engines focus on SPARQL query evaluation whereas graph management frameworks perform only generic graph computations. In this work, we bridge the gap by introducing SPARTex, an RDF analytics framework based on the vertex-centric computation model. In SPARTex, user-defined vertex centric programs can be invoked from SPARQL as stored procedures. SPARTex allows the execution of a pipeline of graph algorithms without the need for multiple reads/writes of input data and intermediate results. We use a cost-based optimizer for minimizing the communication cost. SPARTex evaluates queries that combine SPARQL and generic graph computations orders of magnitude faster than existing RDF engines. We demonstrate a real system prototype of SPARTex running on a local cluster using real and synthetic datasets. SPARTex has a real-time graphical user interface that allows the participants to write regular SPARQL queries, use our proposed SPARQL extension to declaratively invoke graph algorithms or combine/pipeline both SPARQL querying and generic graph analytics.
I2RS
Authors: Chen Lu , Gao Yunjun , Xing Zhihao , Jensen Christian S. , Chen Gang
Published: September 2015

Massive amounts of geo-tagged and textually annotated images are provided by online photo services such as Flickr and Zommr. However, most existing image retrieval engines only consider text annotations. We present I2RS, a system that allows users to view geo-textual images on Google Maps, find hot topics within a specific geographic region and time period, retrieve images similar to a query image, and receive recommended images that they might be interested in. I2RS is a distributed geo-textual image retrieval and recommendation system that employs SPB-trees to index geo-textual images, and that utilizes metric similarity queries, including top-
m
spatio-temporal range and
k
nearest neighbor queries, to support geo-textual image retrieval and recommendation. The system adopts the browser-server model, whereas the server is deployed in a distributed environment that enables efficiency and scalability to huge amounts of data and requests. A rich set of 100 million geo-textual images crawled from Flickr is used to demonstrate that, I2RS can return high-quality answers in an interactive way and support efficient updates for high image arrival rates.
Smart drill-down
Authors: Joglekar Manas , Garcia-Molina Hector , Parameswaran Aditya
Published: September 2015

We present a data exploration system equipped with
smart drill-down
, a novel operator for interactively exploring a relational table to discover and summarize "interesting" groups of tuples. Each such group of tuples is represented by a
rule.
For instance, the rule (
a, b
, *, 1000) tells us that there are a thousand tuples with value a in the first column and
b
in the second column (and any value in the third column). Smart drill-down presents an analyst with a list of rules that together describe interesting aspects of the table. The analyst can tailor the definition of interesting, and can interactively apply smart drill-down on an existing rule to explore that part of the table. In the demonstration, conference attendees will be able to use the data exploration system equipped with smart drill-down, and will be able to contrast smart drill-down to traditional drill-down, for various interestingness measures, and resource constraints.
Annotating database schemas to help enterprise search
Authors: Cortez Eli , Bernstein Philip A. , He Yeye , Novik Lev
Published: September 2015

In large enterprises, data discovery is a common problem faced by users who need to find relevant information in relational databases. In this scenario, schema annotation is a useful tool to enrich a database schema with descriptive keywords. In this paper, we demonstrate Barcelos, a system that automatically annotates corporate databases. Unlike existing annotation approaches that use Web oriented knowledge bases, Barcelos mines enterprise spreadsheets to find candidate annotations. Our experimental evaluation shows that Barcelos produces high quality annotations; the top-5 have an average precision of 87%.
KATARA
Authors: Chu Xu , Morcos John , Ilyas Ihab F. , Ouzzani Mourad , Papotti Paolo , Tang Nan , Ye Yin
Published: September 2015

Data cleaning with guaranteed reliability is hard to achieve without accessing external sources, since the truth is not necessarily discoverable from the data at hand. Furthermore, even in the presence of external sources, mainly knowledge bases and humans, effectively leveraging them still faces many challenges, such as aligning heterogeneous data sources and decomposing a complex task into simpler units that can be consumed by humans. We present K
atara
, a novel
end-to-end
data cleaning system powered by knowledge bases and crowdsourcing. Given a table, a
kb
, and a crowd, K
atara
(i) interprets the table semantics
w.r.t.
the given
kb
; (ii) identifies correct and wrong data; and (iii) generates top-
k
possible repairs for the wrong data. Users will have the opportunity to experience the following features of K
atara
: (1)
Easy specification:
Users can define a K
atara
job with a browser-based specification; (2)
Pattern validation:
Users can help the system to resolve the ambiguity of different table patterns (
i.e.
, table semantics) discovered by K
atara
; (3)
Data annotation:
Users can play the role of internal crowd workers, helping K
atara
annotate data. Moreover, K
atara
will visualize the annotated data as correct data validated by the
kb
, correct data jointly validated by the kb and the crowd, or erroneous tuples along with their possible repairs.
Error diagnosis and data profiling with data x-ray
Authors: Wang Xiaolan , Feng Mary , Wang Yue , Dong Xin Luna , Meliou Alexandra
Published: September 2015

The problem of identifying and repairing data errors has been an area of persistent focus in data management research. However, while traditional data cleaning techniques can be effective at identifying several data discrepancies, they disregard the fact that many errors aresystematic, inherent to the process that produces the data, and thus will keep occurring unless the root cause is identified and corrected.

In this demonstration, we will present a large-scale diagnostic framework called DataXRay. Like a medical X-ray that aids the diagnosis of medical conditions by revealing problems underneath the surface, DataXRayreveals hidden connections and common properties among data errors. Thus, in contrast to traditional cleaning methods, which treat the symptoms, our system investigates the underlying conditions that cause the errors.

The core of DataXRaycombines an intuitive and principled cost model derived by Bayesian analysis, and an efficient, highly-parallelizable diagnostic algorithm that discovers common properties among erroneous data elements in a top-down fashion. Our system has a simple interface that allows users to load different datasets, to interactively adjust key diagnostic parameters, to explore the derived diagnoses, and to compare with solutions produced by alternative algorithms. Through this demonstration, participants will understand (1) the characteristics of good diagnoses, (2) how and why errors occur in real-world datasets, and (3) the distinctions with other related problems and approaches.
WADaR
Authors: Ortona Stefano , Orsi Giorgio , Buoncristiano Marcello , Furche Tim
Published: September 2015

Web scraping (or wrapping) is a popular means for acquiring data from the web. Recent advancements have made scalable wrapper-generation possible and enabled data acquisition processes involving thousands of sources. This makes wrapper analysis and maintenance both needed and challenging as no scalable tools exists that support these tasks.

We demonstrate WADaR, a scalable and highly automated tool for joint wrapper and data repair. WADaR uses off-the-shelf entity recognisers to locate target entities in wrapper-generated data. Markov chains are used to determine structural repairs, that are then encoded into suitable repairs for both the data and corresponding wrappers.

We show that WADaR is able to increase the quality of wrapper-generated relations between 15% and 60%, and to fully repair the corresponding wrapper without any knowledge of the original website in more than 50% of the cases.
Tornado
Authors: Mahmood Ahmed R. , Aly Ahmed M. , Qadah Thamir , Rezig El Kindi , Daghistani Anas , Madkour Amgad , Abdelhamid Ahmed S. , Hassan Mohamed S. , Aref Walid G. , Basalamah Saleh
Published: September 2015

The widespread use of location-aware devices together with the increased popularity of micro-blogging applications (e.g., Twitter) led to the creation of large streams of spatio-textual data. In order to serve real-time applications, the processing of these large-scale spatio-textual streams needs to be distributed. However, existing distributed stream processing systems (e.g., Spark and Storm) are not optimized for spatial/textual content. In this demonstration, we introduce Tornado, a distributed in-memory spatio-textual stream processing server that extends Storm. To efficiently process spatio-textual streams, Tornado introduces a spatio-textual indexing layer to the architecture of Storm. The indexing layer is adaptive, i.e., dynamically re-distributes the processing across the system according to changes in the data distribution and/or query workload. In addition to keywords, higher-level textual concepts are identified and are semantically matched against spatio-textual queries. Tornado provides data deduplication and fusion to eliminate redundant textual data. We demonstrate a prototype of Tornado running against real Twitter streams, where the users can register continuous or snapshot spatio-textual queries using a map-assisted query-interface.
SQL-on-hadoop systems
Authors: Abadi Daniel , Babu Shivnath , Özcan Fatma , Pandis Ippokratis
Published: September 2015

Enterprises are increasingly using Apache Hadoop, more specifically HDFS, as a central repository for all their data; data coming from various sources, including operational systems, social media and the web, sensors and smart devices, as well as their applications. At the same time many enterprise data management tools (e.g. from SAP ERP and SAS to Tableau) rely on SQL and many enterprise users are familiar and comfortable with SQL. As a result, SQL processing over Hadoop data has gained significant traction over the recent years, and the number of systems that provide such capability has increased significantly. In this tutorial we use the term SQL-on-Hadoop to refer to systems that provide some level of declarative SQL(-like) processing over HDFS and noSQL data sources, using architectures that include computational or storage engines compatible with Apache Hadoop.
Big data research
Authors: Balazinska Magdalena
Published: September 2015

The need for effective tools for big data data management and analytics continues to grow. While the ecosystem of tools is expanding many research problems remain open: they include challenges around efficient processing, flexible analytics, ease of use, and operation as a service. Many new systems and much innovation, however, come from industry (or from academic projects that quickly became big players in industry). An important question for our community is whether industry will solve all the problems or whether there is a place for academic research in big data and what is that place. In this paper, we address this question by looking back at our research on the Nuage, CQMS, Myria, and Data Pricing projects, and the SciDB collaboration.
Databases and hardware
Authors: Ailamaki Anastasia
Published: September 2015

Fast query and transaction processing is the goal of 40 years of database research and the reason of existence for many new database system architectures. In data management, system performance means acceptable response time and throughput on critical-path operations, ideally with scalability guarantees. Performance is improved with top-of-the line research on data processing algorithms; efficiency, however, is contingent on seamless collaboration between the database software and hardware and storage devices. In 1980, the goal was to minimize disk accesses; in 2000, memory replaced disks in terms of access costs. Nowadays performance is synonymous to scalability; scalability, in turn, translates into sustainable and predictable use of hardware resources in the face of embarrassing parallelism and deep storage hierarchies while minimizing energy needs - a challenging goal in multiple dimensions.

We discuss work done in the past four decades to tighten the interaction between the database software and underlying hardware and show that, as application and microarchitecture roadmaps evolve, the effort of maintaining smooth collaboration blossoms into a multitude of interesting research avenues with direct technological impact.
Metadiscourse Use in English Job Applications
Authors: Lin Meizhen
Published: September 2015

Under the theoretical framework of Hyland’s interpersonal model of metadiscourse, an in-depth analysis of the distribution and characteristics of metadiscourse in English job applications is carried out. The findings show that metadiscourse is frequently used in English job applications and these resources have different occurrence frequencies. The writers use more interactional metadiscourse than interactive metadiscourse. Among all the metadiscourse subcategories, self-mentions, transitions and hedges are frequently used. The analysis demonstrates that all metadiscourse resources seem to stress the interpersonal potential in order to convey a persuasive message under an informative mask. It is also shown that metadiscourse use is genre-constrained and the writer’s writing purpose.
Subjective outcome evaluation of a university subject on service leadership
Authors: Shek Daniel T.L. , Liang Jianqiang
Published: September 2015

University students (n=58) responded to a 45-item subjective outcome evaluation scale after taking a credit-bearing elective subject titled “Service Leadership” at The Hong Kong Polytechnic University in the first semester of the 2013–14 academic year. Results showed that the students generally displayed positive perceptions of the program content and the instructors, and most of them perceived the subject to be beneficial to different aspects of their development. As predicted, three subscales of the scale (Program Content, Program Implementer, and Program Benefits) were significantly correlated. Similar to the previous studies, perceived quality of the program but not quality of instructors and program benefits predicted the students’ overall satisfaction with the program.
Analysis of Performance for 100 Gbit/s Dual-Polarization QPSK Modulation Format System
Authors: Li Li , Xiao-bo Guo , Jing Li
Published: September 2015

This article introduces modulation technology, coherent reception technology, the overall design and other key issues for 100 Gbit/s dual-polarization quadrature phase shift keying (DP-QPSK) modulation. Using the technologies based on digital signal processing (DSP), it realizes the long-range transmissions of 100 Gbit/s optical systems to achieve optical signal dispersion compensation, polarized solution reuse and phase estimation. The effect of this scheme is verified with OptiSystem, and the simulation results indicate, with the help of DSP module for processing of the received signal, that the last constellation is ideal and the data transmission error rate is less than 1.3 e
3D/4D sonography – any safety problem
Authors: Pooh Ritsuko K. , Maeda Kazuo , Kurjak Asim , Sen Cihat , Ebrashy Alaa , Adra Abdallah , Dayyabu Aliyu Labaran , Wataganara Tuangsit , de Sá Renato Augusto Moreira , Stanojevic Milan
Published: September 2015

Gray-scale image data are processed in 3D ultrasound by repeated scans of multiple planes within a few seconds to achieve one surface rendering image and three perpendicular plane images. The 4D image is achieved by repeating 3D images in short intervals, i.e. 3D and 4D ultrasound are based on simple B-mode images. During 3D/4D acquisition, a fetus
»Indian Country«. Der Raum als Feind in der Gewaltgeschichte der europäischen Expansion
Authors: Walter Dierk
Published: September 2015

More than many other armed conflicts of the modern era, the colonial wars/wars of empire fought by Western powers at the periphery of the world system over the past five centuries were defined by spatial categories. The problems of transoceanic or transcontinental power projection and the economic logic of the imperial system limited the military means employed on the periphery, making them often insufficient for the effective control of extended, inaccessible, and inhospitable spaces. Faced with an adversary capable of using these wide spaces to avoid decisive battle, the imperial military resorted to warfare against entire societies. Cognitively and mentally, Western armed forces experienced the periphery as an alien space, a space in which physical geography and human enemy seemed to be organically connected in opposing the invader. This perception of the peripheral space was not only partially responsible for atrocities, but could also result in warfare against nature itself.
Bending properties of carbon fiber nanocomposites with lamination structure of reinforcement
Authors: Song Jun Hee
Published: September 2015

Advanced materials with excellent performance are in high demand in modern industry. Carbon fiber composites offer a number of advantageous mechanical properties. A significant improvement in fiber-reinforced composites can be achieved by dispersing a very small amount of nanofiller in the resin. Vacuum-assisted resin transfer molding (VARTM) is one of the most important processes for producing reinforced plastics. In this work, several composite samples were fabricated with the infusion of carbon nanofibers (CNFs) into the epoxy matrix using VARTM process. Using scanning electron microscopy (SEM), it was confirmed that CNFs were well dispersed in the resin. Bending tests were performed to investigate the mechanical properties of the samples, and SEM, to examine the fracture surfaces.
A Newly Discovered Text by Russell on Pythagoras and the History of Mathematics
Authors: Vianelli Giovanni
Published: September 2015

This paper presents a lengthy unpublished passage by Russell on the attempts by Pythagoras and subsequent mathematicians to deal with continuity and the logical paradoxes, recently discovered in the manuscript of the History of Western Philosophy. In the first part, I provide a short introduction to the new material. In the second, I analyze its philosophical content. In the third, I develop some considerations, mainly in the attempt to solve the following problems: can we determine when and for what purpose Russell wrote these leaves? why were they never published? where do we find similar subjects expounded in the History? where does the significance of the discovery really lie?
Did Russell Advocate Preventive Atomic War against the USSR?
Authors: Blitz David
Published: September 2015

Russell's statements in the immediate post-World War II period about war with the Soviet Union have generated considerable controversy. Some commentators interpret his declarations as if he advocated a preventive war against the Soviet Union. To the contrary, Russell advanced a strategy of conditional threat of war with the aim not of provoking war, but of preventing it. However, Russell was unable to satisfy his critics. Despite initial accuracy in his restatements of what he had originally said, Russell erred in later affirmations, lending credence to the erroneous view that he had something to hide.
Amyloid β Oligomers Disrupt Blood–CSF Barrier Integrity by Activating Matrix Metalloproteinases
Authors: Brkic Marjana , Balusu Sriram , Van Wonterghem Elien , Gorlé Nina , Benilova Iryna , Kremer Anna , Van Hove Inge , Moons Lieve , De Strooper Bart , Kanazir Selma , Libert Claude , Vandenbroucke Roosmarijn E.
Published: September 2015

The blood–CSF barrier (BCSFB) consists of a monolayer of choroid plexus epithelial (CPE) cells that maintain CNS homeostasis by producing CSF and restricting the passage of undesirable molecules and pathogens into the brain. Alzheimer's disease is the most common progressive neurodegenerative disorder and is characterized by the presence of amyloid β (Aβ) plaques and neurofibrillary tangles in the brain. Recent research shows that Alzheimer's disease is associated with morphological changes in CPE cells and compromised production of CSF. Here, we studied the direct effects of Aβ on the functionality of the BCSFB. Intracerebroventricular injection of Aβ1–42 oligomers into the cerebral ventricles of mice, a validated Alzheimer's disease model, caused induction of a cascade of detrimental events, including increased inflammatory gene expression in CPE cells and increased levels of proinflammatory cytokines and chemokines in the CSF. It also rapidly affected CPE cell morphology and tight junction protein levels. These changes were associated with loss of BCSFB integrity, as shown by an increase in BCSFB leakage. Aβ1–42 oligomers also increased matrix metalloproteinase (MMP) gene expression in the CPE and its activity in CSF. Interestingly, BCSFB disruption induced by Aβ1–42 oligomers did not occur in the presence of a broad-spectrum MMP inhibitor or in MMP3-deficient mice. These data provide evidence that MMPs are essential for the BCSFB leakage induced by Aβ1–42 oligomers. Our results reveal that Alzheimer's disease-associated soluble Aβ1–42 oligomers induce BCSFB dysfunction and suggest MMPs as a possible therapeutic target.

SIGNIFICANCE STATEMENTNo treatments are yet available to cure Alzheimer's disease; however, soluble Aβ oligomers are believed to play a crucial role in the neuroinflammation that is observed in this disease. Here, we studied the effect of Aβ oligomers on the often neglected barrier between blood and brain, called the blood–CSF barrier (BCSFB). This BCSFB is formed by the choroid plexus epithelial cells and is important in maintaining brain homeostasis. We observed Aβ oligomer-induced changes in morphology and loss of BCSFB integrity that might play a role in Alzheimer's disease progression. Strikingly, both inhibition of matrix metalloproteinase (MMP) activity and MMP3 deficiency could protect against the detrimental effects of Aβ oligomer. Clearly, our results suggest that MMP inhibition might have therapeutic potential.
A Single Bolus of Docosahexaenoic Acid Promotes Neuroplastic Changes in the Innervation of Spinal Cord Interneurons and Motor Neurons and Improves Functional Recovery after Spinal Cord Injury
Authors: Liu Zhuo-Hao , Yip Ping K. , Adams Louise , Davies Meirion , Lee Jae Won , Michael Gregory J. , Priestley John V. , Michael-Titus Adina T.
Published: September 2015

Docosahexaenoic acid (DHA) is an ω-3 polyunsaturated fatty acid that is essential in brain development and has structural and signaling roles. Acute DHA administration is neuroprotective and promotes functional recovery in animal models of adult spinal cord injury (SCI). However, the mechanisms underlying this recovery have not been fully characterized. Here we investigated the effects of an acute intravenous bolus of DHA delivered after SCI and characterized DHA-induced neuroplasticity within the adult injured spinal cord. We found robust sprouting of uninjured corticospinal and serotonergic fibers in a rat cervical hemisection SCI model. A mouse pyramidotomy model was used to confirm that this robust sprouting was not species or injury model specific. Furthermore, we demonstrated that corticospinal fibers sprouting to the denervated side of the cord following pyramidotomy contact V2a interneurons. We also demonstrated increased serotonin fibers and synaptophysin in direct contact with motor neurons. DHA also increased synaptophysin in rat cortical cell cultures. A reduction in phosphatase and tensin homolog (PTEN) has been shown to be involved in axonal regeneration and synaptic plasticity. We showed that DHA significantly upregulates miR-21 and downregulates PTEN in corticospinal neurons. Downregulation of PTEN and upregulation of phosphorylated AKT by DHA were also seen in primary cortical neuron cultures and were accompanied by increased neurite outgrowth. In summary, acute DHA induces anatomical and synaptic plasticity in adult injured spinal cord. This study shows that DHA has therapeutic potential in cervical SCI and provides evidence that DHA could exert its beneficial effects in SCI via enhancement of neuroplasticity.

SIGNIFICANCE STATEMENTIn this study, we show that an acute intravenous injection of docosahexaenoic acid (DHA) 30 min after spinal cord injury induces neuroplasticity. We found robust sprouting of uninjured corticospinal and serotonergic fibers in a rat hemisection spinal cord injury model. A mouse pyramidotomy model was used to confirm that the robust sprouting involved V2a interneurons. We show that DHA significantly upregulates miR-21 and phosphorylated AKT, and downregulates phosphatase and tensin homolog (PTEN), which is involved in suppressing anatomical plasticity, in corticospinal neurons and in primary cortical neuron cultures. We conclude that acute DHA can induce anatomical and synaptic plasticity. This provides direct evidence that DHA could exert its beneficial effects in spinal cord injury via neuroplasticity enhancement.