bluuebunny/crossref_metadata_2025 huggingface dataset:
PARADIS
Authors: Cho Minsik , Brand Daniel , Bordawekar Rajesh , Finkler Ulrich , Kulandaisamy Vincent , Puri Ruchir
Published: September 2015

In-place radix sort is a popular distribution-based sorting algorithm for short numeric or string keys due to its linear run-time and constant memory complexity. However, efficient parallelization of in-place radix sort is very challenging for two reasons. First, the initial phase of permuting elements into buckets suffers read-write dependency inherent in its
in-place
nature. Secondly, load balancing of the recursive application of the algorithm to the resulting buckets is difficult when the buckets are of very different sizes, which happens for skewed distributions of the input data. In this paper, we present a novel parallel in-place radix sort algorithm, PARADIS, which addresses both problems: a) "speculative permutation" solves the first problem by assigning multiple non-continuous array stripes to each processor. The resulting shared-nothing scheme achieves full parallelization. Since our speculative permutation is not complete, it is followed by a "repair" phase, which can again be done in parallel without any data sharing among the processors. b) "distribution-adaptive load balancing" solves the second problem. We dynamically allocate processors in the context of radix sort, so as to minimize the overall completion time. Our experimental results show that PARADIS offers excellent performance/scalability on a wide range of input data sets.
Join size estimation subject to filter conditions
Authors: Vengerov David , Menck Andre Cavalheiro , Zait Mohamed , Chakkappen Sunil P.
Published: September 2015

In this paper, we present a new algorithm for estimating the size of equality join of multiple database tables. The proposed algorithm, Correlated Sampling, constructs a small space synopsis for each table, which can then be used to provide a quick estimate of the join size of this table with other tables subject to dynamically specified predicate filter conditions, possibly specified over multiple columns (attributes) of each table. This algorithm makes a single pass over the data and is thus suitable for streaming scenarios. We compare this algorithm analytically to two other previously known sampling approaches (independent Bernoulli Sampling and End-Biased Sampling) and to a novel sketch-based approach. We also compare these four algorithms experimentally and show that results fully correspond to our analytical predictions based on derived expressions for the estimator variances, with Correlated Sampling giving the best estimates in a large range of situations.
Asynchronous and fault-tolerant recursive datalog evaluation in shared-nothing engines
Authors: Wang Jingjing , Balazinska Magdalena , Halperin Daniel
Published: September 2015

We present a new approach for data analytics with iterations. Users express their analysis in Datalog with bag-monotonic aggregate operators, which enables the expression of computations from a broad variety of application domains. Queries are translated into query plans that can execute in shared-nothing engines, are incremental, and support a variety of iterative models (synchronous, asynchronous, different processing priorities) and failure-handling techniques. The plans require only small extensions to an existing shared-nothing engine, making the approach easily implementable. We implement the approach in the Myria big-data management system and use our implementation to empirically study the performance characteristics of different combinations of iterative models, failure handling methods, and applications. Our evaluation uses workloads from a variety of application domains. We find that no single method outperforms others but rather that application properties must drive the selection of the iterative query execution model.
Keys for graphs
Authors: Fan Wenfei , Fan Zhe , Tian Chao , Dong Xin Luna
Published: September 2015

Keys for graphs aim to uniquely identify entities represented by vertices in a graph. We propose a class of keys that are recursively defined in terms of graph patterns, and are interpreted with subgraph isomorphism. Extending conventional keys for relations and XML, these keys find applications in object identification, knowledge fusion and social network reconciliation. As an application, we study the entity matching problem that, given a graph
G
and a set Σ of keys, is to find all pairs of entities (vertices) in
G
that are identified by keys in Σ. We show that the problem is intractable, and cannot be parallelized in logarithmic rounds. Nonetheless, we provide two parallel scalable algorithms for entity matching, in MapReduce and a vertex-centric asynchronous model. Using real-life and synthetic data, we experimentally verify the effectiveness and scalability of the algorithms.
Spatial partitioning techniques in SpatialHadoop
Authors: Eldawy Ahmed , Alarabi Louai , Mokbel Mohamed F.
Published: September 2015

SpatialHadoop is an extended MapReduce framework that supports
global indexing
that spatial partitions the data across machines providing orders of magnitude speedup, compared to traditional Hadoop. In this paper, we describe seven alternative partitioning techniques and experimentally study their effect on the quality of the generated index and the performance of range and spatial join queries. We found that using a 1% sample is enough to produce high quality partitions. Also, we found that the total area of partitions is a reasonable measure of the quality of indexes when running spatial join. This study will assist researchers in choosing a good spatial partitioning technique in distributed environments.
Argonaut
Authors: Haas Daniel , Ansel Jason , Gu Lydia , Marcus Adam
Published: September 2015

Crowdsourced workflows are used in research and industry to solve a variety of tasks. The databases community has used crowd workers in query operators/optimization and for tasks such as entity resolution. Such research utilizes
microtasks
where crowd workers are asked to answer simple yes/no or multiple choice questions with little training. Typically, microtasks are used with voting algorithms to combine redundant responses from multiple crowd workers to achieve result quality. Microtasks are powerful, but fail in cases where larger context (e.g., domain knowledge) or significant time investment is needed to solve a problem, for example in large-document structured data extraction.

In this paper, we consider context-heavy data processing tasks that may require many hours of work, and refer to such tasks as
macrotasks.
Leveraging the infrastructure and worker pools of existing crowdsourcing platforms, we automate macrotask scheduling, evaluation, and pay scales. A key challenge in macrotask-powered work, however, is evaluating the quality of a worker's output, since ground truth is seldom available and redundancy-based quality control schemes are impractical. We present Argonaut, a framework that improves macrotask powered work quality using a hierarchical review. Argonaut uses a predictive model of worker quality to select trusted workers to perform review, and a separate predictive model of task quality to decide which tasks to review. Finally, Argonaut can identify the ideal trade-off between a single phase of review and multiple phases of review given a constrained review budget in order to maximize overall output quality. We evaluate an industrial use of Argonaut to power a structured data extraction pipeline that has utilized over half a million hours of crowd worker input to complete millions of macrotasks. We show that Argonaut can capture up to 118% more errors than random spot-check reviews in review budget-constrained environments with up to two review layers.
Gobblin
Authors: Qiao Lin , Li Yinan , Takiar Sahil , Liu Ziyang , Veeramreddy Narasimha , Tu Min , Dai Ying , Buenrostro Issac , Surlaker Kapil , Das Shirshanka , Botev Chavdar
Published: September 2015

Data ingestion is an essential part of companies and organizations that collect and analyze large volumes of data. This paper describes Gobblin, a generic data ingestion framework for Hadoop and one of LinkedIn's latest open source products. At LinkedIn we need to ingest data from various sources such as relational stores, NoSQL stores, streaming systems, REST endpoints, filesystems, etc. into our Hadoop clusters. Maintaining independent pipelines for each source can lead to various operational problems. Gobblin aims to solve this issue by providing a centralized data ingestion framework that makes it easy to support ingesting data from a variety of sources.

Gobblin distinguishes itself from similar frameworks by focusing on three core principles: generality, extensibility, and operability. Gobblin supports a mixture of data sources out-of-the-box and can be easily extended for more. This enables an organization to use a single framework to handle different data ingestion needs, making it easy and inexpensive to operate. Moreover, with an end-to-end metrics collection and reporting module, Gobblin makes it simple and efficient to identify issues in production.
One trillion edges
Authors: Ching Avery , Edunov Sergey , Kabiljo Maja , Logothetis Dionysios , Muthukrishnan Sambavi
Published: September 2015

Analyzing large graphs provides valuable insights for social networking and web companies in content ranking and recommendations. While numerous graph processing systems have been developed and evaluated on available benchmark graphs of up to 6.6B edges, they often face significant difficulties in scaling to much larger graphs. Industry graphs can be two orders of magnitude larger - hundreds of billions or up to one trillion edges. In addition to scalability challenges, real world applications often require much more complex graph processing workflows than previously evaluated. In this paper, we describe the usability, performance, and scalability improvements we made to Apache Giraph, an open-source graph processing system, in order to use it on Facebook-scale graphs of up to one trillion edges. We also describe several key extensions to the original Pregel model that make it possible to develop a broader range of production graph applications and workflows as well as improve code reuse. Finally, we report on real-world operations as well as performance characteristics of several large-scale production applications.
Gorilla
Authors: Pelkonen Tuomas , Franklin Scott , Teller Justin , Cavallaro Paul , Huang Qi , Meza Justin , Veeraraghavan Kaushik
Published: September 2015

Large-scale internet services aim to remain highly available and responsive in the presence of unexpected failures. Providing this service often requires monitoring and analyzing tens of millions of measurements per second across a large number of systems, and one particularly effective solution is to store and query such measurements in a time series database (TSDB).

A key challenge in the design of TSDBs is how to strike the right balance between efficiency, scalability, and reliability. In this paper we introduce Gorilla, Facebook's in-memory TSDB. Our insight is that users of monitoring systems do not place much emphasis on individual data points but rather on aggregate analysis, and recent data points are of much higher value than older points to quickly detect and diagnose the root cause of an ongoing problem. Gorilla optimizes for remaining highly available for writes and reads, even in the face of failures, at the expense of possibly dropping small amounts of data on the write path. To improve query efficiency, we aggressively leverage compression techniques such as delta-of-delta timestamps and XOR'd floating point values to reduce Gorilla's storage footprint by 10x. This allows us to store Gorilla's data in memory, reducing query latency by 73x and improving query throughput by 14x when compared to a traditional database (HBase)-backed time series data. This performance improvement has unlocked new monitoring and debugging tools, such as time series correlation search and more dense visualization tools. Gorilla also gracefully handles failures from a single-node to entire regions with little to no operational overhead.
ConfSeer
Authors: Potharaju Rahul , Chan Joseph , Hu Luhui , Nita-Rotaru Cristina , Wang Mingshi , Zhang Liyuan , Jain Navendu
Published: September 2015

We introduce ConfSeer, an automated system that detects potential configuration issues or deviations from identified best practices by leveraging a knowledge base (KB) of technical solutions. The intuition is that these KB articles describe the configuration problems and their fixes so if the system can
accurately
understand them, it can
automatically
pinpoint both the errors and their resolution. Unfortunately, finding an accurate match is difficult because (a) the KB articles are written in natural language text, and (b) configuration files typically contain a large number of parameters with a high value range. Thus, expert-driven manual troubleshooting is not scalable.

While there are several state-of-the-art techniques proposed for individual tasks such as keyword matching, concept determination and entity resolution, none offer a practical
end-to-end
solution to detect problems in machine configurations. In this paper, we describe our experiences building ConfSeer using a novel combinations of ideas from natural language processing, information retrieval and interactive learning. ConfSeer powers the recommendation engine behind Microsoft Operations Management Suite that proposes fixes for software configuration errors. The system has been running in production for about a year to proactively find misconfigurations on tens of thousands of servers. Our evaluation of ConfSeer against an expert-defined rule-based commercial system, an expert survey and web search engines shows that it achieves 80%-97.5% accuracy and incurs low runtime overheads.
SAASFEE
Authors: Bux Marc , Brandt Jörgen , Lipka Carsten , Hakimzadeh Kamal , Dowling Jim , Leser Ulf
Published: September 2015

Across many fields of science, primary data sets like sensor read-outs, time series, and genomic sequences are analyzed by complex chains of specialized tools and scripts exchanging intermediate results in domain-specific file formats. Scientific workflow management systems (SWfMSs) support the development and execution of these tool chains by providing workflow specification languages, graphical editors, fault-tolerant execution engines, etc. However, many SWfMSs are not prepared to handle large data sets because of inadequate support for distributed computing. On the other hand, most SWfMSs that do support distributed computing only allow static task execution orders. We present SAASFEE, a SWfMS which runs arbitrarily complex workflows on Hadoop YARN. Workflows are specified in Cuneiform, a functional workflow language focusing on parallelization and easy integration of existing software. Cuneiform workflows are executed on Hi-WAY, a higher-level scheduler for running workflows on YARN. Distinct features of SAASFEE are the ability to execute iterative workflows, an adaptive task scheduler, re-executable provenance traces, and compatibility to selected other workflow systems. In the demonstration, we present all components of SAASFEE using real-life workflows from the field of genomics.
A demonstration of HadoopViz
Authors: Eldawy Ahmed , Mokbel Mohamed F. , Jonathan Christopher
Published: September 2015

This demonstration presents HadoopViz; an extensible MapReduce-based system for visualizing Big Spatial Data. HadoopViz has two main unique features that distinguish it from other techniques. (1) It provides an extensible interface that allows users to visualize various types of data by defining five abstract functions, without delving into the details of the MapReduce algorithms. We show how it is used to create four types of visualizations, namely,
scatter plot, road network, frequency heat map
, and
temperature heat map.
(2) HadoopViz is capable of generating big images with giga-pixel resolution by employing a three-phase approach of
partitioning, rasterize
, and
merging.
HadoopViz generates single and multi-level images, where the latter allows users to zoom in/out to get more/less details. Both types of images are generated with a very high resolution using the extensible and scalable framework of HadoopViz.
RINSE
Authors: Zoumpatianos Kostas , Idreos Stratos , Palpanas Themis
Published: September 2015

Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available. An adaptive index data structure, ADS+, which is specifically tailored to solve the problem of indexing and querying very large data series collections has been recently proposed as a solution to this problem. The main idea is that instead of building the complete index over the complete data set up-front and querying only later, we interactively and adaptively build parts of the index, only for the parts of the data on which the users pose queries. The net effect is that instead of waiting for extended periods of time for the index creation, users can immediately start exploring the data series. In this work, we present a demonstration of ADS+; we introduce RINSE, a system that allows users to experience the benefits of the ADS+ adaptive index through an intuitive web interface. Users can explore large datasets and find patterns of interest, using nearest neighbor search. They can draw queries (data series) using a mouse, or touch screen, or they can select from a predefined list of data series. RINSE can scale to large data sizes, while drastically reducing the data to query delay: by the time state-of-the-art indexing techniques finish indexing 1 billion data series (and before answering even a single query), adaptive data series indexing can already answer 3 * 10
5
queries.
FLORIN
Authors: Liu Qingyuan , Dragut Eduard C. , Mukherjee Arjun , Meng Weiyi
Published: September 2015

In this paper, we propose a system, FLORIN, which provides support for near real-time applications on user generated content on daily news. FLORIN continuously crawls news outlets for articles and user comments accompanying them. It attaches the articles and comments to daily event stories. It identifies the opinionated content in user comments and performs named entity recognition on news articles. All these pieces of information are organized hierarchically and exportable to other applications. Multiple applications can be built on this data. We have implemented a sentiment analysis system that runs on top of it.
VINERy
Authors: Li Yunyao , Kim Elmer , Touchette Marc A. , Venkatachalam Ramiya , Wang Hao
Published: September 2015

Information Extraction (IE) is the key technology enabling analytics over unstructured and semi-structured data. Not surprisingly, it is becoming a critical building block for a wide range of emerging applications. To satisfy the rising demands for information extraction in real-world applications, it is crucial to lower the barrier to entry for IE development and enable users with general computer science background to develop higher quality extractors.

In this demonstration
1
, we present VINERy, an intuitive yet expressive visual IDE for information extraction. We show how it supports the full cycle of IE development without requiring a single line of code and enables a wide range of users to develop high quality IE extractors with minimal efforts. The extractors visually built in VINERY are automatically translated into semantically equivalent extractors in a state-of-the-art declarative language for IE. We also demonstrate how the auto-generated extractors can then be imported into a conventional Eclipse-based IDE for further enhancement. The results of our user studies indicate that VINERY is a significant step forward in facilitating extractor development for both expert and novice IE developers.
A framework for clustering uncertain data
Authors: Schubert Erich , Koos Alexander , Emrich Tobias , Züfle Andreas , Schmid Klaus Arthur , Zimek Arthur
Published: September 2015

The challenges associated with handling uncertain data, in particular with querying and mining, are finding increasing attention in the research community. Here we focus on clustering uncertain data and describe a general framework for this purpose that also allows to visualize and understand the impact of uncertainty---using different uncertainty models---on the data mining results. Our framework constitutes release 0.7 of ELKI (http://elki.dbs.ifi.lmu.de/) and thus comes along with a plethora of implementations of algorithms, distance measures, indexing techniques, evaluation measures and visualization components.
Structured analytics in social media
Authors: Das Mahashweta , Das Gautam
Published: September 2015

The rise of social media has turned the Web into an online community where people connect, communicate, and collaborate with each other. Structured analytics in social media is the process of discovering the structure of the relationships emerging from this social media use. It focuses on identifying the users involved, the activities they undertake, the actions they perform, and the items (e.g., movies, restaurants, blogs, etc.) they create and interact with. There are two key challenges facing these tasks: how to organize and model social media content, which is often unstructured in its raw form, in order to employ structured analytics on it; and how to employ analytics algorithms to capture both explicit link-based relationships and implicit behavior-based relationships. In this tutorial, we systemize and summarize the research so far in analyzing social interactions between users and items in the Web from data mining and database perspectives. We start with a general overview of the topic, including discourse to various exciting and practical applications. Then, we discuss the state-of-art for modeling the data, formalizing the mining task, developing the algorithmic solutions, and evaluating on real datasets. We also emphasize open problems and challenges for future research in the area of structured analytics and social media.
Existence and multiplicity of entire solutions for fractional p-Kirchhoff equations
Authors: Pucci Patrizia , Xiang Mingqi , Zhang Binlin
Published: September 2015

The purpose of this paper is mainly to investigate the existence of entire solutions of the stationary Kirchhoff type equations driven by the fractional p-Laplacian operator in ℝ
N
. By using variational methods and topological degree theory, we prove multiplicity results depending on a real parameter λ and under suitable general integrability properties of the ratio between some powers of the weights. Finally, existence of infinitely many pair of entire solutions is obtained by genus theory. Last but not least, the paper covers a main feature of Kirchhoff problems which is the fact that the Kirchhoff function M can be zero at zero. The results of this paper are new even for the standard stationary Kirchhoff equation involving the Laplace operator.
Effects of Strategic Planning Time on L2 Paired Oral Test Performance
Authors: Wang Haizhen , Song Fangqi
Published: September 2015

Planning, as a task condition, is hypothesized to influence L2 test performance and thus test scores (Skehan, 1998). This study investigates the effects of lengths of strategic planning time on L2 paired oral test performance, moderated by L2 proficiency. It aims to determine whether differences in performance result from 0, 1, 2 or 3 minutes of planning time, and whether planning time and proficiency interactively affect performance. The participants were 72 Chinese EFL learners, divided into four groups, each performing the same dialogic task with 1 or 2 or 3 minute planning time or none. All speech recordings were rated by two trained raters, and the transcripts of the speech samples subjected to a discourse analysis, measuring fluency features of Rate A and Rate B, complexity features of syntactic complexity, syntactic variety and lexical variety, and accuracy features of error-free clauses and correct verb forms. Findings show a stable accuracy, higher fluency in the planned condition, and greater syntactic complexity when learners are given 3 minutes’ planning time. No interaction is found between planning time and proficiency.
The Development of Bilingual Children’s Narrative Skills: A Report of the “Looking Glass Neighborhood” Program
Authors: Chen Sibo
Published: September 2015

This paper evaluates Look Glass Neighborhood (LGN), an educational after-school program being experimented in San Diego, California. Following the theories of Vygotskian psychology and the “Fifth-Dimension” education model, LGN aims at improving bilingual children’s literacy via interactive games and letter writing activities. Based on previous studies on first language acquisition over past decades, the paper first discusses the inadequacy of research on child narrative development, especially in terms of the lack of attention to bilingual children and the insufficient discussion on applying first language acquisition theories to early literacy education. Then, it demonstrates the unique designs of the “Looking Glass Neighborhood” program by a qualitative analysis of ethnographic data from two elementary school bilingual participants in the program, explicating the program’s focuses on the interactions between oral performance and content-focused co-writing activities. Finally, the paper explores the possibility to embed some design elements of LGN such as content-based, co-writing activities and indirect oral corrective feedback into China’s current kindergarten and elementary EFL curriculums.
The Effects of Written Corrective Feedback on Chinese EFL Learners’ Acquisition of English Collocations
Authors: Wang Ting , Jiang Lin
Published: September 2015

The role of written corrective feedback (CF) in the process of acquiring a second language (L2) has been an issue of considerable controversies over past decades. This study thus endeavors to extend current work on written CF by investigating and comparing the effect on collocation learning of one traditional type of feedback—direct corrective feedback (DCF)—with an innovative type of error correction, feedback provided within context—situated feedback (SF). The effects of the two types of written feedback were measured by examining the accurate use of target collocations in a translation test and a multiple choice test completed by 73 intermediate EFL students in China. Three groups were formed: a DCF group, an SF group, and a control group. The study found that both treatment groups outperformed the control group in the posttests and delayed posttests and that there were significant advantages of the SF group in comparison to the DCF group in both posttests. The results suggested that the provision of written CF was helpful for collocation learning and that situational context could promote the facilitative role of written CF in language acquisition. These findings are discussed from the perspectives of both second language acquisition (SLA) theory and language pedagogy and implications for future research efforts are put forward.
Umbilicity and characterization of Pansu spheres in the Heisenberg group
Authors: Cheng Jih-Hsin , Chiu Hung-Lin , Hwang Jenn-Fang , Yang Paul
Published: September 2015

For everyn≥2{n\geq 2}we define a notion of umbilicity for hypersurfaces in the Heisenberg groupHn{H_{n}}. We classify umbilic hypersurfaces in some cases, and prove that Pansu spheres are the only umbilic spheres with positive constantp-mean (or horizontal-mean) curvature inHn{H_{n}}up to Heisenberg translations.
The Effect of Plug-in Electric Vehicles on Harmonic Analysis of Smart Grid
Authors: Heidarian T. , Joorabian M. , Reza A.
Published: September 2015

In this paper, the effect of plug-in electric vehicles is studied on the smart distribution system with a standard IEEE 30-bus network. At first, harmonic power flow analysis is performed by Newton-Raphson method and by considering distorted substation voltage. Afterward, proper sizes of capacitors is selected by cuckoo optimization algorithm to reduce the power losses and cost and by imposing acceptable limit for total harmonic distortion and RMS voltages. It is proposed that the impact of generated current harmonics by electric vehicle battery chargers should be factored into overall load control strategies of smart appliances. This study is generalized to the different hours of a day by using daily load curve, and then optimum time for charging of electric vehicles batteries in the parking lots are determined by cuckoo optimization algorithm. The results show that injecting harmonic currents of plug-in electric vehicles causes a drop in the voltage profile and increases power loss. Moreover, charging the vehicle batteries has more impact on increasing the power losses rather than the harmonic currents effect. Also, the findings showed that the current harmonics has a great influence on increasing of THD. Finally, optimum working times of all parking lots was obtained for the utilization cost reduction.
A Computational Methodology to Support Reimbursement Requests Analysis Concerning Electrical Damages
Authors: Almeida Junior Afonso Bernardino , Gondim Isaque Nogueira , Rezende Paulo Henrique Oliveira , Oliveira José Carlos
Published: September 2015

In light of the growing number of reimbursement requests processed from consumers for electrical damage to equipment, supposedly caused through the manifestation of anomalies on the power grid, there comes the need for reliable means for providing a decision on the issues highlighted herein. Through the recognition that in the current context, the procedures used are based on reviews, information and records of occurrences in the field, there has been significant inadequacy and fragility in the issuing of conclusive advice or opinions. In particular, the search for mechanisms grounded in classical principles and accepted in electrical engineering presents itself as an important challenge on which to base the decision making process in full awareness of its incumbent science and technology. Therefore, with the aim of meeting these assumptions, the study in question excels in its presentation of the principles that guided the software analysis, which intend above all else to correlate cause and effect. The elaborated strategy involves modelling stages as well as studies aimed at: distribution supply reproduction; characterization of the distribution network to the complainant consumer; representation of the diverse electro-electronic appliances and lastly, a proposal for correlating the disturbances impacting on equipment with their dielectric and thermal supportability requirements. For the purpose of illustrating the software process, an actual case study coupled with a loss and claim scenario is presented.
Raum in der Militärgeschichte und Gewaltgeschichte. Probleme, Ergebnisse und neue Felder der Forschung
Authors: Nübel Christoph
Published: September 2015

»Space in military history and the history of violence. Issues, results and new fields of research«. Whilst the history of violence already deals with spatial concepts, military history has largely omitted space as a means of study. This article shows that the concept of space is useful in creating new questions and findings in the field of military history. The article is an introduction into a spatial military history and history of violence. It deals with hermeneutic problems of a spatial approach with specific examples and discusses already existing studies on space and the military. Finally it suggests four conceptions of space which are appropriate to point out when dealing with the multi-faceted dimensions of space.
Kultureller Raum und Bewegungskrieg. Raumerfahrungen und Raumdeutungen zu Osteuropa in Selbstzeugnissen deutschsprachiger Kriegsteilnehmer der k.u.k. Armee
Authors: Dornik Wolfram
Published: September 2015

Due to the permanent shift between mobile and trench warfare as well as conquest and occupation, the soldiers of the First World War in Eastern Europe were brought into more intense relationship to the surrounding space and the local population than on other theatres of war. This article focuses on cultural interpretation of space on the Eastern Front by German-speaking Austro-Hungarian soldiers. Using eleven diaries and unpublished memoirs of subaltern officers, non-commissioned officers and ordinary soldiers, it seeks to analyse the perceptions of cultural space, Kriegslandschaften (Kurt Lewin) and the image of the »East«. It is shown to what extent the specific war experience shaped the cultural images of the soldiers during the war, and which interpretations they offered in their writings.
Raumwahrnehmung und Raumpraktiken des deutschen Militärs im »Kampfraum Stadt« 1939–1942
Authors: Wettstein Adrian E.
Published: September 2015

Historical spatial theories have rarely been used in operational military history. However, they can offer a fertile approach to provide a theoretical framework in operational history. This article shows the potential use of spatial theories and spatial terms in operational history by analysing urban warfare and its perception in the German army during the Second World War. Taking the battle of Stalingrad as a case study, special emphasis is given to physical and social-organisational spatial concepts.
Preparation and characterization of biodegradable blends of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) and poly(butylene adipate-co-terephthalate)
Authors: Zhang Min , Diao Xiaoqian , Jin Yujuan , Weng Yunxuan
Published: September 2015

Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH) was blended with poly(butylene adipate-co-terephthalate) (PBAT) by extrusion at different weight ratios (PHBH/PBAT: 100:0, 80:20, 60:40, 50:50, 40:60, 20:80 and 0:100). Films were then prepared from the blends and characterized in terms of their morphological, rheological, mechanical and thermal properties. The morphological and rheological results indicated that PHBH/PBAT blends are immiscible but exhibit possible molecular interaction. The crystallization temperature of PHBH in the blends decreased, indicating that the addition of PBAT inhibited the crystallization of PHBH. Blending PBAT with PHBH improved the processability compared with that of pure polymers. The mechanical properties, including tensile strength, elongation at break and tear strength, increased with increasing PBAT content. The PHBH/PBAT 20:80 blend exhibited significantly improved mechanical properties, which was due to the reinforcing and toughening effect of the finely dispersed PHBH phase.
Different patterns of 5-HT receptor and transporter dysfunction in neuropsychiatric disorders – a comparative analysis of in vivo imaging findings
Authors: Nikolaus Susanne , Müller Hans-Wilhelm , Hautzel Hubertus
Published: September 2015

Impairment of serotonin receptor and transporter function is increasingly recognized to play a major role in the pathophysiology of neuropsychiatric diseases including anxiety disorder (AD), major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ). We conducted a PubMed search, which provided a total of 136 in vivo studies with PET and SPECT, in which 5-HT synthesis, 5-HT transporter binding, 5-HT1 receptor binding or 5-HT2 receptor binding in patients with the primary diagnosis of acute AD, MDD, BD or SZ was compared to healthy individuals. A retrospective analysis revealed that AD, MDD, BD and SZ differed as to affected brain region(s), affected synaptic constituent(s) and extent as well as direction of dysfunction in terms of either sensitization or desensitization of transporter and receptor binding sites.
Russell and the Communist-Aligned Peace Movement in the Mid-1950s
Authors: Bone Andrew G.
Published: September 2015

The Soviet Union's successful test of an atomic bomb in 1949 altered Russell's outlook on international politics. But there was a considerable delay between this critical juncture of the Cold War and any perceptible softening of Russell's anti-Communism. Even after a muted optimism about the possibility of improvement in the foreign and domestic policies of the Soviet Union entered Russell's writing, he remained apprehensive about campaigning for peace alongside western Communists and fellow-travellers. He disliked the central thrust of pro-Soviet peace propaganda but regarded ideological diversity as a vital prerequisite for meaningful peace work. Russell also understood that such an approach carried with it a risk that his efforts might be tarnished by association with the Communist-aligned peace movement. His dilemma was eased not by a shift in his own tactics, but by external factors: a crisis within western Communism and the emergence of broadly based movements for peace that could not easily be tainted by their critics as "pro-Soviet".
Functional Integration of Adult-Born Hippocampal Neurons after Traumatic Brain Injury
Authors: Villasana Laura E. , Kim Kristine N. , Westbrook Gary L. , Schnell Eric
Published: September 2015

Traumatic brain injury (TBI) increases hippocampal neurogenesis, which may contribute to cognitive recovery after injury. However, it is unknown whether TBI-induced adult-born neurons mature normally and functionally integrate into the hippocampal network. We assessed the generation, morphology, and synaptic integration of new hippocampal neurons after a controlled cortical impact (CCI) injury model of TBI. To label TBI-induced newborn neurons, we used 2-month-old POMC-EGFP mice, which transiently and specifically express EGFP in immature hippocampal neurons, and doublecortin-CreERT2transgenic mice crossed with Rosa26-CAG-tdTomato reporter mice, to permanently pulse-label a cohort of adult-born hippocampal neurons. TBI increased the generation, outward migration, and dendritic complexity of neurons born during post-traumatic neurogenesis. Cells born after TBI had profound alterations in their dendritic structure, with increased dendritic branching proximal to the soma and widely splayed dendritic branches. These changes were apparent during early dendritic outgrowth and persisted as these cells matured. Whole-cell recordings from neurons generated during post-traumatic neurogenesis demonstrate that they are excitable and functionally integrate into the hippocampal circuit. However, despite their dramatic morphologic abnormalities, we found no differences in the rate of their electrophysiological maturation, or their overall degree of synaptic integration when compared to age-matched adult-born cells from sham mice. Our results suggest that cells born after TBI participate in information processing, and receive an apparently normal balance of excitatory and inhibitory inputs. However, TBI-induced changes in their anatomic localization and dendritic projection patterns could result in maladaptive network properties.
Calcitonin Gene-Related Peptide Reduces Taste-Evoked ATP Secretion from Mouse Taste Buds
Authors: Huang Anthony Y. , Wu Sandy Y.
Published: September 2015

Immunoelectron microscopy revealed that peripheral afferent nerve fibers innervating taste buds contain calcitonin gene-related peptide (CGRP), which may be as an efferent transmitter released from peripheral axon terminals. In this report, we determined the targets of CGRP within taste buds and studied what effect CGRP exerts on taste bud function. We isolated mouse taste buds and taste cells, conducted functional imaging using Fura-2, and used cellular biosensors to monitor taste-evoked transmitter release. The findings showed that a subset of Presynaptic (Type III) taste cells (53%) responded to 0.1 μmCGRP with an increase in intracellular Ca2+. In contrast, Receptor (Type II) taste cells rarely (4%) responded to 0.1 μmCGRP. Using pharmacological tools, the actions of CGRP were probed and elucidated by the CGRP receptor antagonist CGRP8-37. We demonstrated that this effect of CGRP was dependent on phospholipase C activation and was prevented by the inhibitor U73122. Moreover, applying CGRP caused taste buds to secrete serotonin (5-HT), a Presynaptic (Type III) cell transmitter, but not ATP, a Receptor (Type II) cell transmitter. Further, our previous studies showed that 5-HT released from Presynaptic (Type III) cells provides negative paracrine feedback onto Receptor (Type II) cells by activating 5-HT1Areceptors, and reducing ATP secretion. Our data showed that CGRP-evoked 5-HT release reduced taste-evoked ATP secretion. The findings are consistent with a role for CGRP as an inhibitory transmitter that shapes peripheral taste signals via serotonergic signaling during processing gustatory information in taste buds.

SIGNIFICANCE STATEMENTThe taste sensation is initiated with a highly complex set of interactions between a variety of cells located within the taste buds before signal propagation to the brain. Afferent signals from the oral cavity are carried to the brain in chemosensory fibers that contribute to chemesthesis, the general chemical sensitivity of the mucus membranes in the oronasal cavities and being perceived as pungency, irritation, or heat. This is a study of a fundamental question in neurobiology: how are signals processed in sensory end organs, taste buds? More specifically, taste-modifying interactions, via transmitters, between gustatory and chemosensory afferents inside taste buds will help explain how a coherent output is formed before being transmitted to the brain.
Distinct Functions for Anterograde and Retrograde Sorting of SORLA in Amyloidogenic Processes in the Brain
Authors: Dumanis Sonya B. , Burgert Tilman , Caglayan Safak , Füchtbauer Annette , Füchtbauer Ernst-Martin , Schmidt Vanessa , Willnow Thomas E.
Published: September 2015

SORLA is a neuronal sorting receptor implicated both in sporadic and familial forms of AD. SORLA reduces the amyloidogenic burden by two mechanisms, either by rerouting internalized APP molecules from endosomes to thetrans-Golgi network (TGN) to prevent proteolytic processing or by directing newly produced Aβ to lysosomes for catabolism. Studies in cell lines suggested that the interaction of SORLA with cytosolic adaptors retromer and GGA is required for receptor sorting to and from the TGN. However, the relevance of anterograde or retrograde trafficking for SORLA activityin vivoremained largely unexplored. Here, we generated mouse models expressing SORLA variants lacking binding sites for GGA or retromer to query this concept in the brain. Disruption of retromer binding resulted in a retrograde-sorting defect with accumulation of SORLA in endosomes and depletion from the TGN, and in an overall enhanced APP processing. In contrast, disruption of the GGA interaction did not impact APP processing but caused increased brain Aβ levels, a mechanism attributed to a defect in anterograde lysosomal targeting of Aβ. Our findings substantiated the significance of adaptor-mediated sorting for SORLA activitiesin vivo, and they uncovered that anterograde and retrograde sorting paths may serve discrete receptor functions in amyloidogenic processes.

SIGNIFICANCE STATEMENTSORLA is a sorting receptor that directs target proteins to distinct intracellular compartments in neurons. SORLA has been identified as a genetic risk factor for sporadic, but recently also for familial forms of AD. To confirm the relevance of SORLA sorting for AD processes in the brain, we generated mouse lines, which express trafficking mutants instead of the wild-type form of this receptor. Studying neuronal activities in these mutant mice, we dissected distinct trafficking routes for SORLA guided by two cytosolic adaptors termed GGA and retromer. We show that these sorting pathways serve discrete functions in control of amyloidogenic processes and may represent unique therapeutic targets to interfere with specific aspects of neurodegenerative processes in the diseased brain.
Distinct Modulations in Sensorimotor Postmovement and Foreperiod β-Band Activities Related to Error Salience Processing and Sensorimotor Adaptation
Authors: Torrecillos Flavie , Alayrangues Julie , Kilavik Bjørg Elisabeth , Malfait Nicole
Published: September 2015

In a recent study, Tan et al. (2014a,b) showed that the increase in β-power typically observed after a movement above sensorimotor regions (β-rebound) is attenuated when movement-execution errors are induced by visual perturbations. Moreover, akin to sensorimotor adaptation, the effect depended on the context in which the errors are experienced. Thus the β-rebound attenuation might relate to neural processes involved in trial-to-trial adaptive mechanisms. In two EEG experiments with human participants, along with the β-rebound, we examine β-activity during the preparation of reaches immediately following perturbed movements. In the first experiment, we show that both foreperiod and postmovement β-activities are parametrically modulated by the sizes of kinematic errors produced by unpredictable mechanical perturbations (force field) independent of their on-line corrections. In the second experiment, we contrast two types of reach errors: movement-execution errors that trigger trial-to-trial adaptive mechanisms and goal errors that do not elicit sensorimotor adaptation. Movement-execution errors were induced by mechanical or visual perturbations, whereas goal errors were caused by unexpected displacements of the target at movement initiation. Interestingly, foreperiod and postmovement β-activities exhibit contrasting patterns, pointing to important functional differences of their underlying neuronal activity. While both types of reach errors attenuate the postmovement β-rebound, only the kinematic errors that trigger trial-to-trial motor-command updates influenced β-activity during the foreperiod. These findings suggest that the error-related modulation of the β-rebound may reflect salience processing, independent of sensorimotor adaptation. In contrast, modulations in the foreperiod β-power might relate to the motor-command adjustments activated after movement-execution errors are experienced.

SIGNIFICANCE STATEMENTThe functional significance of sensorimotor β-band (15–25 Hz) oscillations remains uncertain. Recently β-power was found to be reduced following erroneous movements. We extend and refine this novel finding in two crucial ways. First, by contrasting the EEG correlates of movement errors driving or not driving adaptation we dissociate error-salience processing from error-based adaptation. Second, in addition to β-activity in error trials, we examine β-power during the preparation of the subsequent movements. We find clearly distinct patterns of error-related modulations for β-activities preceding and succeeding movements, highlighting critical functional differences. Postmovement β-power may reflect error-salience processing independent of sensorimotor adaptation. In contrast, modulations in the foreperiod β-band power may directly relate to the motor-command adjustments activated after movement-execution errors are experienced.