Miracle-dz/UniFAR-FTUs huggingface dataset:
Versatile, portable, and efficient file system profiling

File systems are complex and their behavior depends on many factors. Source code, if available, does not directly help understand the file system's behavior, as the behavior depends on actual workloads and external inputs. Runtime profiling is a key technique for understanding the behavior and mutual-influence of modern OS components. Such profiling is useful to prove new concepts, debug problems, and optimize the performance of existing file systems. Unfortunately, existing profiling methods are lacking in important areas: they do not provide much of the necessary information about the file system's behavior, they require OS modification and therefore are not portable, or they exact high overheads thus perturbing the profiled file system. We developed a direct, real-time file system profiling method based on the analysis of latency distributions. Our method is versatile: a suitable workload can be used to profile virtually any OS component. Our method is portable because we can intercept operations and measure file system behavior from the user level or from inside the kernel without requiring source code. Our method is efficient: it has small overheads (less than 4% of the CPU time). Moreover, if the source code is available, we can use it to reduce overheads even further. In this dissertation we describe our profiling method, the theory behind it, and the automation of the profile analysis. We demonstrate the usefulness of our method through a series of profiles conducted on Linux, FreeBSD, and Windows, including client/server scenarios. We discovered and investigated a number of interesting interactions, including scheduler behavior, multi-modal I/O distributions, and a previously unknown lock contention, which we fixed. We use our profiling method for performance analysis of a complex RAID-like fan-out stackable file system called RAIF that we have developed.
Resolving Surface Forms to Wikipedia Topics

Ambiguity of entity mentions and concept references is a challenge to mining text beyond surface-level keywords. We describe an effective method of disambiguating surface forms and resolving them to Wikipedia entities and concepts. Our method employs an extensive set of features mined from Wikipedia and other large data sources, and combines the features using a machine learning approach with automatically generated training data. Based on a manually labeled evaluation set containing over 1000 news articles, our resolution model has 85% precision and 87.8% recall. The performance is significantly better than three baselines based on traditional context similarities or sense commonness measurements. Our method can be applied to other languages and scales well to new entities and concepts.
Atmospheric Moisture Measurements Explain Increases in Tropical Rainfall Extremes

Anthropogenic climate change is increasing extreme rainfall as a result of an increased water‐holding capacity of the atmosphere due to higher temperatures. However, observed rainfall‐temperature scaling relationships often differ from the theorized increases in moisture‐holding capacity. This discrepancy is most evident in the tropics, where higher surface temperatures show a marked decrease in extreme rainfall intensity despite observed increases in extreme rainfall. Here we use atmospheric moisture measurements from the National Aeronautics and Space Administration's Atmospheric Infrared Sounder with surface data to investigate the tropical rainfall‐temperature scaling relationship. We show rainfall intensity scales positively with integrated water vapor in all regions. Further, integrated water vapor does not consistently scale positively with surface air temperature and its dependence on background temperature offers a physical explanation for the apparent negative scaling. We conclude that the inconsistent relationship between surface air temperature and moisture is the reason for the “apparent” negative scaling consistently found in the tropics.
A multiple-candidate-regeneration-based object tracking system with enhanced learning capability by nearest neighbor classifier

We present a real-time object tracking system that employs the nearest neighbor classifier and the multiple candidate regeneration as the appearance model and the searching strategy. Based on the analysis of the likelihood measurement, a novel appearance model has been proposed, with an online learning strategy specifically designed for tracking task. The number of templates is reduced to a small number and reliable template selection is realized. Because of its simplicity, the system can be efficiently built on hardware. The evaluation of the proposed system on challenging video sequences shows robust tracking capability with accurate tracking results. Hardware implementation of this system is also discussed and a processing speed much faster than the frame rate can be expected.
Deep Learning with Minimal Training Data: TurkuNLP Entry in the BioNLP Shared Task 2016

We present the TurkuNLP entry to the BioNLP Shared Task 2016 Bacteria Biotopes event extraction (BB3-event) subtask. We propose a deep learning-based approach to event extraction using a combination of several Long Short-Term Memory (LSTM) networks over syntactic dependency graphs. Features for the proposed neural network are generated based on the shortest path connecting the two candidate entities in the dependency graph. We further detail how this network can be efﬁciently trained to have good generalization performance even when only a very limited number of training examples are available and part-of-speech (POS) and dependency type feature representations must be learned from scratch. Our method ranked second among the entries to the shared task, achieving an F-score of 52.1% with 62.3% precision and 44.8% re-call.
Mathematical aspects in the meteorological interpretation of satellite hyperspectral infrared measurements part II: estimates of the cloud absorption vertical profile of Hurricane Ioke on 28 August 2006

ABSTRACT This study processes and analyses hyperspectral measurements from the Atmospheric Infrared Sounder on 28 August 2006 covering day and night scenes of Hurricane Ioke with a temporal spacing of 12 hours. A semi-discrete multilevel cloud model is used to describe the perturbation of the outgoing thermal radiation caused by cloudiness in the field of view (FOV) of a satellite instrument. Cloud spectral effects in the model are represented by an effective cloud absorption vertical profile (CAVP). The CAVP estimate is considered an indicator of the presence of clouds at specific atmospheric layers. The CAVP estimates are compared with lidar measurements. Results indicate a realistic characterization of cloud top and cloud vertical scale. The spatial distribution of the CAVP estimates is used to describe the spatial structure of the hurricane and to monitor its changes over time. Comparison of daytime and night-time CAVP estimates shows that the effective hurricane radius is drastically reduced from about 578 km during the day to about 463 km at night at an atmospheric layer above 212 hPa and from about 604 km to about 499 km at atmospheric layer above 300 hPa. In addition, there is indication of a significant presence of ice crystals in the upper troposphere 10–14 km at night over the large areas adjacent to the hurricane. These crystal clouds have the potential to affect the hurricane energy budget by reducing the night-time cooling rate and trapping heat and moisture in the lower atmospheric layers.
A non-conforming composite quadrilateral finite element pair for feedback stabilization of the Stokes equations

Abstract - In this contribution, we show a method for the boundary feedback stabilization of the Stokes problem around a stationary trajectory. We derive a formal low-rank algorithm for solving the stabilization problem in operator notation. The appearing operator equations are formulated in terms of stationary partial differential equations (PDEs) instead of using their finite dimensional representations in terms of matrices. A Galerkin method, satisfying the divergence constraint pointwise locally is especially appealing since it represents appropriately the action of the Helmholtz projection. The main advantages of the composite technique are the efficient assembly of element matrices, the reduction of computational costs using static condensation, and the diagonal mass matrix. The non-conforming character of the composite element guarantees a better sparsity pattern, compared to conforming elements, due to the lower number of couplings between basis functions corresponding to neighboring cells. We also achieve the pointwise mass conservation on sub-triangles of each element.
Contiki-based mitigation of UDP flooding attacks in the Internet of things

As Internet of things (IoT) continue to ensconce into our homes, offices, hospitals, electricity grids and other walks of life, the stakes are too high to leave security to chance. IoT devices are resource constrained devices and hence it is very easy to exhaust them of their resources or deny availability. One of the most prominent attacks on the availability is the Distributed Denial of service (DDoS) attack. Although, DDoS is not a new Internet attack but a large number of new, constrained and globally accessible IoT devices have escalated the attack surface beyond imagination. This paper provides a broad anatomy of IoT protocols and their inherent weaknesses that can enable attackers to launch successful DDoS attacks. One of the major contributions of this paper is the implementation and demonstration of UDP (User Datagram Protocol) flood attack in the Contiki operating system, an open-source operating system for the IoT. This attack has been implemented and demonstrated in Cooja simulator, an inherent feature of the Contiki operating system. Furthermore, in this paper, a rate limiting mechanism is proposed that must be incorporated in the Contiki OS to mitigate UDP flood attacks. This proposed scheme reduces CPU power consumption of the victim by 9% and saves the total transmission power of the victim by 55%.
Automated Metabolic Reconstruction at the Molecular Level

The analysis of metabolism in bacteria facilitates a new application area such as drug synthesis or toxin degradation, using genetically engineered bacteria. However, the understanding of bacterial metabolism is still premature, because in a newly sequenced bacterium, gene functions are determined for half its total ORFs. Only from sequence similarity, it is impossible to decide functions of the remaining ORFs. It seems speculative to estimate metabolism from only half of its component, but the good news is basic metabolism is conserved throughout species. Therefore, the basic strategy for predicting pathways is to (1) map known functions to the pathways we already have; and to (2) ll gaps by inserting a missing piece of a metabolic jigsaw puzzle. The latter step corresponds to the prediction of ORF functions, and not only sequence similarity but substrate motif becomes available in this analysis. For this purpose, we designed and implemented Automated Metabolic Reconstruction (AMR) system, which includes the database of chemical molecules, the database of enzymatic functions, and the deduction engine for computing putative pathways.
Improvement of Postprandial Endothelial Function After a Single Dose of Exenatide in Individuals With Impaired Glucose Tolerance and Recent-Onset Type 2 Diabetes

OBJECTIVE Endothelial dysfunction is frequently present in individuals with insulin resistance or type 2 diabetes and can be induced by high-fat or high-carbohydrate meals. Because exenatide reduces postprandial glucose and lipid excursions, we hypothesized that it may also improve postprandial endothelial function. RESEARCH DESIGN AND METHODS In a double-blinded randomized crossover design, postprandial endothelial function was examined in 28 individuals with impaired glucose tolerance or recent-onset type 2 diabetes after a single injection of exenatide or placebo given just before a high-fat meal. Endothelial function was determined with peripheral arterial tonometry pre- and postprandially. RESULTS Postprandial endothelial function was higher after exenatide compared with placebo (P = 0.0002). In the placebo phase, postprandial change in endothelial function was inversely associated with mean postprandial concentrations of triglycerides (r = −0.62, P = 0.0004). Changes in postprandial triglyceride concentrations explained 64% of exenatide's effect on postprandial endothelial function. CONCLUSIONS Exenatide ameliorates postprandial endothelial dysfunction after a high-fat meal.
Prospective pilot intervention study to prevent medication errors in drugs administered to children by mouth or gastric tube: a programme for nurses, physicians and parents

Background Drug administration in children is an error-prone task for nurses and parents because individual dose adjustment is often necessary, and suitable formulations for children are frequently lacking. Hence, in the absence of measures for their prevention, medication errors are likely to occur. Objective To assess the error prevalence in drug administration by mouth or gastric tube before and after implementing a programme for quality improvement for nurses and parents. Design, setting and participants Prospective, two-period cohort intervention study on a paediatric neurology ward of a university hospital where drug administration procedures of nurses and parents were consecutively monitored during the routine drug administration hours. Main outcomes measure Prevalence of administration errors before and after implementing instructions for appropriate drug administration, and a teaching and training programme supported by information pamphlets. Results Altogether, 1164 predefined administration tasks were assessed, 675 before and 489 after the intervention. Of these, 95.7% (after the intervention: 92.6%) were performed by nurses. Errors addressed by the intervention were reduced from 261/646 tasks (40.4%) to 36/453 (7.9%, p<0.001) in nurses and from 28/29 (96.6%) to 2/36 (5.6%, p<0.001) in parents. Errors in predefined categories concerning tablet dissolution, tablet storage, oral liquids, tablet splitting, administration by gastric tube and others were all considerably less frequent after the intervention (each p<0.001). Conclusion Errors of drug administration by mouth and gastric tube represent a considerable and often neglected drug-related problem in paediatric inpatients. Targeted quality-improvement programmes can substantially and rapidly reduce error prevalence. Appropriate teaching and training of both nurses and parents supported by pamphlets was a highly efficient way to reduce error prevalence.
Inserting Points Uniformly at Every Instance

Arranging n points as uniformly as possible is a frequently occurring problem. It is equivalent to packing n equal and non-overlapping circles in a unit square. In this paper we generalize this problem in such a way that points are inserted one by one with uniformity preserved at every instance. Our criterion for uniformity is to minimize the gap ratio (which is the maximum gap over the minimum gap) at every point insertion. We present a linear time algorithm for finding an optimal n-point sequence with the maximum gap ratio bounded by 2⌊n/2⌋/(⌊n/2⌋+1) in the 1-dimensional case. We describe how hard the same problem is for a point set in the plane and propose a local search heuristics for finding a good solution.
Under Consideration for Publication in J. Functional Programming Ott: Effective Tool Support for the Working Semanticist

Semantic definitions of full-scale programming languages are rarely given, despite the many potential benefits. Partly this is because the available metalanguages for expressing semantics — usually either L A T E X for informal mathematics, or the formal mathematics of a proof assistant — make it much harder than necessary to work with large definitions. We present a metalanguage specifically designed for this problem, and a tool, Ott, that sanity-checks such definitions and compiles them into proof assistant code for Coq, HOL, and Isabelle/HOL, together with L A T E X code for production-quality typesetting, and OCaml boilerplate. The main innovations are: (1) metalanguage design to make definitions concise, and easy to read and edit; (2) an expressive but intuitive metalanguage for specifying binding structures; and (3) compilation to proof assistant code. This has been tested in substantial case studies, including modular specifications of calculi from the TAPL text, a Lightweight Java with Java JSR 277/294 module system proposals, and a large fragment of OCaml (OCaml light , 310 rules), with mechanised proofs of various soundness results. Our aim with this work is to enable a phase change: making it feasible to work routinely, without heroic effort, with rigorous semantic definitions of realistic languages.
iSARST: an integrated SARST web server for rapid protein structural similarity searches

iSARST is a web server for efficient protein structural similarity searches. It is a multi-processor, batch-processing and integrated implementation of several structural comparison tools and two database searching methods: SARST for common structural homologs and CPSARST for homologs with circular permutations. iSARST allows users submitting multiple PDB/SCOP entry IDs or an archive file containing many structures. After scanning the target database using SARST/CPSARST, the ordering of hits are refined with conventional structure alignment tools such as FAST, TM-align and SAMO, which are run in a PC cluster. In this way, iSARST achieves a high running speed while preserving the high precision of refinement engines. The final outputs include tables listing co-linear or circularly permuted homologs of the query proteins and a functional summary of the best hits. Superimposed structures can be examined through an interactive and informative visualization tool. iSARST provides the first batch mode structural comparison web service for both co-linear homologs and circular permutants. It can serve as a rapid annotation system for functionally unknown or hypothetical proteins, which are increasing rapidly in this post-genomics era. The server can be accessed at http://sarst.life. nthu.edu. tw/iSARST/.
Kinetics of labeling of the S-adenosylmethionine pool of Saccharomyces cerevisiae

A method has been developed for studying the specific activity of the pool of S-adenosylmethionine in yeast. The pool reaches half-maximal specific activity within 30 s after the addition of [methyl-3H]methionine. After addition of an excess of nonradioactive methionine, the specific activity of S-adenosylmethionine is reduced by half within 20 s. During that period there is a substantial expansion of the pool. A logarithmically growing cell in synthetic medium contains about 2 X 10(6) molecules of S-adenosylmethionine, of which only 10% is used for the methylation of ribonucleic acid molecules.
Learning optimal features for music transcription

This paper aims to design time-frequency representation (TFR) functions for automatic music transcription. It is desirable that the decomposition of those TFR functions are suitable for notes having variation of both pitch and spectral envelop over time. The Harmonic Adaptive Latent Component Analysis (HALCA) model adopted in this paper allows considering those two kinds of variations simultaneously. We evaluate the influence of three TFR functions including IIR, FIR filter bank semigram (FBSG) and constant-Q transform semigram in automatic music transcription task, on a database of popular and polyphonic classic music. The experiment results show that the filter bank based representations are suitable for multiple-instrument recordings and a CQT-based representation turns out to provide very accurate transcription for solo-instrument recordings.
Employ a mobile agent for making a payment

The mobile agent paradigm offers flexibility and autonomy to e-commerce applications. But it is challenging to employ a mobile agent to make a payment due to the security consideration. In this paper, we propose a new agent-assisted secure payment protocol, which is based on SET payment protocol and aims at enabling the dispatched consumer-agent to autonomously sign contracts and make the payment on behalf of the cardholder after having found the best merchant, without the possibility of disclosing any secret to any participant. This is realized by adopting the Signature-Share scheme, and employing a Trusted Third Party (TTP). In the proposed protocol, the principle that each participant knows what is strictly necessary for his/her role is followed as in SET. In addition, mechanisms have been devised for preventing and detecting double payment, overspending and overpayment attacks. Finally the security properties of the proposed protocol are studied analytically. In comparison with other existing models, the proposed protocol is more efficient and can detect more attacks.
Membrane Amine Oxidase Cloning and Identification as a Major Protein in the Adipocyte Plasma Membrane*

A 97-kDa protein present in the glucose transporter (GLUT4 isotype)-containing vesicles from rat adipocytes has been isolated, the sequences of two tryptic peptides were obtained, and on the basis of these its cDNA partially cloned. The 97-kDa protein is almost certainly identical to a major integral glycoprotein of this size in the rat adipocyte plasma membrane, since its predicted N-terminal sequence is the same as that recently determined for this glycoprotein by amino acid sequencing. Moreover, the predicted partial sequence (322 amino acids) of the 97-kDa protein is highly homologous to the corresponding region of a human placental amine oxidase, which was cloned simultaneously and proposed to be a secreted protein. The amino acid sequence of the 97-kDa rat/human amine oxidase indicates that the protein consists of a very short N-terminal cytoplasmic domain followed by a single transmembrane segment and a large extracellular domain containing the catalytic site. Thus this study establishes the 97-kDa rat/human amine oxidase as the first integral membrane amine oxidase to be cloned. The membrane amine oxidase was more abundant in the plasma membranes than the low density microsomes of the adipocyte, and in contrast to some other proteins found in GLUT4 vesicles, it did not redistribute to the plasma membrane in response to treatment of the cells with insulin.
A Heuristic Approach for the Vertex Cover Problem

A vertex cover is a subset of the vertex set of a given graph G such that every edge in G has at least one endpoint in this set. The Minimum Vertex Cover problem consists to find the minimum sized vertex cover in a graph. This problem which belongs to the class of NP-hard graph theoretical problems, has many practical applications in various fields. In this article, we propose a novel heuristic algorithm for solving this problem. The test results obtained on some graph examples available in the literature confirm the effectiveness of the proposed method.
Robust video denoising by low-rank decomposition and modeling noises with mixture of Gaussian

This paper introduces a new approach for video denoising. Based on the idea of patch based low rank matrix completion, we improve the method by modeling noises with Mixture of Gaussians (MoG). By utilizing a series of different Gaussian distributions to fit the representation of video noises without any assumptions on the statistical properties, the parameters of MoG are learned from video data automatically. It can deal with the fact that for most of the time, the real distribution of noises appeared in videos are unknown so that traditional methods do not work well without any priori knowledge. After the model and algorithm statements, we provide a group of experiments on real videos for comparisons with the state-of-art video denoising algorithm, which demonstrates the effectiveness and advantage of our approach.