Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Predictors and Outcome of Metabolic Acidosis in Under-Five Children Admitted to an Urban Hospital in Bangladesh with Diarrhea and Pneumonia

Background Clinical features of metabolic acidosis and pneumonia frequently overlap in young diarrheal children, resulting in differentiation from each other very difficult. However, there is no published data on the predictors of metabolic acidosis in diarrheal children also having pneumonia. Our objective was to evaluate clinical predictors of metabolic acidosis in under-five diarrheal children with radiological pneumonia, and their outcome. Methods We prospectively enrolled all under-five children (n = 164) admitted to the Special Care Ward (SCW) of the Dhaka Hospital of icddr, b between September and December 2007 with diarrhea and radiological pneumonia who also had their total serum carbon-dioxide estimated. We compared the clinical features and outcome of children with radiological pneumonia and diarrhea with (n = 98) and without metabolic acidosis (n = 66). Results Children with metabolic acidosis more often had higher case-fatality (16% vs. 5%, p = 0.039) compared to those without metabolic acidosis on admission. In logistic regression analysis, after adjusting for potential confounders such as age of the patient, fever on admission, and severe wasting, the independent predictors of metabolic acidosis in under-five diarrheal children having pneumonia were clinical dehydration (OR 3.57, 95% CI 1.62–7.89, p = 0.002), and low systolic blood pressure even after full rehydration (OR 1.02, 95% CI 1.01–1.04, p = 0.005). Proportions of children with cough, respiratory rate/minute, lower chest wall indrawing, nasal flaring, head nodding, grunting respiration, and cyanosis were comparable (p>0.05) among the groups. Conclusion and Significance Under-five diarrheal children with radiological pneumonia having metabolic acidosis had frequent fatal outcome than those without acidosis. Clinical dehydration and persistent systolic hypotension even after adequate rehydration were independent clinical predictors of metabolic acidosis among the children. However, metabolic acidosis in young diarrheal children had no impact on the diagnostic clinical features of radiological pneumonia which underscores the importance of early initiation of appropriate antibiotics to combat morbidity and deaths in such population.
A P2P Security Model Based on Trust and Availability

In order to overcome the existing deficiencies that studies pure trust mechanism in the current P2P research, the concept of the availability grade and the reputation grade such as the subject and the object are introduced. A new P2P access control model based on trust and availability is defined, which strategies are compatible and expansion of the existing access control strategy, by used the existing access control strategies and model ideas, and it applies to any of the P2P network environment. It is a security model after analysis and discussion, which is positive on researched on the P2P access control.
A CAS for Finding the Best Strategy for Prisoner ’ s Dilemma

Prisoner’s Dilemma (PD) is a typical type of non-zero-sum game in game theory. Since first raised by Merrill Flood and Melvin Dresher in 1950’s, a lot of research has been done in this area, especially after Robert Axelrod introduced the concept of the iterated prisoner’s dilemma in his book “The Evolution of Cooperation” in 1984. In this project, we have explored a complex adaptive system (CAS) designed for finding the “best” strategy for playing PD. The winning strategy depends on the starting conditions. After running the system for a while, an interesting pattern emerges. First, there is an initial consolidation of starting strategies. Second, one (and the same) strategy emerges as the favorite one in the middle of the run. In the end, however, either Tit-for-Tat or “History-Matters” wins the “minds” of the agents. Both of those strategies are of the “cooperate” flavor.
Assamese Numeral Speech Recognition using Multiple Features and Cooperative LVQ

A set of Artificial Neural Network (ANN) based meth- ods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a micro- phone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.
Item Retrieval and Competition in Noun and Verb Generation: An fMRI Study

Selection between competing responses and stimulus-response association strength is thought to affect performance during verb generation. However, the specific contribution of these two processes remains unclear. Here we used fMRI to investigate the role of selection and association within frontal and BG circuits that are known to be involved in verb production. Subjects were asked to generate verbs from nouns in conditions requiring either high or low selection, but with constant association strength, and in conditions of weak or strong association strength, now with constant selection demands. Furthermore, we examined the role of selection and association during noun generation from noun stimuli. We found that the midpart of the left inferior frontal gyrus was more active in conditions requiring high compared with low selection, with matched association strength. The same left inferior frontal region activated irrespective of verb or noun generation. Results of ROI analyses showed effects of association strength only for verb generation and specifically in the anterior/ventral part of the left inferior frontal gyrus. Moreover, the BG were more active when weakly associated verbs had to be produced relative to weakly associated nouns. These results highlight a functional segregation within the left inferior frontal gyrus for verb generation. More generally, the findings suggest that both factors of selection between competing responses and association strength are important during single-word production with the latter factor becoming particularly critical when task-irrelevant stimuli interfere with the current task (here nouns during verb production), triggering additional activation of the BG.
Fluconazole susceptibility testing of Candida inconspicua clinical isolates: comparison of four methods.

Since ﬂuconazole is the most widely used drug in the clinicalsetting, and in the case of rare Candida species susceptibilitytest results may precede deﬁnitive identiﬁcation (24 or 48h ver-sus 48 or 72h), the method used for susceptibility testing shouldbe suitable to correctly determine the ﬂuconazole susceptibilitynot only of the four most frequent species, but also of relativelyfrequently isolated rare species.The aim of our study was to evaluate Etest, Fungitest andmodiﬁed BMD methods as alternatives for determination ofﬂuconazole susceptibility of our C. inconspicua clinicalisolates and to compare their agreement with the standardmethod.The isolates studied included 57 C. inconspicua strainsisolated from 48 patients during a 3 year period (2001–2003). Twenty-two of the 42 hospitalized patients were immunocom-promised and 15 were hospitalized in seven different intensivecare units. Eleven patients received ﬂuconazole previously. Themajority of specimens were from the upper and lower respiratorytract (16 and 24, respectively), but wound, blood and genital iso-lates were also obtained. Inpatients were treated at 10 separateclinics at different times. Identiﬁcation of the isolates was carried out as described ear-lier.
Collaborative IDS Framework for Cloud

Cloud computing is used extensively to deliver utility computing over the Internet. Defending network accessible Cloud resources and services from various threats and attacks is of great concern. Intrusion Detection System (IDS) has become popular as an important network security technology to detect cyber-attacks. In this paper, we propose a novel Collaborative IDS (CIDS) Framework for cloud. We use Snort to detect the known stealthy attacks using signature matching. To detect unknown attacks, anomaly detection system (ADS) is built using Decision Tree Classifier and Support Vector Machine (SVM). Alert Correlation and automatic signature generation reduce the impact of Denial of Service (DoS)/Distributed DoS (DDoS) attacks and increase the performance and accuracy of IDS.
Foreign object detection based on circular bistatic synthetic aperture radar

Synthetic Aperture Radar is well known for producing a radar image of the ground, so it can be used for detecting on-the-ground object which is interesting for some applications. A possible application can be Foreign Object Detection (FOD), which is an important issue in aviation safety. A ground-based Circular Bistatic Synthetic Aperture Radar (Circular-BiSAR) is introduced in this paper. The circular movement makes it more practical while the bistatic configuration offers some advantages. Wideband Linear Frequency Modulated (LFM) chirp pulses are employed here, for transmission and reception of reflection pulses to and from the under test object. A simulated model is developed for the system which analyzes the transmitting, receiving, Doppler and LFM signals by considering the distances and movement of antennas. A prototype system is launched, and some experiments are done to detect and localize various objects based on their reflection properties of microwaves. A processing algorithm is proposed in this paper to confirm the detection. The results show that the proposed system can detect and localize on-the ground objects with as small a dimension as 2 cm height and 2 cm diameter located several metres away.
Committing to Peace: The Successful Settlement of Civil Wars

List of Figures ix List of Tables xi Acknowledgments xiii PART ONE: THEORY 1 1. Introduction 3 2. Theory and Hypotheses 19 PART TWO: DATA AND QUANTITATIVE ANALYSIS 45 3. Measuring the Variables 47 4. Quantitative Tests 70 5. A Closer Look at the Findings 92 PART THREE: CASE STUDIES 109 6. Negotiating for Security Guarantees: The Civil War in Zimbabwe 113 7. The Breakdown of Rwanda's Peace Process 143 8. Explaining the Resolution of Civil Wars 160 Appendix 1 169 Appendix 2 171 Bibliography 177 Index 193
Internet statistical measurement - sampling through overbiasing

In this paper, we propose an IP address-based approach to track the growth of the Web for making a reliable and accurate estimate of the IP address usage. Our method uses a proper sampling of the entire IP address space, resulting in a significant reduction of effort to obtain an accurate estimate. A thorough analysis of the proposed improved Importance Sampling approach is presented. Based on the measurement of the number of active Web servers over the past years, an exponential growth of the Web is observed and modeled.
A Kantian pattern of knowledge, the observation representation

This paper suggests a new pattern of human knowledge. Its execution represents an important stage in the general framework of aiming the building of an artificial cognitive system. First the general presentation of the artificial cognitive system, its objective, main principles and implementation phases are highlighted. The known patterns, which have a cultural (philosophical, psychological and linguistic) origin are then analyzed. Finally the details concerning the proposed pattern are pointed out.
Transcutaneous Electrical Nerve Stimulation for Phantom Pain and Stump Pain in Adult Amputees

Abstract Following amputation, 50% to 90% of individuals experience phantom and/or stump pain. Transcutaneous electrical nerve stimulation (TENS) may prove to be a useful adjunct analgesic intervention, although a recent systematic review was unable to judge effectiveness owing to lack of quality evidence. The aim of this pilot study was to gather data on the effect of TENS on phantom pain and stump pain at rest and on movement. Ten individuals with a transtibial amputation and persistent moderate‐to‐severe phantom and/or stump pain were recruited. Inclusion criteria was a baseline pain score of ≥3 using 0 to 10 numerical rating scale (NRS). TENS was applied for 60 minutes to generate a strong but comfortable TENS sensation at the site of stump pain or projected into the site of phantom pain. Outcomes at rest and on movement before and during TENS at 30 minutes and 60 minutes were changes in the intensities of pain, nonpainful phantom sensation, and prosthesis embodiment. Mean (SD) pain intensity scores were reduced by 1.8 (1.6) at rest (P < 0.05) and 3.9 (1.9) on movement (P < 0.05) after 60 minutes of TENS. For five participants, it was possible to project TENS sensation into the phantom limb by placing the electrodes over transected afferent nerves. Nonpainful phantom sensations and prosthesis embodiment remained unchanged. This study has demonstrated that TENS has potential for reducing phantom pain and stump pain at rest and on movement. Projecting TENS sensation into the phantom limb might facilitate perceptual embodiment of prosthetic limbs. The findings support the delivery of a feasibility trial.
Building Collaborative Capacity for Homeland Security

Abstract : The purpose of this project was to build a foundation of relevant knowledge about interorganizational collaboration that would assist local, state and federal officials in their management of activities related to Homeland Security. Academics and practitioners stress the criticality of coordinating the efforts of federal, state, local and private sectors. Some barriers to interorganizational collaboration include: missions that are at odds with one another, unclear roles and responsibilities lack of accountability. Managers of homeland security will need to find ways to overcome these barriers and work together more effectively. This project is meant to discover the factors that contribute to and inhibit collaboration. The first phase of the research focused on the development of a conceptual model of interagency collaboration. Phase II was an action-based workshop to gather data from a group of 30 senior homeland security managers. Nine major topics that were central to interagency collaboration were identified in Phase III. We anticipate that these deliverables will be used for future workshops, seminars, short class modules or longer graduate-level courses. Future plans include developing a diagnostic survey. This diagnostic tool could be used by HLS organizations to evaluate their current collaborative capacity and, based on this assessment, establish action plans to improve their collaborative capacity.
Nonlinear Modeling of Economic and Financial Time-series

Within the subprime crisis (2007) and the recent global financial crisis of 2008-2009, we have observed significant decline, corrections and structural changes in most US and European financial markets. Furthermore, it seems that this crisis has been rapidly transmitted toward the most developed and emerging countries and has strongly affected the whole economy. This volume aims to present recent researches in linear and nonlinear modelling of economic and financial time-series. The several discussions of empirical results of its chapters clearly help to improve the understanding of the financial mechanisms inherent to this crisis. They also yield an important overview on the sources of the financial crisis and its main economic and financial consequences. The book provides the audience a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It addresses the empirical techniques needed by economic agents to analyze the dynamics of these markets and illustrates how they can be applied to the actual data. It also presents and discusses new research findings and their implications.
An approach of web text information filtering based on domain ontology to expand users' requirements

Semantic-based information filtering has become a hotspot in text filtering field. Based on the research of traditional text information filtering method which includes too little semantic information to represent user requirements and be understood by the computer, and leads the filtering result not to coincidence of user demands as well as significant influence on filtration performance. This paper presents a web text information filtering method that employs domain ontology to extend customer requirements aiming at these problems. This method includes the semantic extension of user profile based on domain-ontology as well as expression, and the matching algorithm of user demand and the file waiting to be filtered. Firstly, check whether the user requirements belong to domain ontology according to membership degree. Subsequently, deduce and extend the meaning of user demand on the basis of concept description, relational definition and rules of domain ontology. Finally, match document and user demand vector representation after expressing user requirements and file waiting to be filtered by vector space model. The experiment showed this approach can yields good effect on information filtering.
Gastrointestinal urease in man' Part I Activity of mucosal urease

Mucosal estimations of urease show that it is highest in the gastric mucosa and lowest in the large intestine. It seems that bacterial urease activity may be limited to the colon. The relationship postulated between hepatic coma and hyperammonaemia implicates the gastrointestinal tract as a major source of the excess ammonia in the peripheral blood of some patients with cirrhosis (
An SVC-MDC video coding scheme using the multi-core parallel programming paradigm for P2P video streaming

In this paper, we propose a COmbined SVC-MDC (Scalable Video Coding & Multiple Description Coding) video coding scheme using the multi-core parallel programming paradigm for P2P video streaming, which is denoted Co-SVC-MDC. To date, P2P video streaming applications are widely popular and emphasized, e.g., PPstream and PPlive, because of higher transmission speed and data availability. However, in the heterogeneous P2P network environment, users are able to utilize PDA, notebook or desktop computer through distinct network interfaces to get on-demand videos ubiquitously. To provide distinct spatial-resolution/fidelity videos and flexible video transmission (playback) over P2P networks, a brand new coding architecture needs to be devised. In the proposed Co-SVC-MDC coding scheme, distinct MDC descriptions contain distinct portions of raw video frames, and each raw frame can be compressed as base layer and SVC enhancement layers. In our experiments, a real implementation of Co-SVC-MDC is exhibited and corresponding performances, e.g., PSNR and decoding speeds, are compared with original SVC in distinct congestion-level P2P networks.
On the Order of Search for Personal Identification with Biometric Images

The processing time of personal identification can be a critical problem in systems with a large number of users. This paper proposes an efficient algorithm for personal identification with biometric images. The algorithm reduces the number of image comparisons for the search of a similar image to the query image by preparing a suitable order of image comparison. The candidates of the order are decided based on the similarities between the registered images, and then the order is selected according to the results of comparisons between the query image and a small number of images. This paper also evaluates the algorithm by experiments with palmprint images in terms of the number of image comparisons and the error rate of personal identification. As the result, the algorithm reduces the number of comparisons to 30% of the standard linear search algorithm with no loss of the error rate.
Forest-to-String Statistical Translation Rules

In this paper, we propose forest-to-string rules to enhance the expressive power of tree-to-string translation models. A forestto-string rule is capable of capturing nonsyntactic phrase pairs by describing the correspondence between multiple parse trees and one string. To integrate these rules into tree-to-string translation models, auxiliary rules are introduced to provide a generalization level. Experimental results show that, on the NIST 2005 Chinese-English test set, the tree-to-string model augmented with forest-to-string rules achieves a relative improvement of 4.3% in terms of BLEU score over the original model which allows treeto-string rules only.
Re-regulation of commodity derivative markets: Critical assessment of current reform proposals in the EU and the US

In the context of recent commodity price hikes, a political consensus has emerged on regulatory measures to reduce excessive speculation in commodity derivative markets. This paper gives an overview of current reform proposals of commodity derivate market regulation at the international (G20), US and EU level and assesses their scope and limitations. For such an assessment, the primary functions of commodity derivative markets for the real economy, i.e. price discovery and price risk hedging for commercial traders have to be taken as a benchmark. The paper concludes that important regulatory initiatives have been under way with a focus on improving transparency, regulating over the counter trade, installing position limits and strengthening regulatory authorities. However, there are important limitations, in particular in the form of broad exemptions (e.g. concerning position limits and commercial traders). Regulations that would more substantially reduce the dominance of financial investors and ensure the dominance of fundamentally based trading strategies have only marginally been addressed, such as restrictions on certain trading strategies (e.g. indexbased investments, technical/algorithmic trading, high frequency trading) and price stabilization mechanisms such as a multitier financial transaction tax. A prerequisite for effective regulation is a pro-active, flexible and dynamic approach that reflects on the risks of failure and adapts regulations if necessary given the changing dynamics and complexities of markets. Further, effective regulation has to take into account the multiple and interrelated roles of financial and large commercial traders being increasingly involved in speculative derivative and physical commodity trading.