Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Pneumococcal Vaccination on Nasopharyngeal Carriage of Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, and Staphylococcus aureus in Fijian Children

ABSTRACT The 7-valent pneumococcal conjugate vaccine (PCV7) reduces carriage of vaccine type Streptococcus pneumoniae but leads to replacement by nonvaccine serotypes and may affect carriage of other respiratory pathogens. We investigated nasopharyngeal carriage of S. pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, and Staphylococcus aureus in Fijian infants participating in a pneumococcal vaccine trial using quantitative PCR. Vaccination did not affect pathogen carriage rates or densities, whereas significant differences between the two major ethnic groups were observed.
Greedy sparse signal reconstruction from sign measurements

This paper presents Matched Sign Pursuit (MSP), a new greedy algorithm to perform sparse signal reconstruction from signs of signal measurements, i.e., measurements quantized to 1-bit. The algorithm combines the principle of consistent reconstruction with greedy sparse reconstruction. The resulting MSP algorithm has several advantages, both theoretical and practical, over previous approaches. Although the problem is not convex, the experimental performance of the algorithm is significantly better compared to reconstructing the signal by treating the quantized measurement as values. Our results demonstrate that combining the principle of consistency with a sparsity prior outperforms approaches that use only consistency or only sparsity priors.
Requirements specification and design of knowledge discovery and source monitoring services for a collaborative network platform

This report presents, as main goal, a collaborative platform requirements specification, that would serve as a base to the design of two service modules related to an abstract knowledge management module. This platform is within the scope of the H-Know European project, to help the SME's, related to the rehabilitation construction area, to work together, sharing knowledge and improving their way to work. For the purpose of eliciting the requirements, it has been used the methodology developed to the H-Know project, that made use of a scenario-based requirements engineering that has been deeply studied. Based on a first iteration of the scenarios developed by the SME's involved, were made some storyboards that would help to present and discuss with the future system users, the main system requirements. After eliciting the requirements, the second purpose of this work was to design the modules of knowledge discovery and knowledge source monitoring. The first one has been designed to grant a easy and innovative way to discover knowledge making use of the ontology browser or to query a simple common knowledge repository. The second module purpose was achieve the monitoring of any kind of knowledge sources, as well as to customize, through the use of RSS services, the knowledge within the personal interest areas. This monitoring would be both internal and external, like the H-Know blogs, forums and other knowledge sharing applications, as well as the external RSS services that might interest the end-users.
A large carbon sink in the woody biomass of Northern forests

The terrestrial carbon sink, as of yet unidentified, represents 15–30% of annual global emissions of carbon from fossil fuels and industrial activities. Some of the missing carbon is sequestered in vegetation biomass and, under the Kyoto Protocol of the United Nations Framework Convention on Climate Change, industrialized nations can use certain forest biomass sinks to meet their greenhouse gas emissions reduction commitments. Therefore, we analyzed 19 years of data from remote-sensing spacecraft and forest inventories to identify the size and location of such sinks. The results, which cover the years 1981–1999, reveal a picture of biomass carbon gains in Eurasian boreal and North American temperate forests and losses in some Canadian boreal forests. For the 1.42 billion hectares of Northern forests, roughly above the 30th parallel, we estimate the biomass sink to be 0.68 ± 0.34 billion tons carbon per year, of which nearly 70% is in Eurasia, in proportion to its forest area and in disproportion to its biomass carbon pool. The relatively high spatial resolution of these estimates permits direct validation with ground data and contributes to a monitoring program of forest biomass sinks under the Kyoto protocol.
Sex Disparities in Control and Treatment of Modifiable Cardiovascular Disease Risk Factors Among Patients With Diabetes

OBJECTIVE—Cardiovascular disease (CVD) mortality has decreased in men but not in women with diabetes. We investigated whether sex differences in control and treatment of CVD risk factors might underlie this disparity. RESEARCH DESIGN AND METHODS—We performed cross-sectional analyses from a cohort of patients with diabetes sampled from 10 U.S. managed care health plans. Study end points included not being in control for CVD risk factors (≥140 mmHg for systolic blood pressure [SBP], ≥3.35 mmol/l for LDL cholesterol, and ≥8.0% for A1C) and the intensity of medication management (number of medication classes) for patients not in control. Logistic regression models with random intercepts were used to adjust probabilities of control and management for demographics, clinical characteristics, and clustering within health plans. RESULTS—There were 1,315 women and 1,575 men with a history of CVD and 3,415 women and 2,516 men without a history of CVD. Among patients with CVD, adjusted estimated probabilities for not being in control and risk differences varied significantly between men and women for SBP (men 41.2%, women 46.6%; risk difference −5.4% [95% CI −9.5 to −1.3]) and LDL cholesterol (men 22.4%, women 28.3%; risk difference −5.9% [−9.9 to −1.8]). There were no significant sex differences in intensity of medication management for patients not in control. In patients without CVD there were no significant differences in control or intensity of medication management. CONCLUSIONS—In diabetic patients with CVD, poorer control of SBP and LDL cholesterol for women may contribute to the sex disparity in CVD mortality trends.
Multilevel-Huffman Test-Data Compression for IP Cores With Multiple Scan Chains

Various compression methods have been proposed for tackling the problem of increasing test-data volume of contemporary, core-based systems. Despite their effectiveness, most of the approaches that are based on classical codes (e.g., run-lengths, Huffman) cannot exploit the test-application-time advantage of multiple-scan-chain cores, since they are not able to perform parallel decompression of the encoded data. In this paper, we take advantage of the inherent parallelism of Huffman decoding and we present a generalized multilevel Huffman-based compression approach that is suitable for cores with multiple scan chains. The size of the encoded data blocks is independent of the slice size (i.e., the number of scan chains), and thus it can be adjusted so as to maximize the compression ratio. At the same time, the parallel data-block decoding ensures the exploitation of most of the scan chains' parallelism. The proposed decompression architecture can be easily modified to suit any Huffman-based compression scheme.
EmStar: An Environment for Developing Wireless Embedded Systems Software

Recently, increasing research attention has been directed toward wireless sensor networks: collections of small, low-power nodes, physically situated in the environment, that can intelligently deliver high-level sensing results to the user. As the community has moved into more complex design efforts—large-scale, longlived systems that truly require self-organization and adaptivity to the environment—a number of important software design issues have arisen. The data reduction process is critical for meeting energy and channel capacity constraints by preventing raw sensor time-series from being delivered. However, the lack of raw data prevents the data reduction process itself from being evaluated. Simulation is difficult to apply; the network’s physical situatedness makes it sensitive to subtleties of sensors and wireless communication channels that are difficult to model. A second problem that arises is that the traditional layered protocol stack, designed to emphasize conceptual abstraction and reusability, has too high of an efficiency cost in this domain where efficiency is paramount. In this paper, we describe EmStar, a Linux-based software framework that addresses these issues. EmStar’s novel execution environment encompasses pure simulation, true in-situ deployment, and a hybrid mode that combines simulation with real wireless communication and sensors situated in the environment. Each of these modes run the same code and use the same configuration files, allowing developers to seamlessly iterate between the convenience of simulation and the reality afforded by physically situated devices. We also describe a modular programming model that allows domain knowledge in one module to affect the modules around it, without sacrificing the advantages of reusability and abstraction that strict layering provides. Using several case studies, we show how EmStar has been applied to building real sensor network services.
Oil exploration data mining image processing

In this paper, an oil exploration software is designed, introduced and implementation. The software is based on the procedures of oil exploration and seismic prospecting. In the environment of Microsoft Visual Studio 2008 with the C++ programming language, the standard SEG-Y seismic data is successfully transferred into visible geological sectional view and histogram chart, which makes the geologists obtain a quick access to the idea of geophysics structures of the target field. With more than one kind of color schemes to be chosen, geologists can highlight different geological structure of the seismic data. Implementation shows good performance of the designed oil exploration data mining image processing software.
Retweet Modeling Using Conditional Random Fields

Among the most popular micro-blogging service, Twitter recently introduced their reblogging service called retweet to allow a user to repopulate another user's content for his followers. It quickly becomes one of the most prominent features on Twitter and an important mean for secondary content promotion. However, it remains unclear what motivates users to retweet and whether the retweeting decisions are predictable based on a user's tweeting history and social relationships. In this paper, we propose modeling the retweet patterns using conditional random fields with a three types of user-tweet features: content influence, network influence and temporal decay factor. We also investigate approaches to partition the social graphs and construct the network relations for retweet prediction. Our experiments demonstrate that CRF can improve prediction effectiveness by incorporating social relationships compared to the baselines that do not.
Note: This Copy Is for Your Personal, Non-commercial Use Only. to Order Presentation-ready Copies for Distribution to Your Colleagues or Clients, Contact Us at Www.rsna.org/rsnarights. Delayed Contrast Enhancement on Mr Images of Myocardium: Past, Present, Future

1 Differential enhancement of myocardial infarction was fi rst recognized on computed tomographic (CT) images obtained with iodinated contrast material in the late 1970s. Gadolinium enhancement of myocardial infarction was initially reported for T1-weighted magnetic resonance (MR) imaging in 1984. The introduction of an inversion-recovery gradient-echo MR sequence for accentuation of the contrast between normal and necrotic myocardium was the impetus for widespread clinical use for demonstrating the extent of myocardial infarction. This sequence has been called delayed-enhancement MR and MR viability imaging. The physiologic basis for differential enhancement of myocardial necrosis is the greater distribution volume of injured myocardium compared with that of normal myocardium. It is now recognized that delayed enhancement occurs in both acute and chronic (scar) infarc-tions and in an array of other myocardial processes that cause myocardial necrosis, infi ltration, or fi brosis. These include myocarditis, hypertrophic cardiomyopathy, amy-loidosis, sarcoidosis, and other myocardial conditions. In several of these diseases, the presence and extent of delayed enhancement has prognostic implications. Future applications of delayed enhancement with development of MR imaging and CT techniques will be discussed. n Describe the mechanism of delayed contrast enhancement of the myocardium. n Describe the expected signal intensity of the infarct core, the peripheral zone, microvascular obstruction, and the remote myocardium on delayed-enhancement images after myocardial infarction. n List the most common delayed-enhancement patterns seen in nonischemic cardiomyopathies. n List two prognostic applications of myocardial delayed-enhancement images. Accreditation and Designation Statement The RSNA is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The RSNA designates this journal-based activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Disclosure Statement The ACCME requires that the RSNA, as an accredited provider of CME, obtain signed disclosure statements from the authors, editors, and reviewers for this activity. For this journal-based CME activity, author disclosures are listed at the end of this article. The editor and the reviewers indicated that they had no relevant relationships to disclose.
Mining negative fuzzy sequential patterns

Many methods have been proposed for mining fuzzy sequential patterns. However, most of conventional methods only consider the occurrences of fuzzy itemsets in sequences. The fuzzy sequential patterns discovered by these methods are called as positive fuzzy sequential patterns. In practice, the absences of frequent fuzzy itemsets in sequences may imply significant information. We call a fuzzy sequential pattern as a negative fuzzy sequential pattern, if it also expresses the absencesof fuzzy itemsets in a sequence. In this paper, we proposed a method for mining negative fuzzy sequential patterns, called NFSPM. In our method, the absences of fuzzy itemsets are also considered. Besides, only sequences with high degree of interestingness can be selected as negative fuzzy sequential patterns. An example was taken to illustrate the process of the algorithm NFSPM. The result showed that our algorithm could prune a lot of redundant candidates, and could extract meaningful fuzzy sequential patterns from a large number of frequent sequences.
Impact of infectious etiology on the outcome of Taiwanese patients hospitalized with community acquired pneumonia.

INTRODUCTION This study aimed to assess the relationships between infectious etiology, empiric treatment, and outcomes in Taiwanese patients with community acquired pneumonia (CAP). METHODOLOGY A retrospective analysis of the data of 208 adult patients from a single medical center was performed with patients classified as having low or high disease severity based on the Pneumonia Severity Index (PSI). Patients with PSI ≤ 90 (n=120) were classified as low severity and patients with PSI > 90 (n=88) were classified as high severity. RESULTS The low-risk group had significantly higher rates of infection with Chlamydia pneumoniae (C. pneumoniae) and Mycoplasma pneumoniae (M. pneumoniae), whereas the high-risk group had significantly higher rates of infection with Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) (p < 0.05). Empiric treatment in both groups was in accordance with the 2007 guidelines issued by the Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS). Twenty-nine of 208 patients (13.9%) died, one in the low-risk group and 28 in the high-risk group. The highest rates of mortality were in patients infected with P. aeruginosa or K. pneumoniae. CONCLUSIONS In the present study, we demonstrated that the patients with different severity had different microbiologic etiology. In general, P. aeruginosa and K. pneumoniae were the most commonly isolated organisms in high-risk patients who died from CAP. We showed that use of the IIDSA/ATS guidelines for treatment of CAP in Taiwan resulted in a better outcome in the low PSI group.
Modifying the CSMA / CD ( IEEE 802 . 3 ) Protocol to Involve a Network Queue ( CSMA / CDNQ )

The carrier sense multiple access protocol with collision detections (CSMA/CD) often suffers from performance issues when it comes to transmission collisions within a network. This paper proposes a solution to the packet starvation effect [3], which is similar to Ethernet capture [2] of CSMA/CD by combining findings from previously performed research to improve CSMA/CD. The proposed solution, carrier sense multiple access with collision detection and network queue (CSMA/CDNQ) modifies the current CSMA/CD protocol by using a network queue to avoid multiple collisions while allowing behavior to resort back to IEEE standard 802.3 (CSMA/CD) in the event of queue failure, thus classifying it as a sometimes centralized, sometimes decentralized multiple access protocol. The Binary Exponential Backoff algorithm is slightly modified in CSMA/CDNQ to allow the queue dominance over the network and each node on the channel will utilize a lock, which is also referred to as the send variable, that controls when the node
A Feasibility Study on Developing IoT/M2M Applications over ETSI M2M Architecture

A common service platform is considered as the key enabler to catalyze the development of IoT/M2M applications for a large variety of vertical markets such as smart energy, smart transportation, home and industry automation, eHealth and connected vehicles. This paper reports an initial effort at National Chiao Tung University in Taiwan with such an experimental approach. We first train our graduate students with an ETSI M2M architecture-compliant service platform OpenMTC from FOKUS, and then charter them with the tasks of developing diverse M2M applications. The effort is used as a feasibility study to investigate how useful the notion of a common service platform for IoT/M2M is and how urgent an international standard is required in defining such a platform. We intend to use the result of the study to create a suitable IoT/M2M curriculum for our students.
Intra-Chunk Dependency Annotation : Expanding Hindi Inter-Chunk Annotated Treebank

We present two approaches (rule-based and statistical) for automatically annotating intra-chunk dependencies in Hindi. The intra-chunk dependencies are added to the dependency trees for Hindi which are already annotated with inter-chunk dependencies. Thus, the intra-chunk annotator finally provides a fully parsed dependency tree for a Hindi sentence. In this paper, we first describe the guidelines for marking intra-chunk dependency relations. Although the guidelines are for Hindi, they can easily be extended to other Indian languages. These guidelines are used for framing the rules in the rule-based approach. For the statistical approach, we use MaltParser, a data driven parser. A part of the ICON 2010 tools contest data for Hindi is used for training and testing the MaltParser. The same set is used for testing the rule-based approach.
On optimal risk sensitive execution problem

This paper considers the risk sensitive optimal execution problem. In the financial market, trading(buying or selling) of large amount of assets usually causes moving of the price to unfavorable direction and further generates additional trading cost. The optimal execution problem is seeking the best execution strategy(control) in a given horizon to trade(buy or sell) certain amount of asset in order to maximize the profit. In this work, instead of considering the sole objective of maximizing the expected profit, we consider the risk sensitive formulation of such a problem, in which the execution risk is combined implicitly. By using the stochastic control approach, the analytical optimal execution strategy is derived. Using different risk sensitive parameter, our model could generate different mean-variance efficient execution strategy, which provides the investor freedom to adjust the execution strategy. Comparing with the traditional risk neutral formulation, our model shows prominent feature in controlling the execution risk.
Sponge: A searchable P2P mobile app store using DHTs

In this paper we propose a novel searchable P2P content storage for storing mobile apps. In the growing need of storing and distributing huge number mobile apps across large number of users, it has been deemed necessary to think of a storage that leverages enormous amount of content space that common people can share these days. In our proposal, we leverage popular P2P stores, such as standard DHTs, for storing apps. One problem with DTHs is that they support flat names (denoted as keys) for content objects, which do not make content objects searchable by their different attributes. When users look for a certain app in an app store, they do not necessarily look by their unique names, instead by a set of attribute-value pairs (multi-attribute queries). We devise a technique, called predicate hashing, by which we hash these attribute-value pairs into hashed keys that are in turn used to locate corresponding apps from the underlying DHT. By doing this we effectively instrument flat named DHTs into reverse ifndexable content store. To this end, we build Sponge, a Kademlia based P2P app store, and do simulation based experiments to show that Sponge can retrieve content against multi-attribute queries.
Transparent System Call Based Performance Debugging for Cloud Computing

Problem diagnosis and debugging in distributed environments such as the cloud and popular distributed systems frameworks has been a hard problem. We explore an evaluation of a novel way of debugging distributed systems, such as the MapReduce framework, by using system calls. Performance problems in such systems can be hard to diagnose and to localize to a specific node or a set of nodes. Additionally, most debugging systems often rely on forms of instrumentation and signatures that sometimes cannot truthfully represent the state of the system (logs or application traces for example). We focus on evaluating the performance debugging of these frameworks using a low level of abstraction system calls. By focusing on a small set of system calls, we try to extrapolate meaningful information on the control flow and state of the framework, providing accurate and meaningful automated debugging.
3D soundfield reproduction using higher order loudspeakers

Three dimensional surround sound reproduction over large areas is a prevailing challenge due to the enormous numbers of loudspeakers required. In this paper, we propose an array of higher order loudspeakers which provide a mode matching solution to the problem based on 3D wavefield translation. It is shown that for a given bandwidth, the use of Lth order sources significantly brings down the minimum loudspeaker requirement by a factor of 1=(L + 1)2. Furthermore, the array is shown to be capable of exterior field cancellation, increasing its performance in echoing environments. Design examples are given for interior field, exterior field and interior and exterior combined field reproduction.