bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enteric Pathogens Exploit the Microbiota-generated Nutritional Environment of the Gut
Authors: Pacheco Alline R. , Sperandio Vanessa 
Published: June 2015

ABSTRACT

Host bacterial associations have a profound impact on health and disease. The human gastrointestinal (GI) tract is inhabited by trillions of commensal bacteria that aid in the digestion of food and vitamin production and play crucial roles in human physiology. Disruption of these relationships and the structure of the bacterial communities that inhabit the gut can contribute to dysbiosis, leading to disease. This fundamental relationship between the host and microbiota relies on chemical signaling and nutrient availability and exchange. GI pathogens compete with the endogenous microbiota for a colonization niche (
1
,
2
). The ability to monitor nutrients and combine this information with the host physiological state is important for the pathogen to precisely program the expression of its virulence repertoire. A major nutrient source is carbon, and although the impact of carbon nutrition on the colonization of the gut by the microbiota has been extensively studied, the extent to which carbon sources affect the regulation of virulence factors by invading pathogens has not been fully defined. The GI pathogen enterohemorrhagic
E. coli
(EHEC) gages sugar sources as an important cue to regulate expression of its virulence genes. EHEC senses whether it is in a gluconeogenic versus a glycolytic environment, as well as fluctuations of fucose levels to fine tune regulation of its virulence repertoire.
Small RNAs Regulate Primary and Secondary Metabolism in Gram-negative Bacteria
Authors: Bobrovskyy Maksym , Vanderpool Carin K. , Richards Gregory R. 
Published: June 2015

ABSTRACT
Over the last decade, small (often noncoding) RNA molecules have been discovered as important regulators influencing myriad aspects of bacterial physiology and virulence. In particular, small RNAs (sRNAs) have been implicated in control of both primary and secondary metabolic pathways in many bacterial species. This chapter describes characteristics of the major classes of sRNA regulators, and highlights what is known regarding their mechanisms of action. Specific examples of sRNAs that regulate metabolism in gram-negative bacteria are discussed, with a focus on those that regulate gene expression by base pairing with mRNA targets to control their translation and stability.
Borrelia burgdorferi
: Carbon Metabolism and the Tick-Mammal Enzootic Cycle
Authors: Corona Arianna , Schwartz Ira 
Published: June 2015

ABSTRACT

Borrelia burgdorferi
, the spirochetal agent of Lyme disease, is a zoonotic pathogen that is maintained in a natural cycle that typically involves mammalian reservoir hosts and a tick vector of the
Ixodes
species. During each stage of the enzootic cycle,
B. burgdorferi
is exposed to environments that differ in temperature, pH, small molecules, and most important, nutrient sources.
B. burgdorferi
has a highly restricted metabolic capacity because it does not contain a tricarboxylic acid cycle, oxidative phosphorylation, or any pathways for
de novo
biosynthesis of carbohydrates, amino acids, or lipids. Thus,
B. burgdorferi
relies solely on glycolysis for ATP production and is completely dependent on the transport of nutrients and cofactors from extracellular sources. Herein, pathways for carbohydrate uptake and utilization in
B. burgdorferi
are described. Regulation of these pathways during the different phases of the enzootic cycle is discussed. In addition, a model for differential control of nutrient flux through the glycolytic pathway as the spirochete transits through the enzootic cycle is presented.
The Fish Pathogen
Vibrio vulnificus
Biotype 2: Epidemiology, Phylogeny, and Virulence Factors Involved in Warm-Water Vibriosis
Authors: Amaro Carmen , Sanjuán Eva , Fouz Belén , Pajuelo David , Lee Chung-Te , Hor Lien-I , Barrera Rodolfo 
Published: June 2015

ABSTRACT

Vibrio vulnificus
biotype 2 is the etiological agent of warm-water vibriosis, a disease that affects eels and other teleosts, especially in fish farms. Biotype 2 is polyphyletic and probably emerged from aquatic bacteria by acquisition of a transferable virulence plasmid that encodes resistance to innate immunity of eels and other teleosts. Interestingly, biotype 2 comprises a zoonotic clonal complex designated as serovar E that has extended worldwide. One of the most interesting virulence factors produced by serovar E is RtxA1
3
, a multifunctional protein that acts as a lethal factor for fish, an invasion factor for mice, and a survival factor outside the host. Two practically identical copies of
rtxA1

3

are present in all biotype 2 strains regardless of the serovar, one in the virulence plasmid and the other in chromosome II. The plasmid also contains other genes involved in survival and growth in eel blood:
vep07
, a gene for an outer membrane (OM) lipoprotein involved in resistance to eel serum and
vep20
, a gene for an OM receptor specific for eel-transferrin and, probably, other related fish transferrins. All the three genes are highly conserved within biotype 2, which suggests that they are under a strong selective pressure. Interestingly, the three genes are related with transferable plasmids, which emphasizes the role of horizontal gene transfer in the evolution of
V. vulnificus
in nutrient-enriched aquatic environments, such as fish farms.
Flare frequency, healthcare resource utilisation and costs among patients with gout in a managed care setting: a retrospective medical claims-based analysis
Authors: Jackson Robert , Shiozawa Aki , Buysman Erin K , Altan Aylin , Korrer Stephanie , Choi Hyon 
Published: June 2015

ObjectivesFor most gout patients, excruciatingly painful gout attacks are the major clinical burden of the disease. The goal of this study was to assess the association of frequent gout flares with healthcare burden, and to quantify how much lower gout-related costs and resource use are for those with infrequent flares compared to frequent gout flares.DesignRetrospective cohort study.SettingAdministrative claims data from a large US health plan.ParticipantsPatients aged 18 years or above, and with evidence of gout based on medical and pharmacy claims between January 2009 and April 2012 were eligible for inclusion. Patient characteristics were assessed during a 12-month baseline period.Outcome measuresFrequency of gout flares, healthcare costs and resource utilisation were assessed in the 12 months following the first qualifying gout claim. Generalised linear models were employed to assess the impact of flare frequency on cost outcomes after adjusting for covariates.Results102 703 patients with gout met study inclusion criteria; 89 201 had 0–1 gout flares, 9714 had 2 flares, and 3788 had 3+ flares. Average counts of gout-related inpatient stays, emergency room visits and ambulatory visits were higher among patients with 2 or 3+ flares, compared to those with 0–1 flares (all p<0.001). Adjusted annual gout-related costs were $1804, $3014 and $4363 in those with 0–1, 2 and 3+ gout flares, respectively (p<0.001 comparing 0–1 flares to 2 or 3+ flares).ConclusionsGout-related costs and resource use were lower for those with infrequent flares, suggesting significant cost benefit to a gout management plan that has a goal of reducing flare frequency.
Gestational age and newborn size according to parental social mobility: an intergenerational cohort study
Authors: Gigante Denise P , Horta Bernardo L , Matijasevich Alicia , Loret de Mola Christian , Barros Aluisio J D , Santos Ina S , Barros Fernando C , Victora Cesar G 
Published: June 2015

BackgroundWe examined the associations between socioeconomic trajectories from birth to adulthood and gestational age and birth size in the next generation, using linked data from two population-based birth cohorts carried out in a Brazilian city. By comparing socioeconomic trajectories of mothers and fathers, we attempted to identify-specific effects of maternal and paternal socioeconomic trajectory on offspring birth weight, birth length, head circumference and gestational age at birth.Methods2 population-based birth cohort studies were carried out in 1982 and 2004 in Pelotas (Brazil); 156 mothers and 110 fathers from the earlier cohort had children in 2004. Gestational age and birth length, weight and head circumference were measured. Analyses were carried out separately for mothers and fathers. Mediation analyses assessed the role of birth weight and adult body mass index (BMI).ResultsAmong mothers, but not for fathers, childhood poverty was strongly associated with smaller size in the next generation (about 400 g in weight and 1.5 cm in height) and shorter gestations (about 2 weeks). Adult poverty did not play a role. For mothers, the associations with gestational age, birth length and weight—but not with head circumference—persisted after adjusting for maternal birth weight and for the height and weight of the grandmother. Maternal birth weight did not mediate the observed associations, but high maternal BMI in adulthood was partly responsible for the association with gestational age.ConclusionsStrong effects of early poverty on gestational age and birth size in the next generation were observed among mothers, but not among fathers. These findings suggest a specific maternal effect of socioeconomic trajectory, and in particular of early poverty on offspring size and duration of pregnancy.
Magnetic susceptibility application: a window onto ancient environments and climatic variations: foreword
Authors: Da Silva A. C. , Whalen M. T. , Hladil J. , Chadimova L. , Chen D. , Spassov S. , Boulvain F. , Devleeschouwer X. 
Published: June 2015

Abstract
Magnetic susceptibility (MS) is a powerful tool, which is being applied increasingly on sedimentary rocks to constrain stratigraphic correlations, or as a palaeo-environmental or palaeo-climatic tool. The origin of the magnetic minerals responsible for the variations in MS can be linked to various phenomena such as detrital inputs, pedogenesis, bacterial precipitation or diagenesis. Therefore, it is critical to improve our knowledge of the origin of the MS signal in order to apply it for correlations or as a proxy. Here, we present a synthesis of the techniques that can be applied to get a better understanding of the origin of the MS signal, through comparison with other palaeo-environmental proxies, through magnetic measurements or through dissolution and direct observation of the extracted minerals. We also propose an overview of the different techniques applied in order to use MS as a correlation tool, and we show various examples of successful applications of MS as a recorder of change in past sea-level and climate. We also present the main results and activities of the IGCP-580 project ‘Application of magnetic susceptibility as a palaeo-climatic proxy on Palaeozoic sedimentary rocks and characterization of the magnetic signal’.
An Improved Competitive Algorithm for Reordering Buffer Management
Authors: Avigdor-Elgrabli Noa , Rabani Yuval 
Published: June 2015

We design and analyze an online reordering buffer management algorithm with improved
O
(log
k
/log log
k
) competitive ratio for nonuniform costs, where
k
is the buffer size. This improves on the best previous result (even for uniform costs) of Englert and Westermann (2005) giving
O
(log
k
) competitive ratio, which was also the best (offline) polynomial time approximation guarantee for this problem. Our analysis is based on an intricate dual fitting argument using a linear programming relaxation for the problem that we introduce in this article.
Intercepting Functions for Memoization
Authors: Suresh Arjun , Swamy Bharath Narasimha , Rohou Erven , Seznec André 
Published: June 2015

Memoization is the technique of saving the results of executions so that future executions can be omitted when the input set repeats. Memoization has been proposed in previous literature at the instruction, basic block, and function levels using hardware, as well as pure software--level approaches including changes to programming language.
In this article, we focus on software memoization for procedural languages such as C and Fortran at the granularity of a function. We propose a simple linker-based technique for enabling software memoization of any dynamically linked pure function by function interception and illustrate our framework using a set of computationally expensive pure functions—the transcendental functions. Transcendental functions are those that cannot be expressed in terms of a finite sequence of algebraic operations (trigonometric functions, exponential functions, etc.) and hence are computationally expensive.
Our technique does not need the availability of source code and thus can even be applied to commercial applications, as well as applications with legacy codes. As far as users are concerned, enabling memoization is as simple as setting an environment variable. Our framework does not make any specific assumptions about the underlying architecture or compiler toolchains and can work with a variety of current architectures. We present experimental results for a x86-64 platform using both gcc and icc compiler toolchains, and an ARM Cortex-A9 platform using gcc. Our experiments include a mix of real-world programs and standard benchmark suites: SPEC and Splash2x. On standard benchmark applications that extensively call the transcendental functions, we report memoization benefits of up to 50% on Intel Ivy Bridge and up to 10% on ARM Cortex-A9.

Memoization was able to regain a performance loss of 76% in bwaves due to a known performance bug in the GNU implementation of the
pow
function. The same benchmark on ARM Cortex-A9 benefited by more than 200%.
Section-Based Program Analysis to Reduce Overhead of Detecting Unsynchronized Thread Communication
Authors: Das Madan , Southern Gabriel , Renau Jose 
Published: June 2015

Most systems that test and verify parallel programs, such as deterministic execution engines, data race detectors, and software transactional memory systems, require instrumenting loads and stores in an application. This can cause a very significant runtime and memory overhead compared to executing uninstrumented code. Multithreaded programming typically allows any thread to perform loads and stores to any location in the process’s address space independently, and such tools monitor all these memory accesses. However, many of the addresses in these unsynchronized memory accesses are only used by a single thread and do not affect other executing threads.
We propose Section-Based Program Analysis (SBPA), a novel way to decompose the program into disjoint code sections to identify and eliminate instrumenting such loads and stores during program compilation so that the program runtime overhead is significantly reduced. Our analysis includes improvements to pointer analysis and uses a few user directives to increase the effectiveness of SBPA further. We implemented SBPA for a deterministic execution runtime environment and were able to eliminate 51% of dynamic memory access instrumentations. When combined with directives, such reduction increased to 63%. We also integrated SBPA with ThreadSanitizer, a state-of-the-art dynamic race detector, and achieved a speedup of 2.43 (2.74 with directives) on a geometric mean basis.
Report on the Seventh Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR'14)
Authors: Alonso Omar , Kamps Jaap , Karlgren Jussi 
Published: June 2015

There is an increasing amount of structure on the Web as a result of modern Web languages, user tagging and annotation, emerging robust NLP tools, and an ever growing volume of linked data. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing the depth of analysis of today's systems. The goal of the ESAIR'14 workshop remained to advance the general research agenda on this core problem, with an explicit focus on one of the most challenging aspects to address in the coming years. The main remaining challenge is on the user's side---the potential of rich document annotations can only be realized if matched by more articulate queries exploiting these powerful retrieval cues---and a more dynamic approach is emerging by exploiting new forms of query autosuggest. How can the query suggestion paradigm be used to encourage searcher to articulate longer queries, with concepts and relations linking their statement of request to existing semantic models? How do entity results and social network data in "graph search" change the classic division between searchers and information and lead to extreme personalization---are you the query? How to leverage transaction logs and recommendation, and how adaptive should we make the system? What are the privacy ramifications and the UX aspects---how to not creep out users.
There was a strong feeling that we made substantial progress. Specifically, the discussion contributed to our understanding of the way forward. First, for notable (head, shoulder, but not tail) entities in semantic search we have reached the level of quality at minimal costs allowing for deployment in major web search engines---the dream has become a reality. Second, entity detection is moving fast into domain specific, personal, and business domains, and has become a vital component for a range of applications. Third, semantic web has exchanged logic for machine learning approaches, and machine learning is the natural unification of semantic web and information retrieval approaches.
DiskAccel
Authors: Tarihi Mojtaba , Asadi Hossein , Sarbazi-Azad Hamid 
Published: June 2015

Disk traces are typically used to analyze real-life workloads and for replay-based evaluations. This approach benefits from capturing important details such as varying behavior patterns, bursty activity, and diurnal patterns of system activity, which are often missing from the behavior of workload synthesis tools. However, accurate capture of such details requires recording traces containing long durations of system activity, which are difficult to use for replay-based evaluation. One way of solving the problem of long storage trace duration is the use of disk simulators. While publicly available disk simulators can greatly accelerate experiments, they have not kept up with technological innovations in the field. The variety, complexity, and opaque nature of storage hardware make it very difficult to implement accurate simulators. The alternative, replaying the whole traces on real hardware, suffers from either long run-time or required manual reduction of experimental time, potentially at the cost of reduced accuracy. On the other hand, burstiness, auto-correlation, and complex spatio-temporal properties of storage workloads make the known methods of sampling workload traces less effective.
In this paper, we present a methodology called DiskAccel to efficiently select key intervals of a trace as representatives and to replay them to estimate the response time of the whole workload. Our methodology extracts a variety of spatial and temporal features from each interval and uses efficient data mining techniques to select the representative intervals. To verify the proposed methodology, we have implemented a tool capable of running whole traces or selective intervals on real hardware, warming up hardware state in an accelerated manner, and emulating request causality while minimizing request inter-arrival time error. Based on our experiments, DiskAccel manages to speed up disk replay by more than two orders of magnitude, while keeping average estimation error at 7.6%.
Memory Row Reuse Distance and its Role in Optimizing Application Performance
Authors: Kandemir Mahmut , Zhao Hui , Tang Xulong , Karakoy Mustafa 
Published: June 2015

Continuously increasing dataset sizes of large-scale applications overwhelm on-chip cache capacities and make the performance of last-level caches (LLC) increasingly important. That is, in addition to maximizing LLC hit rates, it is becoming equally important to reduce LLC miss latencies. One of the critical factors that influence LLC miss latencies is row-buffer locality (i.e., the fraction of LLC misses that hit in the large buffer attached to a memory bank). While there has been a plethora of recent works on optimizing row-buffer performance, to our knowledge, there is no study that quantifies the full potential of row-buffer locality and impact of maximizing it on application performance.
Focusing on multithreaded applications, the first contribution of this paper is the definition of a new metric called (memory) row reuse distance (RRD). We show that, while intra-core RRDs are relatively small (increasing the chances for row-buffer hits), inter-core RRDs are quite large (increasing the chances for row-buffer misses). Motivated by this, we propose two schemes that measure the maximum potential benefits that could be obtained from minimizing RRDs, to the extent allowed by program dependencies. Specifically, one of our schemes (Scheme-I) targets only intra-core RRDs, whereas the other one (Scheme-II) aims at reducing both intra-core RRDs and inter-core RRDs. Our experimental evaluations demonstrate that (i) Scheme-I reduces intra-core RRDs but increases inter-core RRDs; (ii) Scheme-II reduces inter-core RRDs significantly while achieving a similar behavior to Scheme-I as far as intra-core RRDs are concerned; (iii) Scheme-I and Scheme-II improve execution times of our applications by 17% and 21%, respectively, on average; and (iv) both our schemes deliver consistently good results under different memory request scheduling policies.
Reliable Multiple-choice Iterative Algorithm for Crowdsourcing Systems
Authors: Lee Donghyeon , Kim Joonyoung , Lee Hyunmin , Jung Kyomin 
Published: June 2015

The appearance of web-based crowdsourcing systems gives a promising solution to exploiting the wisdom of crowds efficiently in a short time with a relatively low budget. Despite their efficiency, crowdsourcing systems have an inherent problem in that responses from workers can be unreliable since workers are low-paid and have low responsibility. Although simple majority voting can be a solution, various research studies have sought to aggregate noisy responses to obtain greater reliability in results through effective techniques such as Expectation-Maximization (EM) based algorithms. While EM-based algorithms get the limelight in crowdsourcing systems due to their useful inference techniques, Karger et al. made a significant breakthrough by proposing a novel iterative algorithm based on the idea of low-rank matrix approximations and the message passing technique. They showed that the performance of their iterative algorithm is order-optimal, which outperforms majority voting and EM-based algorithms. However, their algorithm is not always applicable in practice since it can only be applied to binary-choice questions. Recently, they devised an inference algorithm for multi-class labeling, which splits each task into a bunch of binary-choice questions and exploits their existing algorithm. However, it has difficulty in combining into real crowdsourcing systems since it overexploits redundancy in that each split question should be queried in multiple times to obtain reliable results.
In this paper, we design an iterative algorithm to infer true answers for multiple-choice questions, which can be directly applied to real crowdsourcing systems. Our algorithm can also be applicable to short-answer questions as well. We analyze the performance of our algorithm, and prove that the error bound decays exponentially. Through extensive experiments, we verify that our algorithm outperforms majority voting and EM-based algorithm in accuracy.