bluuebunny/crossref_metadata_2025 huggingface dataset:
Contraceptive counseling among pediatric primary care providers in Western Pennsylvania: A survey-based study
Authors: Papas Beth Ann , Shaikh Nader , Watson Katherine , Sucato Gina S
Published: September 2017

Objectives:

Data suggest that adolescents in the United States receive inadequate contraceptive counseling. This study sought to determine factors affecting pediatricians’ discussion of contraception with adolescent patients, with a specific focus on long-acting reversible contraception—implantable contraception and intrauterine devices.

Methods:

A cross-sectional survey was sent via email to a convenience sample of pediatric residents and pediatric primary care providers in Western Pennsylvania. Self-reported contraceptive counseling and prescribing practices in response to clinical vignettes were assessed.

Results:

Of potential participants (287), 88 (31%) responded. Younger providers and providers who had received contraceptive training were significantly more likely to discuss long-acting reversible contraception methods. Discussion of contraceptive methods also varied by both the age and the sexual history of the patient.

Conclusion:

Variation in contraceptive counseling potentially results in missed opportunities to counsel about and provide the most effective contraceptive methods. More uniform, universal provider training might alleviate some of these inconsistencies.
A qualitative exploration of the experiences of living with and being treated for fibromyalgia
Authors: Ashe Simon C , Furness Penny J , Taylor Sophie J , Haywood-Small Sarah , Lawson Kim
Published: September 2017

This study explores the life and treatment experience of people in the United Kingdom with fibromyalgia in order to inform the development of treatments which are both effective and acceptable to users. Qualitative interviews were conducted with 14 participants with interpretative phenomenological analysis used as the theoretical framework and analytical method. The themes identified were as follows: Inauthenticity of fibromyalgia, An Unconventional healthcare experience, Re-creating support networks, Challenging the working identity, Threatening the family dynamic and Fighting, accepting or accommodating? The biopsychosocial impacts of fibromyalgia disrupted the identity, lifestyle, roles and relationships of our participants with such challenges further exacerbated by the contested nature of the illness.
Embolization of a life-threatening placenta increta hemorrhage with a four-month MRI follow-up
Authors: Bach Annika , Bartens Anne , Gossing Gabriele , Gebauer Bernhard , Günther Rolf W , Althoff Christian
Published: September 2017

A 29-year-old woman with partial placenta increta was treated by bilateral uterine artery embolization (UAE) for bleeding with hemorrhagic shock two months after delivery, resulting in permanent hemostasis. The patient underwent a total of three magnetic resonance imaging (MRI) examinations—before UAE and four days and four months after UAE. At four months, MRI showed a fully regenerated uterus with preserved perfusion and complete resolution of residual placental tissue.
Hemangioma of the rib showing a relatively high 18F-FDG uptake: a case report with a literature review
Authors: Itabashi Takahide , Emori Makoto , Terashima Yoshinori , Hasegawa Tadashi , Shimizu Junya , Nagoya Satoshi , Yamashita Toshihiko
Published: September 2017

Hemangioma of the rib is a rare benign tumor that is often difficult to distinguish from malignant bone tumors. Rib hemangioma often shows bony disruption with a slight cortical disruption, extraosseous lesion, and expanded bone on computed tomography (CT). We report the case of a 68-year-old man with atypical rib hemangioma with a slight cortical disruption and no expanded bone. The tumor showed relatively high 18FDG-uptake on positron emission tomography (PET)/CT. Rib hemangioma often shows higher 18FDG-uptake. PET/CT may not provide useful information for distinguishing rib hemangioma from a malignant tumor. Close observation without surgical resection may be feasible if the tumor is diagnosed as a rib hemangioma by biopsy.
Book Review: Sam Moyo and Yoichi Mine (Eds) (2016), What Colonialism Ignored: ‘African Potentials’ for Resolving Conflicts in Southern Africa
Authors: Ossome Lyn
Published: September 2017

Sam Moyo and Yoichi Mine (Eds) (2016), What Colonialism Ignored: ‘African Potentials’ for Resolving Conflicts in Southern Africa, Cameroon: Langaa RPCIG. Paperback, ISBN 978995 6763399, pp. 365, £28.
Book Review: Renata Motta (2016), Social Mobilization, Global Capitalism and Struggles over Food: A Comparative Study of Social Movements
Authors: Penna Camila
Published: September 2017

Renata Motta (2016), Social Mobilization, Global Capitalism and Struggles over Food: A Comparative Study of Social Movements. Oxon and New York, NY: Routledge. Hardback, ISBN 9781 317053736, pp. 204, US $127.46.
Anti-inflammatory roles of p38α MAPK in macrophages are context dependent and require IL-10
Authors: Raza Abbas , Crothers Jessica W , McGill Mahalia M , Mawe Gary M , Teuscher Cory , Krementsov Dimitry N
Published: September 2017

The p38 MAPK pathway was originally identified as a master regulator of proinflammatory cytokine production by myeloid cells. Numerous drugs targeting this kinase showed promise in preclinical models of inflammatory disease, but so far, none have shown efficacy in clinical trials. The reasons behind this are unclear, but may, in part, be explained by emerging anti-inflammatory functions of this kinase or overly refined selectivity of second-generation pharmacologic inhibitors. Here, we show that p38α signaling in macrophages plays pro- and anti-inflammatory functions in vivo and in vitro, with the outcome depending on the stimulus, output, kinetics, or mode of kinase inhibition (genetic vs. pharmacologic). Different pharmacologic inhibitors of p38 exhibit opposing effects, with second-generation inhibitors acting more specifically but inhibiting anti-inflammatory functions. Functionally, we show that the anti-inflammatory functions of p38α in macrophages are critically dependent on production of IL-10. Accordingly, in the absence of IL-10, inhibition of p38α signaling in macrophages is protective in a spontaneous model of colitis. Taken together, our results shed light on the limited clinical efficacy of drugs targeting p38 and suggest that their therapeutic efficacy can be significantly enhanced by simultaneous modulation of p38-dependent anti-inflammatory mediators, such as IL-10.
Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who, What, Why, When, Where, and a Sixth, So What?
Authors: Vetter Thomas R.
Published: September 2017

Descriptive statistics are specific methods basically used to calculate, describe, and summarize collected research data in a logical, meaningful, and efficient way. Descriptive statistics are reported numerically in the manuscript text and/or in its tables, or graphically in its figures. This basic statistical tutorial discusses a series of fundamental concepts about descriptive statistics and their reporting. The mean, median, and mode are 3 measures of the center or central tendency of a set of data. In addition to a measure of its central tendency (mean, median, or mode), another important characteristic of a research data set is its variability or dispersion (ie, spread). In simplest terms, variability is how much the individual recorded scores or observed values differ from one another. The range, standard deviation, and interquartile range are 3 measures of variability or dispersion. The standard deviation is typically reported for a mean, and the interquartile range for a median. Testing for statistical significance, along with calculating the observed treatment effect (or the strength of the association between an exposure and an outcome), and generating a corresponding confidence interval are 3 tools commonly used by researchers (and their collaborating biostatistician or epidemiologist) to validly make inferences and more generalized conclusions from their collected data and descriptive statistics. A number of journals, including Anesthesia & Analgesia, strongly encourage or require the reporting of pertinent confidence intervals. A confidence interval can be calculated for virtually any variable or outcome measure in an experimental, quasi-experimental, or observational research study design. Generally speaking, in a clinical trial, the confidence interval is the range of values within which the true treatment effect in the population likely resides. In an observational study, the confidence interval is the range of values within which the true strength of the association between the exposure and the outcome (eg, the risk ratio or odds ratio) in the population likely resides. There are many possible ways to graphically display or illustrate different types of data. While there is often latitude as to the choice of format, ultimately, the simplest and most comprehensible format is preferred. Common examples include a histogram, bar chart, line chart or line graph, pie chart, scatterplot, and box-and-whisker plot. Valid and reliable descriptive statistics can answer basic yet important questions about a research data set, namely: “Who, What, Why, When, Where, How, How Much?”
Conditional Cash Transfers: The Case ofProgresa/Oportunidades
Authors: Parker Susan W. , Todd Petra E.
Published: September 2017

Conditional cash transfer (CCT) programs innovate by conditioning transfers to poor families on investments in the human capital of children and other family members. The Mexican CCT program Progresa/Oportunidades began in 1997 and has served as a model for many of the now over sixty countries with CCTs around the world, in large part due to its initial evaluation with an experimental design and numerous follow-up studies. This article reviews the literature on the development, evaluation, and findings of Progresa/Oportunidades, summarizing what is known about program effects, taking into account corrections for multiple-hypothesis testing. ( JEL H23, I18, I28, I32, I38, O15)
Preoperative predicting malignancy in breast mass-like lesions: value of adding histogram analysis of apparent diffusion coefficient maps to dynamic contrast-enhanced magnetic resonance imaging for improving confidence level
Authors: Liu Hong-Li , Zong Min , Wei Han , Lou Jian-Juan , Wang Si-Qi , Zou Qi-Gui , Shi Hai-Bin , Jiang Yan-Ni
Published: September 2017

Objective:

This study aims to find out the benefits of adding histogram analysis of apparent diffusion coefficient (ADC) maps onto dynamic contrast-enhanced MRI (DCE-MRI) in predicting breast malignancy.

Methods:

This study included 95 patients who were found with breast mass-like lesions from January 2014 to March 2016 (47 benign and 48 malignant). These patients were estimated by both DCE-MRI and diffusion-weighted imaging (DWI) and classified into two groups, namely, the benign and the malignant. Between these groups, the DCE-MRI parameters, including morphology, enhancement homogeneity, maximum slope of increase (MSI) and time-signal intensity curve (TIC) type, as well as histogram parameters generated from ADC maps were compared. Then, univariate and multivariate logistic regression analyses were conducted to determine the most valuable variables in predicting malignancy. Receiver operating characteristic curve analyses were taken to assess their clinical values.

Results:

The lesion morphology, MSI and TIC Type (p < 0.05) were significantly different between the two groups. Multivariate logistic regression analyses revealed that irregular morphology, TIC Type II/III and ADC10 were important predictors for breast malignancy. Increased area under curve (AUC) and specificity can be achieved with Model 2 (irregular morphology + TIC Type II/III + ADC10 < 1.047 ×10−3 mm2 s–1) as the criterion than Model 1 (irregular morphology + TIC Type II/III) only (Model 2 vs Model 1; AUC, 0.822 vs 0.705; sensitivity, 68.8 vs 75.0%; specificity, 95.7 vs 66.0%).

Conclusion:

Irregular morphology, TIC Type II/III and ADC10 are indicators for predicting breast malignancy. Histogram analysis of ADC maps can provide additional value in predicting breast malignancy.

Advances in knowledge:

The morphology, MSI and TIC types in DCE-MRI examination have significant difference between the benign and malignant groups. A higher AUC can be achieved by using ADC10 as the diagnostic index than other ADC parameters, and the difference in AUC based on ADC10 and ADCmean was statistically significant. The irregular morphology, TIC Type II/III and ADC10 were significant predictors for malignant lesions.
Proximal Femur Ewing Sarcoma in the Skeletally Immature
Authors: Morris Jonathan , Silver Joshua , Yang Rui , Hoang Bang H. , Fornari Eric , Geller David S.
Published: September 2017

A 3-year-old female presented with a biopsy proven stage IIB proximal femur Ewing sarcoma. Following neoadjuvant chemotherapy, she underwent local control consisting of a wide proximal femur resection and subsequent reconstruction using a custom minimally invasive expandable prosthesis. Following revision to a larger device and serial expansions spanning a number of years the prosthesis slowly subluxated and eventually dislocated. A pelvic osteotomy was not successful in maintaining a concentric hip and a total hip arthroplasty was ultimately required. Dislocation is a known complication of expandable prosthesis. However, there is a paucity of literature describing the management and outcomes of patients who develop this complication. Close ongoing monitoring of hip joint congruency and limb length is recommended. If necessary, early intervention should be undertaken to maintain a reduce hip. Patient-specific management is essential when dealing with skeletally immature patients with more than 10 years of growth remaining.
Approach-Based Complications of Lumbar Interbody Fusion
Authors: Wong Jason , Igoe Sarah , Phan Kevin , Amorosa Louis , Cho Woojin
Published: September 2017

Ever since the introduction of spinal fusion in 1911, the procedure has continued to evolve and improve as the demand of the aging population increased and as new technological advances emerged. With better technology and better instruments, spine surgeons have been able to develop newer and better approaches that achieve stable constructs but with less morbidity. This article will discuss the advantages and complications associated with each of the approaches, including the anterior, posterior, laparoscopic, axial approach, lateral, minimally invasive, and oblique approach. Ultimately, there seems to be no clear advantage to using one approach over another as they all carry similar risks. There has been an increase in interest in more minimally invasive approaches as these present shorter operative times and less morbidity; however, these approaches are newer and present a steep learning curve with little long-term data on efficacy and safety.
Single-incision laparoscopic surgery in gynecologic surgery: a single-institutional experience from Saudi Arabia
Authors: Salamah Kareemah , Abuzaid Mohammed , Abu-Zaid Ahmed
Published: September 2017

Background: Laparoscopy is rapidly replacing laparotomy in the field of gynecologic surgery. Generally, there are limited data concerning the utility of single-incision laparoscopic surgery (SILS) in gynecologic surgery. Specifically, in Saudi Arabia, a third-world country, data are further limited; only one related study has been conducted so far. The purpose of this study is to retrospectively report our single-institutional experience of SILS in terms of feasibility, safety and perioperative outcomes in the management of various gynecologic conditions.

Methods:The study took place at the Women’s Specialized Hospital, King Fahad Medical City, Riyadh, Saudi Arabia. From January 2012 to May 2016, all gynecologic patients who underwent SILS procedures were analyzed for pre-, intra- and post-operative details. SILS was performed using a single multi-port trocar and standard laparoscopic instruments.

Results: A total of 54 patients underwent 66 SILS procedures. The median age and body mass index (BMI) were 36 years and 28.2 kg/m2, respectively. Fourteen patients (26%) had ≥ 1 previous abdominal and/or pelvic surgeries. Twenty-four patients (44.4%) were nulliparous. The three most commonly performed SILS procedures were unilateral salpingo-oophorectomy (45.5%) and unilateral ovarian cystectomy (27.3%) and adhesiolysis (6.1%). The median operative time, estimated blood loss and hospital stay were 74 min, 50 ml and 1 day, respectively. Three patients required conversion to laparotomy, as follows: unidentified non-stopping bleeding source (n=1) and endometriosis stage IV resulting in difficult dissection (n=2). One patient developed post-operative incisional hernia that was treated surgically. The median patients’ post-operative pain (according to Wong-Baker FACES Foundation pain rating scale) within 4 hours was 2. At 4-week post-operatively, the median wound scar length (measured at outpatient clinic) was 2 cm.

Conclusions: SILS is feasible, safe and associated with acceptable clinical and surgical outcomes.
Radiological Justification Of Radionuclide Inventory Control In The Context Of The Long-Term Safety Of Radioactive Waste Disposal Facilities
Authors: Блохин П. , Blohin P. , Самойлов А. , Samoylov A.
Published: September 2017

Purpose: this paper concentrates on the development and validation of an approach enabling to identify radiologically relevant radionuclides in radioactive waste at different stages of their management, as well as to implement their direct instrumental control.

Material and methods: The research was carried out by comparing relevant radiological effects produced by radionuclides contained in activation RW from VVER-440 unit (reactor vessel, vessel internals and fuel rod cladding) on human at different stages of RW management. AKDAM-2.0 complex was used to evaluate the changes in the radionuclide inventory of materials during their irradiation and cooling.

Results: The study enabled to calculate relevant contribution of different radionuclides to the overall activity and dose rate from external and internal human exposure at different stages of RW management. This paper proposes a novel approach to identify radiologically relevant radionuclides based on a comparative evaluation of their contribution to the dose rate their activity, half-lives and migration properties. Relevant lists of radionuclides were developed for the studied materials. These radionuclides should be considered in the safety assessments of RW management practices and the post-closure safety demonstration for deep geological disposal facilities (DGDF). The study suggests that direct instrumental control is feasible for a number of radionuclides along with the use of an integrated approach enabling to evaluate the content of other radionuclides.

Conclusions: Further validation proved the viability of the proposed approach in the development of lists of radiologically relevant radionuclides. It has been found that the generated list is consistent with international practice used to demonstrate DGDF safety. It should be noted that only a small number of radionuclides should be considered radiologically relevant notwithstanding a variety of radionuclides generated due to material activation. In some cases, certain radionuclides are required to be added to the lists specified in the appendices to Radiation Safety Standards (RSS). However, the direct instrumental control covering the entire list of radiologically relevant radionuclides (for each RW management stage) is considered not feasible and hard to implement. The study shows that an integrated approach combining direct instrumental control for certain radionuclides, periodic destructive tests and inventory calculations is a preferred option. At the stage of periodic radiation monitoring in the disposal facility, such instrumental control should be focused on the evaluation of disposal system properties affecting its safety (hydrogeochemical, hydrogeological characteristics and etc.).
Slalom
Authors: Olma Matthaios , Karpathiotakis Manos , Alagiannis Ioannis , Athanassoulis Manos , Ailamaki Anastasia
Published: September 2017

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. Hence, recent in-situ query processing systems operate directly over raw data, alleviating the loading cost. At the same time, analytical workloads have increasing number of queries. Typically, each query focuses on a constantly shifting -- yet small -- range. Minimizing the workload latency, now, requires the benefits of indexing in in-situ query processing.

In this paper, we present Slalom, an in-situ query engine that accommodates workload shifts by monitoring user access patterns. Slalom makes on-the-fly partitioning and indexing decisions, based on information collected by lightweight monitoring. Slalom has two key components: (i) an online partitioning and indexing scheme, and (ii) a partitioning and indexing tuner tailored for in-situ query engines. When compared to the state of the art, Slalom offers performance benefits by taking into account user query patterns to (a)
logically
partition raw data files and (b) build for each partition lightweight
partition-specific
indexes. Due to its lightweight and adaptive nature, Slalom achieves efficient accesses to raw data with minimal memory consumption. Our experimentation with both micro-benchmarks and real-life workloads shows that Slalom outperforms state-of-the-art in-situ engines (3 -- 10×), and achieves comparable query response times with fully indexed DBMS, offering much lower (∼ 3×) cumulative query execution times for query workloads with increasing size and unpredictable access patterns.
Mison
Authors: Li Yinan , Katsipoulakis Nikos R. , Chandramouli Badrish , Goldstein Jonathan , Kossmann Donald
Published: September 2017

The growing popularity of the JSON format has fueled increased interest in loading and processing JSON data within analytical data processing systems. However, in many applications, JSON parsing dominates performance and cost. In this paper, we present a new JSON parser called Mison that is particularly tailored to this class of applications, by pushing down both projection and filter operators of analytical queries into the parser. To achieve these features, we propose to deviate from the traditional approach of building parsers using finite state machines (FSMs). Instead, we follow a two-level approach that enables the parser to jump directly to the correct position of a queried field without having to perform expensive tokenizing steps to find the field. At the upper level, Mison speculatively predicts the logical locations of queried fields based on previously seen patterns in a dataset. At the lower level, Mison builds structural indices on JSON data to map logical locations to physical locations. Unlike all existing FSM-based parsers, building structural indices converts control flow into data flow, thereby largely eliminating inherently unpredictable branches in the program and exploiting the parallelism available in modern processors. We experimentally evaluate Mison using representative real-world JSON datasets and the TPC-H benchmark, and show that Mison produces significant performance benefits over the best existing JSON parsers; in some cases, the performance improvement is over one order of magnitude.
Reverse engineering aggregation queries
Authors: Tan Wei Chit , Zhang Meihui , Elmeleegy Hazem , Srivastava Divesh
Published: September 2017

Query reverse engineering seeks to re-generate the SQL query that produced a given query output table from a given database. In this paper, we solve this problem for OLAP queries with group-by and aggregation. We develop a novel three-phase algorithm named REGAL
1
for this problem. First, based on a lattice graph structure, we identify a set of group-by candidates for the desired query. Second, we apply a set of aggregation constraints that are derived from the properties of aggregate operators at both the table-level and the group-level to discover candidate combinations of group-by columns and aggregations that are consistent with the given query output table. Finally, we find a multi-dimensional filter, i.e., a conjunction of selection predicates over the base table attributes, that is needed to generate the exact query output table. We conduct an extensive experimental study over the TPC-H dataset to demonstrate the effectiveness and efficiency of our proposal.
On sampling from massive graph streams
Authors: Ahmed Nesreen K. , Duffield Nick , Willke Theodore L. , Rossi Ryan A.
Published: September 2017

We propose Graph Priority Sampling (
gps
), a new paradigm for order-based reservoir sampling from massive graph streams.
gps
provides a general way to weight edge sampling according to auxiliary and/or size variables so as to accomplish various estimation goals of graph properties. In the context of subgraph counting, we show how edge sampling weights can be chosen so as to minimize the estimation variance of counts of specified sets of subgraphs. In distinction with many prior graph sampling schemes,
gps
separates the functions of edge sampling and subgraph estimation. We propose two estimation frameworks: (1) Post-Stream estimation, to allow
gps
to construct a reference sample of edges to support retrospective graph queries, and (2) In-Stream estimation, to allow
gps
to obtain lower variance estimates by incrementally updating the subgraph count estimates during stream processing. Unbiasedness of subgraph estimators is established through a new Martingale formulation of graph stream order sampling, in which subgraph estimators, written as a product of constituent edge estimators, are unbiased, even when computed at different points in the stream. The separation of estimation and sampling enables significant resource savings relative to previous work. We illustrate our framework with applications to triangle and wedge counting. We perform a large-scale experimental study on real-world graphs from various domains and types.
gps
achieves high accuracy with < 1% error for triangle and wedge counting, while storing a small fraction of the graph with average update times of a few microseconds per edge. Notably, for billion-scale graphs,
gps
accurately estimates triangle and wedge counts with < 1% error, while storing a small fraction of < 0.01% of the total edges in the graph.
Dimensions based data clustering and zone maps
Authors: Ziauddin Mohamed , Witkowski Andrew , Kim You Jung , Potapov Dmitry , Lahorani Janaki , Krishna Murali
Published: September 2017

In recent years, the data warehouse industry has witnessed decreased use of indexing but increased use of compression and clustering of data facilitating efficient data access and data pruning in the query processing area. A classic example of data pruning is the partition pruning, which is used when table data is range or list partitioned. But lately, techniques have been developed to prune data at a lower granularity than a table partition or sub-partition. A good example is the use of data pruning structure called zone map. A zone map prunes zones of data from a table on which it is defined. Data pruning via zone map is very effective when the table data is clustered by the filtering columns.

The database industry has offered support to cluster data in tables by its local columns, and to define zone maps on clustering columns of such tables. This has helped improve the performance of queries that contain filter predicates on local columns. However, queries in data warehouses are typically based on star/snowflake schema with filter predicates usually on columns of the dimension tables joined to a fact table. Given this, the performance of data warehouse queries can be significantly improved if the fact table data is clustered by columns of dimension tables together with zone maps that maintain min/max value ranges of these clustering columns over zones of fact table data. In recognition of this opportunity of significantly improving the performance of data warehouse queries, Oracle 12c release 1 has introduced the support for dimension based clustering of fact tables together with data pruning of the fact tables via dimension based zone maps.
SAP HANA adoption of non-volatile memory
Authors: Andrei Mihnea , Lemke Christian , Radestock Günter , Schulze Robert , Thiel Carsten , Blanco Rolando , Meghlan Akanksha , Sharique Muhammad , Seifert Sebastian , Vishnoi Surendra , Booss Daniel , Peh Thomas , Schreter Ivan , Thesing Werner , Wagle Mehul , Willhalm Thomas
Published: September 2017

Non-Volatile RAM (NVRAM) is a novel class of hardware technology which is an interesting blend of two storage paradigms: byte-addressable DRAM and block-addressable storage (e.g. HDD/SSD). Most of the existing enterprise relational data management systems such as SAP HANA have their internal architecture based on the inherent assumption that memory is volatile and base their persistence on explicit handling of block-oriented storage devices. In this paper, we present the early adoption of Non-Volatile Memory within the SAP HANA Database, from the architectural and technical angles. We discuss our architectural choices, dive deeper into a few challenges of the NVRAM integration and their solutions, and share our experimental results. As we present our solutions for the NVRAM integration, we also give, as a basis, a detailed description of the relevant HANA internals.
CarStream
Authors: Zhang Mingming , Wo Tianyu , Xie Tao , Lin Xuelian , Liu Yaxiao
Published: September 2017

As the Internet-of-Vehicles (IoV) technology becomes an increasingly important trend for future transportation, designing large-scale IoV systems has become a critical task that aims to process big data uploaded by fleet vehicles and to provide data-driven services. The IoV data, especially high-frequency vehicle statuses (e.g., location, engine parameters), are characterized as large volume with a low density of value and low data quality. Such characteristics pose challenges for developing real-time applications based on such data. In this paper, we address the challenges in designing a scalable IoV system by describing CarStream, an industrial system of big data processing for chauffeured car services. Connected with over 30,000 vehicles, CarStream collects and processes multiple types of driving data including vehicle status, driver activity, and passenger-trip information. Multiple services are provided based on the collected data. CarStream has been deployed and maintained for three years in industrial usage, collecting over 40 terabytes of driving data. This paper shares our experiences on designing CarStream based on large-scale driving-data streams, and the lessons learned from the process of addressing the challenges in designing and maintaining CarStream.
FAD.js
Authors: Bonetta Daniele , Brantner Matthias
Published: September 2017

JSON is one of the most popular data encoding formats, with wide adoption in Databases and BigData frameworks as well as native support in popular programming languages such as JavaScript/Node.js, Python, and R.

Nevertheless, JSON data processing can easily become a performance bottleneck in data-intensive applications because of parse and serialization overhead. In this paper, we introduce F
ad
.
js
, a runtime system for efficient processing of JSON objects in data-intensive applications. F
ad
.
js
is based on (1) speculative just-in-time (JIT) compilation and (2) selective access to data. Experiments show that applications using F
ad
.
js
achieve speedups up to 2.7x for encoding and 9.9x for decoding JSON data when compared to state-of-the art JSON processing libraries.
Adaptive statistics in Oracle 12c
Authors: Chakkappen Sunil , Budalakoti Suratna , Krishnamachari Ramarajan , Valluri Satyanarayana R , Wood Alan , Zait Mohamed
Published: September 2017

Database Management Systems (DBMS) continue to be the foundation of mission critical applications, both OLTP and Analytics. They provide a safe, reliable and efficient platform to store and retrieve data. SQL is the lingua franca of the database world. A database developer writes a SQL statement to specify data sources and express the desired result and the DBMS will figure out the most efficient way to implement it. The query optimizer is the component in a DBMS responsible for finding the best execution plan for a given SQL statement based on statistics, access structures, location, and format. At the center of a query optimizer is a cost model that consumes the above information and helps the optimizer make decisions related to query transformations, join order, join methods, access paths, and data movement.

The final execution plan produced by the query optimizer depends on the quality of information used by the cost model, as well as the sophistication of the cost model. In addition to statistics about the data, the cost model also relies on statistics generated internally for intermediate results, e.g. size of the output of a join operation. This paper presents the problems caused by incorrect statistics of intermediate results, survey the existing solutions and present our solution introduced in Oracle 12c. The solution includes validating the generated statistics using table data and via the automatic creation of auxiliary statistics structures. We limit the overhead of the additional work by confining their use to cases where it matters the most, caching the computed statistics, and using table samples. The statistics management is automated. We demonstrate the benefits of our approach based on experiments using two SQL workloads, a benchmark that uses data from the Internal Movie Data Base (IMDB) and a real customer workload.
ARShop
Authors: Wang Chao , Feng Yihao , Guo Qi , Li Zhaoxian , Liu Kexin , Tang Zijian , Tung Anthony K. H. , Wu Lifu , Zheng Yuxin
Published: September 2017

ARShop is a one-stop solution for shopping in the cyber-physical world with the help of crowd knowledge and augmented reality. Its ultimate goal is to improve customers' shopping experience. When a customer enters a physical shop and snaps a shot, the enriched cyber information of the surroundings will pop up and be augmented on the screen. ARShop can also be the customer's personal shopping assistant who can show routes to the shops that the customer is interested in. In addition, ARShop provides merchants with a web-based interface to manage their shops and promote their business to customers, and provides customers with an Android App to query using images.
Monopedia
Authors: Schüle Maximilian E. , Schliski Pascal M. N. , Hutzelmann Thomas , Rosenberger Tobias , Leis Viktor , Vorona Dimitri , Kemper Alfons , Neumann Thomas
Published: September 2017

In order to handle the database load for web scale applications, the conventional wisdom is that a cluster of database servers and a caching layer are essential. In this work, we argue that modern main memory database systems are often fast enough to consolidate this complex architecture into a single server (plus an additional fail over system). To demonstrate this claim, we design the
Monopedia Benchmark
, a benchmark for web scale applications modeled after Wikipedia. Using this benchmark, we show that it is indeed possible to run the database workload of one of the largest web sites in the world on a single database server.
Foresight
Authors: Demiralp Çağatay , Haas Peter J. , Parthasarathy Srinivasan , Pedapati Tejaswini
Published: September 2017

Current tools for exploratory data analysis (EDA) require users to manually select data attributes, statistical computations and visual encodings. This can be daunting for large-scale, complex data. We introduce Foresight, a system that helps the user rapidly discover visual insights from large high-dimensional datasets. Formally, an "insight" is a strong manifestation of a statistical property of the data, e.g., high correlation between two attributes, high skewness or concentration about the mean of a single attribute, a strong clustering of values, and so on. For each insight type, Foresight initially presents visualizations of the top
k
instances in the data, based on an appropriate ranking metric. The user can then look at "nearby" insights by issuing "insight queries" containing constraints on insight strengths and data attributes. Thus the user can directly explore the space of insights, rather than the space of data dimensions and visual encodings as in other visual recommender systems. Foresight also provides "global" views of insight space to help orient the user and ensure a thorough exploration process. Furthermore, Foresight facilitates interactive exploration of large datasets through fast, approximate sketching.
A BAD demonstration
Authors: Jacobs Steven , Uddin Md Yusuf Sarwar , Carey Michael , Hristidis Vagelis , Tsotras Vassilis J. , Venkatasubramanian N. , Wu Yao , Safir Syed , Kaul Purvi , Wang Xikui , Qader Mohiuddin Abdul , Li Yawei
Published: September 2017

Nearly all of today's Big Data systems are
passive
in nature. We demonstrate our Big
Active
Data ("BAD") system, a scalable system that continuously and reliably captures Big Data and facilitates the timely and automatic delivery of new information to a large population of interested users as well as supporting analyses of historical information. We built our BAD project by extending an existing scalable, open-source BDMS (AsterixDB [1]) in this active direction. In this demonstration, we allow our audience to participate in an emergency notification application built on top of our BAD platform, and highlight its capabilities.
Complex event recognition in the big data era
Authors: Giatrakos Nikos , Artikis Alexander , Deligiannakis Antonios , Garofalakis Minos
Published: September 2017

The concept of event processing is established as a generic computational paradigm in various application fields, ranging from data processing in Web environments, over maritime and transport, to finance and medicine. Events report on state changes of a system and its environment. Complex Event Recognition (CER) in turn, refers to the identification of complex/composite events of interest, which are collections of simple events that satisfy some pattern, thereby providing the opportunity for reactive and proactive measures. Examples include the recognition of attacks in computer network nodes, human activities on video content, emerging stories and trends on the Social Web, traffic and transport incidents in smart cities, fraud in electronic marketplaces, cardiac arrhythmias, and epidemic spread. In each scenario, CER allows to make sense of Big event Data streams and react accordingly. The goal of this tutorial is to provide a step-by-step guide for realizing CER in the Big Data era. To do so, it elaborates on major challenges and describes algorithmic toolkits for optimized manipulation of event streams characterized by high volume, velocity and/or lack of veracity, placing emphasis on distributed CER over potentially heterogeneous (data variety) event sources. Finally, we highlight future research directions in the field.
Intelligent probing for locality sensitive hashing
Authors: Lv Qin , Josephson William , Wang Zhe , Charikar Moses , Li Kai
Published: September 2017

The past decade has been marked by the (continued) explosion of diverse data content and the fast development of intelligent data analytics techniques. One problem we identified in the mid-2000s was similarity search of feature-rich data. The challenge here was achieving both high accuracy and high efficiency in high-dimensional spaces. Locality sensitive hashing (LSH), which uses certain random space partitions and hash table lookups to find approximate nearest neighbors, was a promising approach with theoretical guarantees. But LSH alone was insufficient since a large number of hash tables were required to achieve good search quality. Building on an idea of Panigrahy, our multi-probe LSH method introduced the idea of intelligent probing. Given a query object, we strategically probe its neighboring hash buckets (in a query-dependent fashion) by calculating the statistical probabilities of similar objects falling into each bucket. Such intelligent probing can significantly reduce the number of hash tables while achieving high quality. In this paper, we revisit the problem motivation, the challenges, the key design considerations of multi-probe LSH, as well as discuss recent developments in this space and some questions for further research.
Arzneimittelausgaben nach der Gesundheitsausgabenrechnung
Authors: Brungs Stefan
Published: September 2017

Die Gesundheitsausgabenrechnung des Statistischen Bundesamtes ist ein sekundärstatistisches Rechenwerk, das auf eine Vielzahl an Verwaltungsdaten zurückgreift. Sie liefert eine jährliche, dreidimensional gegliederte Erfassung der Ausgaben für Waren und Dienstleistungen im deutschen Gesundheitswesen von 1992 bis zum aktuellen Berichtsjahr 2015. Die Daten können aufgrund ihrer Tiefe als Grundlage für Forschungs- und Politikanalysen dienen, wie dieser Artikel am Beispiel der Arzneimittel zeigt.
Memantine and Ketamine Differentially Alter NMDA Receptor Desensitization
Authors: Glasgow Nathan G. , Povysheva Nadezhda V. , Azofeifa Andrea M. , Johnson Jon W.
Published: September 2017

Memantine and ketamine are clinically useful NMDA receptor (NMDAR) open channel blockers that inhibit NMDARs with similar potency and kinetics, but display vastly different clinical profiles. This discrepancy has been hypothesized to result from inhibition by memantine and ketamine of overlapping but distinct NMDAR subpopulations. For example, memantine but not ketamine may inhibit extrasynaptic NMDARs more effectively than synaptic NMDARs. However, the basis for preferential NMDAR inhibition depending on subcellular location has not been investigated systematically. We integrated recordings from heterologously expressed single NMDAR subtypes, kinetic modeling, and recordings of synaptically evoked NMDAR responses in acute brain slices to investigate mechanisms by which channel blockers may distinguish NMDAR subpopulations. We found that memantine and ketamine differentially alter NMDAR desensitization and that memantine stabilizes a Ca2+-dependent desensitized state. As a result, inhibition by memantine of GluN1/2A receptors in tsA201 cells and of native synaptic NMDARs in cortical pyramidal neurons from mice of either sex increased in conditions that enhanced intracellular Ca2+accumulation. Therefore, differential inhibition by memantine and ketamine based on NMDAR location is likely to result from location dependence of the intensity and duration of NMDAR activation. Modulation of Ca2+-dependent NMDAR desensitization is an unexplored mechanism of inhibitory action with the potential to endow drugs with NMDAR selectivity that leads to superior clinical profiles. Our results suggest that designing compounds to target specific receptor states, rather than specific receptor types, may be a viable strategy for future drug development.

SIGNIFICANCE STATEMENTMemantine and ketamine are NMDA receptor (NMDAR) channel-blocking drugs with divergent clinical effects. Understanding mechanistically their differential actions may advance our understanding of nervous system disorders and suggest strategies for the design of more effective drugs. Here, we show that memantine and ketamine have contrasting effects on NMDAR desensitization. Ketamine binding decreases occupancy of desensitized states of the GluN1/2B NMDAR subtype. In contrast, memantine binding increases occupancy of GluN1/2A and native NMDAR desensitized states entered after accumulation of intracellular Ca2+, a novel inhibitory mechanism. These properties may contribute to inhibition of distinct NMDAR subpopulations by memantine and ketamine and help to explain their differential clinical effects. Our results suggest stabilization of Ca2+-dependent desensitized states as a new strategy for pharmaceutical neuroprotection.
基于创新创业教育的工程造价专业人才培养研究
Authors: 肖 昊
Published: September 2017

随着市场经济的不断完善，市场竞争日益激烈，建筑企业为了降低施工成本，提高项目工程的经济效益，对工程造价人才提出了更高要求。高校作为人才的培养基地，工程造价专业的学生为了适应社会发展的需要，必须加强创新创业教育。基于此，本文阐述了创新创业教育中人才培养的必要性，对基于创新创业教育的工程造价专业人才培养模式及其策略进行了探讨分析，旨在使工程造价专业的学生适应社会变化发展的要求。
试论测绘新技术在工程测量中的应用
Authors: 张 世锋
Published: September 2017

工程测量工作是确保工程施工质量的重要前提。现代的工程市场竞争越来越激烈，为了能够保证施工企业继续生存与发展，开始对各种测绘技术进行研究，并应用到测量工作中去，旨在推动测量工作顺利进行，并促进新技术的推广。本文从应用的角度出发，论述了各种测绘新技术在测量工作的应用。
Sexismo y homofobia en los adolescentes de una institución educativa pública
Authors: Bernuy Castromonte Breiding Junior , Noe Grijalva Hugo Martìn
Published: September 2017

La investigación explora la relación entre sexismo y homofobia en adolescentes de una institución educativa pública de Chimbote. El diseño de investigación fue descriptivo-correlacional  con una muestra de 406 estudiantes, varones y mujeres de 1° a 5° grado de nivel secundaria. Fueron evaluados con la Escala de Detección de Sexismo de Ramos, Cuadrado y Recio (2007) adaptación de Acosta (2010)  y la Escala de Homofobia moderna de Raja y Stokes (2005) adaptación de Paredes (2013). Los resultados de la investigación refleja una relación muy significativa, directa y fuerte que indica que a mayor sexismo en los adolescentes, mayores son las actitudes homofóbicas que puedan mostrar. Para sexismo hostil y homofobia hacia gay se obtiene una correlación de (r=.641** p<.01) y hacia lesbianas (r=.658** p<.01); entre sexismo benévolo y homofobia hacia gay (r=.574** p<.01) y hacia lesbianas (r=.646** p<.01). Se identifica niveles de sexismo, según género, un nivel alto de sexismo hostil y benévolo para la población masculina  con un 14.1% y 15.7% respectivamente. También se encuentra niveles de homofobia, según género, en adolescentes hacia personas gay y lesbianas con un 35.3% y 25.3% respectivamente.
An Integrated Research Framework for Effect of EWOM
Authors: Li Jie , Xue Wenyi , Yang Fang , Li Yakun
Published: September 2017

With the development of the electronic commerce, the electronic word-of-mouth (eWOM) has become important reference information for consumer shopping. EWOM has attracted considerable interest from researchers in the past decade. In this paper, a research review is conducted and an integrated framework is proposed on the effect of eWOM. The effect of eWOM are influenced by its characteristics, communicators, and other factors. The characteristics of eWOM include the source, the volume and the valence. The communicators of eWOM refer to the sender, the receiver and the relationship between them. In addition, dispersion and consistency, persistence and observability, anonymity and deception, and community engagement are related factors for the effect of eWOM.