Miracle-dz/UniFAR-FTUs huggingface dataset:
The War Correspondent

The War Correspondent. Greg McLaughlin. London and Sterling, VA, 2002. 232 pp. $69.95 hbk. $22.50 pbk. Famed former CBS anchor Walter Cronkite once wrote, "Nothing in the field of journalism is more glamorous than being a war correspondent. " While that statement can be debated, what is not debatable is that it is an extremely tough, demanding job. That comes across in many ways in Greg McLaughlin's The War Correspondent, which could be a primer for those who want to do this type of reporting and for editors who must select the best person to send off to dangerous foreign locations. McLaughlin, who teaches in media studies at the University of Ulster, has not written just another history of war correspondents as the title suggests. While the history from the Crimean War of 1854-1856 to the end of the twentieth century takes up about half of the book, the other half examines the challenges faced by war correspondents after they have their story and have to put it down on a computer or face the cameras. The book includes correspondents from the English media as well as the United States, some of whom he interviewed, such as Christiane Amanpour of CNN, and thus the author avoids making the book primarily applicable to just one country, thereby increasing its value. For those who are familiar with the history of war correspondents, they will find few insights in the first part of the book. McLaughlin writes well and keeps the reader interested, using stories appropriately, but this is little more than an obligatory opening to put into context the discussion that occurs in the second half of the book. Nevertheless, he is to be commended for doing a thorough search of the literature, as the book's extensive bibliography will show. The bibliography alone makes The War Correspondent a necessary addition to the library of any scholar writing on the subject. But McLaughlin hits his stride in the second half, and suddenly the book becomes more valuable with the issues raised worthy of wide discussion in classes about reporting, ethics, and mass media and society. For example, the author brings up the question of a reporter's detachment, which is an issue in any media story but is particularly pertinent to war coverage. He points to a statement by war correspondent Ed Vulliamy in the British Journalism Review in 1993: I am one of those reporters who cannot see this [war] as "just another story" from which I must remain detached and in which I must be neutral. …
Comparison and Implementation of High Cited Inverse Reinforcement Learning Algorithms in Object World

Inverse reinforcement learning (inverse RL), an inverse process of reinforcement learning (RL), is mainly used to solve problems in extracting a reward function from observed (nearly) optimal behavior of an expert acting in an environment. The extract of a reward function is one of the biggest obstacles of the deployment of reinforcement learning agents in the real world. In many real-world tasks, designing a suitable reward function takes considerable manual tuning. In this paper, we analyze the principles of three high cited inverse RL algorithm, Maximum Margin Planning (MMP), MMPBoost, and Maximum Entropy (MaxEnt), and implement them in the object world. Experiments show that MMP is not sensitive with environment changes and the effect of boosting is remarkable when comparing the results of MMP and MMPBoost. MaxEnt as an energy-based method is of enormous potential.
The Usage of Optical Flow Algorithm to the Problem of Recovery Contour of the Left Ventricle of the Human Heart on the Ultrasound Image Data

Cardiologist builds contour bounding area of the left ventricle (LV) in each frame of the ultrasound video sequence usually in a manual mode. The article describes results of application of semi-automatic algorithm using the optical flow. The visual and qualitative characteristic of contouring results of this algorithm are obtained. This algorithm is used to select the contour on ultrasound images.
DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language

DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments such as SQL, MapReduce, and Dryad in two ways: by adopting an expressive data model of strongly typed . NET objects; and by supporting general-purpose imperative and declarative operations on datasets within a traditional high-level programming language. A DryadLINQ program is a sequential program composed of LINQ expressions performing arbitrary side-effect-free transformations on datasets, and can be written and debugged using standard . NET development tools. The DryadLINQ system automatically and transparently translates the data-parallel portions of the program into a distributed execution plan which is passed to the Dryad execution platform. Dryad, which has been in continuous operation for several years on production clusters made up of thousands of computers, ensures efficient, reliable execution of this plan. We describe the implementation of the DryadLINQ compiler and runtime. We evaluate DryadLINQ on a varied set of programs drawn from domains such as web-graph analysis, large-scale log mining, and machine learning. We show that excellent absolute performance can be attained--a general-purpose sort of 1012 Bytes of data executes in 319 seconds on a 240-computer, 960- disk cluster--as well as demonstrating near-linear scaling of execution time on representative applications as we vary the number of computers used for a job.
Factors related to publication success among faculty development fellowship graduates.

BACKGROUND AND OBJECTIVES This study's purpose was to understand factors related to scholarly project publication among fellowship graduates and to explore the role of collegial relationships and institutional characteristics on ever having published and number of publications. METHODS We surveyed 5 years of graduates (2000-2004) from the Michigan State University Faculty Development Fellowship Program (n=90) via e-mail. The survey instrument included questions about barriers and facilitators, colleague relationships, and aspects of their institutional environment, the latter adapted from a validated survey by Bland et al. RESULTS The response rate was 70%. Only seven graduates had published the results of their fellowship project; 44% had published at least one paper. Barriers to publishing scholarly project results included lack of time and assistance, inability to finish projects, and rejection of a submitted paper. Factors associated with publication included types of collegial relationships and a number of institutional factors in addition to the Bland score. CONCLUSIONS Few of our fellowship graduates published the results of their scholarly project, and less than half published papers. We identified multiple barriers and facilitators that could be addressed by the fellowship programs and home institutions to enhance publication success.
Flexible parametric models for relative survival, with application in coronary heart disease

Relative survival is frequently used in population‐based studies as a method for estimating disease‐related mortality without the need for information on cause of death. We propose an extension to relative survival of a flexible parametric model proposed by Royston and Parmar for censored survival data. The model provides smooth estimates of the relative survival and excess mortality rates by using restricted cubic splines on the log cumulative excess hazard scale. The approach has several advantages over some of the more standard relative survival models, which adopt a piecewise approach, the main being the ability to model time on a continuous scale, the survival and hazard functions are obtained analytically and it does not use split‐time data. Copyright © 2007 John Wiley & Sons, Ltd.
A preliminary study on deep learning for predicting social insurance payment behavior

Social insurance plays crucial role for protecting the social functionality. Since different occupation would lead to different level salary and different risk, the social insurance for the people is usually designed by the characteristic of their occupation. In Taiwan, Ministry of Health and Welfare provides health care to citizens and guarantees the basic income of their elderly life. Accordingly, Ministry of Health and Welfare operates and sponsor many types of social insurances such as National Pension Insurance, Labor Pension Insurance, etc. However, due to the Population ageing, many social insurances are going to encounter the crisis of pension bankruptcy. Unfortunately, the traditional actuarial methods are based on many hypotheses to calculate cash flow, which cannot predict individuals' personal payment behavior. Besides, most traditional actuarial methods only can estimate short-term cash flow. As the result, the error of traditional actuarial methods would significantly be increased while the period of prediction target is increased. In order to predicting individuals' personal payment behavior with long-term period, we propose a Deep-Learning framework to build a prediction model. Meanwhile, the Recurrent Neural Network (RNN) architecture is adopted to effectively abstract individuals' payment behavior and precisely predict their future payment behavior with a long-term period. We conduct a comprehensive experimental study based on a real dataset collected through Taiwan's Ministry of Health and Welfare. The results demonstrate a significantly improved accuracy of our Deep Learning approach compared with the existing works.
ideR, an Essential Gene in Mycobacterium tuberculosis: Role of IdeR in Iron-Dependent Gene Expression, Iron Metabolism, and Oxidative Stress Response

ABSTRACT The mycobacterial IdeR protein is a metal-dependent regulator of the DtxR (diphtheria toxin repressor) family. In the presence of iron, it binds to a specific DNA sequence in the promoter regions of the genes that it regulates, thus controlling their transcription. In this study, we provide evidence that ideR is an essential gene in Mycobacterium tuberculosis. ideR cannot normally be disrupted in this mycobacterium in the absence of a second functional copy of the gene. However, a rare ideR mutant was obtained in which the lethal effects of ideR inactivation were alleviated by a second-site suppressor mutation and which exhibited restricted iron assimilation capacity. Studies of this strain and a derivative in which IdeR expression was restored allowed us to identify phenotypic effects resulting from ideR inactivation. Using DNA microarrays, the iron-dependent transcriptional profiles of the wild-type, ideR mutant, and ideR-complemented mutant strains were analyzed, and the genes regulated by iron and IdeR were identified. These genes encode a variety of proteins, including putative transporters, proteins involved in siderophore synthesis and iron storage, members of the PE/PPE family, a membrane protein involved in virulence, transcriptional regulators, and enzymes involved in lipid metabolism.
1 The Kalman Foundations of Adaptive Least Squares, With Application to U.S. Inflation

participants at the OSU Money/Macro Seminar and the 2005 conference on Computation in Economics and Finance for helpful comments and suggestions, and especially to James Durbin for his inspirational lectures at Ohio State in 1993. is a method of estimating time-varying relationships and of proxying agents' time-evolving expectations. This paper provides theoretical foundations for ALS as a special case of the generalized Kalman solution of a Time Varying Parameter (TVP) model. The approach is in the spirit of that proposed by Ljung and Sargent, but unlike theirs, nests the rigorous Kalman solution of the elementary Local Level Model, and employs a very simple, yet rigorous, initialization. Unlike CGRLS and related approaches, ALS permits estimation of the asymptotic gain by maximum likelihood (ML). The ALS algorithm is illustrated with a univariate time series model of monthly U.S. inflation, using data for 1913-2005. The estimated asymptotic gain is 0.00779, for a limiting effective sample size of 128.4 months or 10.7 years. Volatility clustering is pronounced, and is modeled as GARCH (1,1). Because the null hypothesis that the coefficients are constant lies on the boundary of the permissible parameter space, the regularity conditions for the chi-square limiting distribution of likelihood-based test statistics are not met. Consequently, critical values of the Likelihood Ratio (LR) test statistics are established by Monte Carlo means and used to test and overwhelmingly reject the constancy of the parameters in the estimated model. Time-specific hypotheses on coefficients may be tested with a customary chi-square test, using either the ALS filter or smoother. Global hypotheses are tested with the Variance Ratio (VR) statistic, which extends the customary LR statistic. Using it, a restricted time-varying AR(6) model of inflation is rejected in favor of a restricted AR(12) specification, while AR(12) cannot be rejected in favor of AR(24). Seasonality is globally significant, although locally insignificant from 1950 – 1973.
Prediction of Success in Audiolingual and Cognitive Classes.

The audio-lingual habit theory relates more closely to a mechanistic theory of learning while the cognitive code-learning theory corresponds more nearly to a mentalistic interpretation. Although both researchers and teachers have tended toward an insistence upon one approach or the other as being the better method, the findings of this study indicated that the student ability factors which affect achievement in language learning are not the same under both methods of instruction. Furthermore, the results of the analyses suggested that, on the basis of information available to the counselor, it would be possible to assign a student to the type of class which would be most suitable to his particular capabilities.
The Future of Software Performance Engineering

Performance is a pervasive quality of software systems; everything affects it, from the software itself to all underlying layers, such as operating system, middleware, hardware, communication networks, etc. Software Performance Engineering encompasses efforts to describe and improve performance, with two distinct approaches: an early-cycle predictive model-based approach, and a late-cycle measurement-based approach. Current progress and future trends within these two approaches are described, with a tendency (and a need) for them to converge, in order to cover the entire development cycle.
Isolation of Strains Belonging to the Cosmopolitan Polynucleobacter necessarius Cluster from Freshwater Habitats Located in Three Climatic Zones

ABSTRACT More than 40 bacterial strains belonging to the cosmopolitan Polynucleobacter necessarius cluster (Betaproteobacteria) were isolated from a broad spectrum of freshwater habitats located in three climatic zones. Sequences affiliated with the freshwater P. necessarius cluster are among the most frequently detected in studies on bacterial diversity in freshwater ecosystems. Despite this frequent detection with culture-independent techniques and the cosmopolitan occurrence of members affiliated with this cluster, no isolates have been reported thus far. The isolated strains have been obtained from lakes, ponds, and rivers in central Europe, the People's Republic of China, and East Africa by use of the filtration-acclimatization method. The 16S rRNA gene sequences of the isolates are 98.8 to 100% identical to reference sequences obtained by various authors by use of culture-independent methods. The isolates, aerobic heterotrophs, grew on a wide range of standard complex media and formed visible colonies on agar plates. Thus, the previous lack of isolates cannot be explained by a lack of appropriate media. Most of the isolates possess, under a wide range of culture conditions, very small cells (<0.1 μm3), even when grown in medium containing high concentrations of organic substances. Thus, these strains are obligate ultramicrobacteria. The obtained strains have a C-shaped cell morphology which is very similar to that of recently isolated ultramicrobacterial Luna cluster strains (Actinobacteria) and the SAR11 cluster strains (Alphaproteobacteria).
Coordinating Fuel Inventory and Electric Power Generation under Uncertainty

We discuss the problem of hedging between the natural gas and electric power markets. Based on multiple forecasts for natural gas prices, natural gas demand, and electricity prices, a stochastic optimization model advises a decision maker on when to buy or sell natural gas and when to transform gas into electricity. For relatively small models, branch-andbound solves the problem to optimality. Larger models are solved using Benders decomposition and Lagrangian relaxation. We apply our approach to the system of an electric utility and succeed in solving problems with 50,000 binary variables in less than four min to within 1.16% of the optimal value.
Thrombolysis in patients with acute stroke caused by cervical artery dissection: analysis of 9 patients and review of the literature.

BACKGROUND Results of recently published studies suggest that intravenous thrombolysis (IVT) and local intra-arterial thrombolysis (LIT) are feasible procedures in acute stroke after cervical artery dissection (CAD). OBJECTIVES To describe 9 patients with acute stroke caused by CAD who were treated by LIT (n = 7) or IVT (n = 2) and to review the literature. METHODS Retrospective analysis of clinical and neuroradiological findings; literature review from 1980 to present. MAIN OUTCOME MEASURE Modified Rankin Scale (mRS) score. RESULTS Of 7 patients treated with LIT, 3 had good outcomes (mRS score of 0-2) and 4 had bad outcomes (mRS score of 3-6) at 3 months. The 2 patients who had received IVT recovered to mRS scores of 0 and 3. Twenty-one patients were identified in the literature. Overall (N = 30), in the IVT group (n = 19), the outcome was good in 8 patients (42%) and bad in 11 (58%); in the LIT group (n = 11), 6 patients (55%) had a good outcome and 5 (45%) had a bad outcome. Overall, 47% (14/30) of the patients (IVT and LIT groups) had a good outcome. Total mortality was 13% (4/30). There were no secondary complications due to extension of wall hematoma or angiography. One symptomatic hemorrhage occurred. CONCLUSIONS Thrombolysis is feasible in acute stroke caused by CAD. Local complications from extension of wall hematoma did not occur. Further prospective studies are needed to determine the safety and efficacy of thrombolysis in the special circumstance of acute stroke caused by CAD.
NUMERICAL COMPUTATION OF PARETO OPTIMAL STRATEGY FOR GENERAL MULTIPARAMETER SINGULARLY PERTURBED SYSTEMS

Abstract In this paper, Pareto optimal strategy for general multiparameter singularly perturbed systems is investigated. The main contribution is to propose a new computational method for obtaining the high-order Pareto near-optimal strategy. Newton's method and two fixed point algorithms are combined. As a result, the new iterative algorithm achieves the quadratic convergence property and succeeds in reducing the computing workspace dramatically. It is newly shown that the resulting optimal strategy achieves the cost functional J j * + O (||μ|| 2 i ).
Event Oriented Query Expansion for News Event Queries

Query expansion techniques have been commonly used by participants in Temporal Summarization tack. However, many previous attempts focused on expanding queries based on their event types, which only covers partially of the information need represented by queries. The reason is that the queries in the TS track are about news events, and for an event query, the event related entities, which are the entities mentioned in the queries, are essential when deﬁning the event. Given the query ”Vauxhall helicopter crash”, without ”Vauxhall” or ”helicopter”, the event cannot be speciﬁcally deﬁned. Therefore, we argue that both event type and event related entities should be considered when expanding a query, and a model based query expansion framework is proposed which incorporates these two types of information. The framework is then employed by using external resources, such as external corpora and Wikipedia pages to build expansion models.
A reactive agent-based problem-solving model: Application to localization and tracking

For two decades, multi-agent systems have been an attractive approach for problem solving and have been applied to a wide range of applications. Despite the lack of generic methodology, the reactive approach is interesting considering the properties it provides. This article presents a problem-solving model based on a swarm approach where agents interact using physics-inspired mechanisms. The initial problem and its constraints are represented through agents' environment, the dynamics of which is part of the problem-solving process. This model is then applied to localization and target tracking. Experiments assess our approach and compare it to widely-used classical algorithms.
Serum uric acid levels predict the development of albuminuria over 6 years in patients with type 1 diabetes: findings from the Coronary Artery Calcification in Type 1 Diabetes study.

BACKGROUND Recent studies suggest that uric acid is a mediator of diabetic nephropathy. We hypothesized that elevated serum uric acid levels are a strong predictor of albuminuria in patients with type 1 diabetes. METHODS We analyzed data from the Coronary Artery Calcification in Type 1 Diabetes study, a prospective observational study. A stepwise logistic regression model was applied to predict the development of micro- or macroalbuminuria after 6 years of follow-up in 324 participants who had no evidence of micro- or macroalbuminuria at baseline. A P-value <0.1 was used as the criteria for entry into and removal from the model. RESULTS The following factors were selected in the stepwise multivariate model as predictors of micro- or macroalbuminuria at the 6-year follow-up visit: baseline serum uric acid levels, HbA(1c) and pre-albuminuria. For every 1-mg/dl increase in serum uric acid levels at baseline, there was an 80% increased risk of developing micro- or macroalbuminuria at 6 years (odds ratio 1.8; 95% confidence interval 1.2, 2.8; P = 0.005). Additional covariates considered in the stepwise model were sex, age, duration of diabetes, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker treatment, waist circumference, waist/hip ratio, body mass index, systolic and diastolic blood pressure, smoking, serum creatinine, cystatin C, high-density lipoprotein cholesterol and triglycerides. CONCLUSION Elevated serum uric acid levels are a strong predictor of the development of albuminuria in patients with type 1 diabetes.