Miracle-dz/UniFAR-FTUs huggingface dataset:
The discovery of very red counterparts to faint X-ray sources

We present deep K-band imaging at the positions of four very faint X-ray sources found in the UK ROSAT Deep Survey to have no optical counterpart brighter than R~23. Likely identifications are found within the ROSAT error circle in all four fields with R-K colours of between 3.2 +/- 0.4 and 6.4 +/- 0.6. From a consideration of the R-K colours and X-ray to optical luminosity ratios of the candidate identifications, we tentatively classify two of the X-ray sources as very distant (z ~ 1) clusters of galaxies, one as a narrow emission line galaxy and one as an obscured QSO.
Comparison of efficacy and safety of Levosulpiride and Domperidone in functional dyspepsia

Copyright  2015 irjpbs Objective: To compare the efficacy and safety of levosulpiride with dompenidone in patients with functional dyspepsia Material & Method: It was a prospective, double blind, randomized study conducted on 182 patients in two groups of 91 each. Group A: levosulpiride 25mg TID daily orally for 4 weeks, Group B: Domperidone 10mg TID daily orally for 4 weeks. Individual symptoms (Abdominal pain, discomfort, nausea, vomiting, anorexia, post prandial bloating, belching, regurgitation, heart burn & abdominal fullness) and severity of symptoms were assessed by predetermined grading system at baseline (0), 2, 4 & 8 weeks i.e. 1st, 2nd, 3rd, & 4th visit respectively. Results: Among 182 patients 171 completed the study most of the cases were in 20 to 40 years (69%) with male preponderance (71.35%). Highly significant (p>0.001)improvement in symptoms like post prandial bloating (82%) and abdominal pain (81.63%) were noticed with levosulpiride as compared to domperidone [post prandial bloating (57%), abdominal pain (45%)]. Both the treatment groups were comparable for other symptoms. Conclusion: levosupiride is more effective but less safe than domperidone in FD.
Declarative Information Extraction Using Datalog with Embedded Extraction Predicates

In this paper we argue that developing information extraction (IE) programs using Datalog with embedded procedural extraction predicates is a good way to proceed. First, compared to current ad-hoc composition using, e.g., Perl or C++, Datalog provides a cleaner and more powerful way to compose small extraction modules into larger programs. Thus, writing IE programs this way retains and enhances the important advantages of current approaches: programs are easy to understand, debug, and modify. Second, once we write IE programs in this framework, we can apply query optimization techniques to them. This gives programs that, when run over a variety of data sets, are more efficient than any monolithic program because they are optimized based on the statistics of the data on which they are invoked. We show how optimizing such programs raises challenges specific to text data that cannot be accommodated in the current relational optimization framework, then provide initial solutions. Extensive experiments over real-world data demonstrate that optimization is indeed vital for IE programs and that we can effectively optimize IE programs written in this proposed framework.
Research Paper: Identifying Adverse Drug Events: Development of a Computer-based Monitor and Comparison with Chart Review and Stimulated Voluntary Report

BACKGROUND Adverse drug events (ADEs) are both common and costly. Most hospitals identify ADEs using spontaneous reporting, but this approach lacks sensitivity; chart review identifies more events but is expensive. Computer-based approaches to ADE identification appear promising, but they have not been directly compared with chart review and they are not widely used. OBJECTIVES To develop a computer-based ADE monitor, and to compare the rate and type of ADEs found with the monitor with those discovered by chart review and by stimulated voluntary report. DESIGN Prospective cohort study in one tertiary-care hospital. PARTICIPANTS All patients admitted to nine medical and surgical units in a tertiary-care hospital over an eight-month period. MAIN OUTCOME MEASURE Adverse drug events identified by the computer-based monitor, by chart review, and by stimulated voluntary report. METHODS A computer-based monitoring program identified alerts, which were situations suggesting that an ADE might be present (e.g., an order for an antidote such as naloxone). A trained reviewer then examined patients' hospital records to determine whether an ADE had occurred. The results of the computer-based monitoring strategy were compared with two other ADE detection strategies: intensive chart review and stimulated voluntary report by nurses and pharmacists. The monitor and the chart review strategies were independent, and the reviewers were blinded. RESULTS The computer monitoring strategy identified 2,620 alerts, of which 275 were determined to be ADEs. The chart review found 398 ADEs, whereas voluntary report detected 23. Of the 617 ADEs detected by at least one method, 76 ADEs were detected by both computer monitor and chart review. The computer monitor identified 45 percent; chart review, 65 percent; and voluntary report, 4 percent. The ADEs identified by computer monitor were more likely to be classified as "severe" than were those identified by chart review (51 versus 42 percent, p = .04). The positive predictive value of computer-generated alerts was 16 percent during the first eight weeks of the study; rule modifications increased this to 23 percent in the final eight weeks. The computer strategy required 11 person-hours per week to execute, whereas chart review required 55 person-hours per week and voluntary report strategy required 5. CONCLUSIONS The computer-based monitor identified fewer ADEs than did chart review but many more ADEs than did stimulated voluntary report. The overlap among the ADEs identified using different methods was small, suggesting that the incidence of ADEs may be higher than previously reported and that different detection methods capture different events. The computer-based monitoring system represents an efficient approach for measuring ADE frequency and gauging the effectiveness of ADE prevention programs.
Dependent types and program equivalence

The definition of type equivalence is one of the most important design issues for any typed language. In dependently typed languages, because terms appear in types, this definition must rely on a definition of term equivalence. In that case, decidability of type checking requires decidability for the term equivalence relation. Almost all dependently-typed languages require this relation to be decidable. Some, such as Coq, Epigram or Agda, do so by employing analyses to force all programs to terminate. Conversely, others, such as DML, ATS, Ωmega, or Haskell, allow nonterminating computation, but do not allow those terms to appear in types. Instead, they identify a terminating index language and use singleton types to connect indices to computation. In both cases, decidable type checking comes at a cost, in terms of complexity and expressiveness. Conversely, the benefits to be gained by decidable type checking are modest. Termination analyses allow dependently typed programs to verify total correctness properties. However, decidable type checking is not a prerequisite for type safety. Furthermore, decidability does not imply tractability. A decidable approximation of program equivalence may not be useful in practice. Therefore, we take a different approach: instead of a fixed notion for term equivalence, we parameterize our type system with an abstract relation that is not necessarily decidable. We then design a novel set of typing rules that require only weak properties of this abstract relation in the proof of the preservation and progress lemmas. This design provides flexibility: we compare valid instantiations of term equivalence which range from beta-equivalence, to contextual equivalence, to some exotic equivalences.
The impact of the diversity on multiple classifier system performance: Identifying changes in the amount of fuel in the fleet management system

When it comes to the use of any recognition systems in the real world environment, it turns out that the reality differs from the theory. There is an assumption that the distribution of the incoming data will be at least similar to the distribution of the data, which were used during the learning process and that learning dataset represents the entire space of the problem. In fact, the incoming data differ from the training set and usually cover only a part of the feature space. Very often we have to deal with imbalanced datasets which leads to underfitting of classifiers in the final ensemble. In this paper we present the Multiple Classifier System based on Random Reference Classifier in the problem of fuel level change detection in the fleet management systems. The ensemble selection process uses probabilistic measures of competence and diversity at the same time. We compare different methods to determine the diversity within the ensemble.
Clinical manifestations of Fabry disease in children: Data from the Fabry Outcome Survey

Background: Fabry disease is a rare X‐linked disorder caused by deficient activity of the enzyme α‐galactosidase A. This produces progressive lysosomal accumulation of globotriaosylceramide throughout the body, leading to organ failure and premature death. Aim: Here, we present the clinical manifestations of Fabry disease in children enrolled in FOS—the Fabry Outcome Survey—a European database of the natural history of Fabry disease and the effects of enzyme replacement therapy with agalsidase alfa (Replagal™). Methods: Currently, there are 545 patients in FOS, from 11 European countries. We analysed the baseline demographic and clinical characteristics of 82 of these patients (40 boys, 42 girls) who were below 18 y of age. The median age at evaluation (defined as the median age at entry into FOS) was 12.5 and 13.2 y for boys and girls, respectively. Results: The most frequent early clinical manifestations of Fabry disease were neurological (acroparaesthesiae, altered temperature sensitivity) and gastrointestinal symptoms (altered bowel habits and abdominal pain), which were documented in about 80% and 60% of patients, respectively, at the time of evaluation and subsequent entry into FOS. Tinnitus, vertigo, fatigue and angiokeratoma were present in over 40% of patients. Symptoms were noted in early childhood and occurred with similar frequency in boys and girls, although the onset of symptoms was 2–5 y later in girls than in boys. There was an approximately 3‐y delay from onset of symptoms to diagnosis, and patients were frequently misdiagnosed.
Trajectories of dynamic predictors of disorder: Their meanings and implications

Developmental psychopathologists are increasingly focused on characterizing heterogeneity of trajectories of psychological disorders across the life course (e.g., developmentally limited vs. chronic forms of disorder). Although the developmental significance of trajectories has been highlighted, there has been little attention to relations between trajectories and their etiologically and clinically relevant time-varying covariates (dynamic predictors). Depending upon the functional relation between a disorder and a dynamic predictor, we expect to see different trajectories of dynamic predictors. Thus, we propose a taxonomy of trajectories of dynamic predictors of course of disorder and provide an initial investigation into its validity. Using a mixed-gender, high-risk sample of young adults followed over 7 years, we identified dynamic predictors that covary with the course of alcohol use disorder (AUD). Based on a logically derived classification to facilitate interpretation of findings, three comparison groups were examined: persons whose AUD “remitted” (n = 33), those with a chronic AUD (n = 29), and nondiagnosers (n = 274). We hypothesized seven patterns of dynamic prediction (stable vulnerability indicators, course trackers, deterioration markers, developmentally specific variables, developmental lag markers, course-referenced variables, and recovery behaviors) and found evidence for five of them. The interpretation of markers of risk for development and course of AUDs and their implications for prevention, early intervention and formal/self-change treatments are discussed.Preparation of this article was supported by NIH Grants R37AA07231 and R01AA013987 to Kenneth J. Sher and P50 AA11998 to Andrew Heath from the National Institute on Alcohol Abuse and Alcoholism. Portions of this research were presented at the annual meeting of the Research Society on Alcoholism, Denver, CO, June 2000; the biennial meeting for the Society for Research on Adolescence, April 2000; and the Michigan Symposium on Developmental Discontinuities, June 2002. We gratefully acknowledge Laurie Chassin, Patrick Curran, Andrea Hussong, Kristina M. Jackson, Jenny Larkins, Terrie Moffitt, and Susan O'Neill for providing numerous, helpful comments on an earlier version of this article.
Inland Water Transport Decision Support System for Sustainable Development Based on Data Warehouse and On-Line Analytical Processing

Considering the lack of effective evaluation on the sustainable development of inland water transport, an indicator system is designed for evaluation, illustration and checking of inland water transport sustainable development and an inland water transport decision support system for sustainable development is constructed based on data warehouse and online analytical processing (OLAP). The system structure includes 5 layers: application interface layer, auxiliary decision making function layer, warehouse management and data interface layer, information warehouse layer and data layer. The system function includes monitoring, evaluation, early warning, comprehensive analysis and search. The data warehouse is designed including determining subject, dimension design, logic model design, the choice of granularity and data partition. The subject of the data warehouse consists of the early warning indices of inland water transport sustainable development. The snow model for data warehouse consists of 4 dimensions(geological area, organization, indicator and time) and 3 granularities(annual, quarterly and monthly). The partitioning scheme for the data warehouse is to do partitioning on the geological area dimension first followed by partitioning on the organization dimension. The multidimensional decision making procedure, including slicing, dicing and rotation, is discussed. The system utilizes the data from multiple sources and provides a support for multi-objective decision making to realize the dynamic analysis, monitoring and early warning in inland water transport sustainable development. Keywords-data warehouse; decision support system; inland water transport; on-line analytical processing; sustainable development; early warning
Identification of Novel Methylation Markers in Hepatocellular Carcinoma using a Methylation Array

Promoter CpG island hypermethylation has become recognized as an important mechanism for inactivating tumor suppressor genes or tumor‐related genes in human cancers of various tissues. Gene inactivation in association with promoter CpG island hypermethylation has been reported to be four times more frequent than genetic changes in human colorectal cancers. Hepatocellular carcinoma is also one of the human cancer types in which aberrant promoter CpG island hypermethylation is frequently found. However, the number of genes identified to date as hypermethylated for hepatocellular carcinoma (HCC) is fewer than that for colorectal cancer or gastric cancer, which can be attributed to fewer attempts to perform genome‐wide methylation profiling for HCC. In the present study, we used bead‐array technology and coupled methylation‐specific PCR to identify new genes showing cancer‐specific methylation in HCC. Twenty‐four new genes have been identified as hypermethylated at their promoter CpG island loci in a cancer‐specific manner. Of these, TNFRSF10C, HOXA9, NPY, and IRF5 were frequently hypermethylated in hepatocellular carcinoma tissue samples and their methylation was found to be closely associated with inactivation of gene expression. Further study will be required to elucidate the clinicopathological implications of these newly found DNA methylation markers in hepatocellular carcinoma.
Variability code analysis using the VITAL tool

As a product line evolves over time, variability realizations become overly complex and difficult to understand. This causes practical challenges in product line maintenance. To solve this issue, the VITAL tool is developed to automatically extract a variability reflexion model from variability code and conduct further analyses. In this paper, variability code analysis process using the VITAL tool is introduced, and each step of the analysis is demonstrated with an example product line.
Schwinger–Dyson operator of Yang–Mills matrix models with ghosts and derivations of the graded shuffle algebra

We consider large-N multi-matrix models whose action closely mimics that of Yang–Mills theory, including gauge-fixing and ghost terms. We show that the factorized Schwinger–Dyson loop equations, expressed in terms of the generating series of gluon and ghost correlations G(ξ), are quadratic equations in concatenation of correlations. The Schwinger–Dyson operator is built from the left annihilation operator, which does not satisfy the Leibnitz rule with respect to concatenation. So the loop equations are not differential equations. We show that left annihilation is a derivation of the graded shuffle product of gluon and ghost correlations. The shuffle product is the point-wise product of Wilson loops, expressed in terms of correlations. So in the limit where concatenation is approximated by shuffle products, the loop equations become differential equations. Remarkably, the Schwinger–Dyson operator as a whole is also a derivation of the graded shuffle product. This allows us to turn the loop equations into linear equations for the shuffle reciprocal, which might serve as a starting point for an approximation scheme.
A Phase Response Curve to Single Bright Light Pulses in Human Subjects

The circadian pacemaker is differentially sensitive to the resetting effects of retinal light exposure, depending upon the circadian phase at which the light exposure occurs. Previously reported human phase response curves (PRCs) to single bright light exposures have employed small sample sizes, and were often based on relatively imprecise estimates of circadian phase and phase resetting. In the present study, 21 healthy, entrained subjects underwent pre‐ and post‐stimulus constant routines (CRs) in dim light (∼2–7 lx) with maintained wakefulness in a semi‐recumbent posture. The 6.7 h bright light exposure stimulus consisted of alternating 6 min fixed gaze (∼10 000 lx) and free gaze (∼5000–9000 lx) exposures. Light exposures were scheduled across the circadian cycle in different subjects so as to derive a PRC. Plasma melatonin was used to determine the phase of the onset, offset, and midpoint of the melatonin profiles during the CRs. Phase shifts were calculated as the difference in phase between the pre‐ and post‐stimulus CRs. The resultant PRC of the midpoint of the melatonin rhythm revealed a characteristic type 1 PRC with a significant peak‐to‐trough amplitude of 5.02 h. Phase delays occurred when the light stimulus was centred prior to the critical phase at the core body temperature minimum, phase advances occurred when the light stimulus was centred after the critical phase, and no phase shift occurred at the critical phase. During the subjective day, no prolonged ‘dead zone’ of photic insensitivity was apparent. Phase shifts derived using the melatonin onsets showed larger magnitudes than those derived from the melatonin offsets. These data provide a comprehensive characterization of the human PRC under highly controlled laboratory conditions.
Gamification of Software Modelling Learning

Software modelling has a fundamental role in software engineering. However, it is perceived as relatively challenging for learners to develop the necessary abstraction skills to master the subject. On the other side, gamification is now flourishing as a popular strategy to engage learners. This research attempts to exploit gameful design as an innovative approach, used to create games that reinforce learners’ mastery of software modelling by developing their abstraction skills. Our approach to gameful design brings together gamification development concepts such as the Lens of Intrinsic Skill Atoms, and pedagogical design principles from several learning theories and models. The research follows the Design Science Research Methodology and exploits ModelDriven Engineering best practices. The target outputs of this research are a modelling game design and generation framework, and a number of games produced using it. The effectiveness of the framework and its games will be evaluated using controlled experiments.
Direct Heuristic Dynamic Programming for Nonlinear Tracking Control With Filtered Tracking Error

This paper makes use of the direct heuristic dynamic programming design in a nonlinear tracking control setting with filtered tracking error. A Lyapunov stability approach is used for the stability analysis of the tracking system. It is shown that the closed-loop tracking error and the approximating neural network weight estimates retain the property of uniformly ultimate boundedness under the presence of neural network approximation error and bounded unknown disturbances under certain conditions.
Deep-Sea Benthic Footprint of the Deepwater Horizon Blowout

The Deepwater Horizon (DWH) accident in the northern Gulf of Mexico occurred on April 20, 2010 at a water depth of 1525 meters, and a deep-sea plume was detected within one month. Oil contacted and persisted in parts of the bottom of the deep-sea in the Gulf of Mexico. As part of the response to the accident, monitoring cruises were deployed in fall 2010 to measure potential impacts on the two main soft-bottom benthic invertebrate groups: macrofauna and meiofauna. Sediment was collected using a multicorer so that samples for chemical, physical and biological analyses could be taken simultaneously and analyzed using multivariate methods. The footprint of the oil spill was identified by creating a new variable with principal components analysis where the first factor was indicative of the oil spill impacts and this new variable mapped in a geographic information system to identify the area of the oil spill footprint. The most severe relative reduction of faunal abundance and diversity extended to 3 km from the wellhead in all directions covering an area about 24 km2. Moderate impacts were observed up to 17 km towards the southwest and 8.5 km towards the northeast of the wellhead, covering an area 148 km2. Benthic effects were correlated to total petroleum hydrocarbon, polycyclic aromatic hydrocarbons and barium concentrations, and distance to the wellhead; but not distance to hydrocarbon seeps. Thus, benthic effects are more likely due to the oil spill, and not natural hydrocarbon seepage. Recovery rates in the deep sea are likely to be slow, on the order of decades or longer.