Miracle-dz/UniFAR-FTUs huggingface dataset:
Consensus Guidelines for the Management of Postoperative Nausea and Vomiting

The present guidelines are the most recent data on postoperative nausea and vomiting (PONV) and an update on the 2 previous sets of guidelines published in 2003 and 2007. These guidelines were compiled by a multidisciplinary international panel of individuals with interest and expertise in PONV under the auspices of the Society for Ambulatory Anesthesia. The panel members critically and systematically evaluated the current medical literature on PONV to provide an evidence-based reference tool for the management of adults and children who are undergoing surgery and are at increased risk for PONV. These guidelines identify patients at risk for PONV in adults and children; recommend approaches for reducing baseline risks for PONV; identify the most effective antiemetic single therapy and combination therapy regimens for PONV prophylaxis, including nonpharmacologic approaches; recommend strategies for treatment of PONV when it occurs; provide an algorithm for the management of individuals at increased risk for PONV as well as steps to ensure PONV prevention and treatment are implemented in the clinical setting.
The watermark evaluation testbed (WET): new functionalities

While Digital Watermarking has received much attention within the academic community and private sector in recent years, it is still a relatively young technology. As such, there are few accepted tools and metrics that can be used to validate the performance claims asserted by members of the research community and evaluate the suitability of a watermarking technique for specific applications. This lack of a universally adopted set of metrics and methods has motivated us to develop a web-based digital watermark evaluation system known as the Watermark Evaluation Testbed or WET. This system has undergone several improvements since its inception. The ultimate goal of this work has been to develop a platform, where any watermarking researcher can test not only the performance of known techniques, but also their own techniques. This goal has been reached by the latest version of the system. New tools and concepts have been designed to achieve the desired objectives. This paper describes the new features of WET. Moreover, we also summarize the development process of the entire project as well as introduce new directions for future work.
A Simulation Study on the Form of Fish Schooling for Escape from Predator

In this paper, on a simulation model of fish schooling considering predator’s existence, we attempt an analysis of the form of school in which prey fish evades predator. We consider an evolutionary model of the fish behavior, and discuss the mechanism of schooling behavior when the school encounters with a predator. This paper then shows our computer simulation of the prey-predator system on an artificial ecology where fishes and a predator coexist, and reports well simulated prey behaviors, especially evading behaviors of the predator with advantage of schooling. On the simulation, we give an informal analysis of the transition of the form of fish school in which fishes have the evading behaviors.
Mining Local Data Sources For Learning Global Cluster Models

Distributed data mining has been a topic getting more important nowadays as there are many cases where physically sharing of data is probibited, e.g., due to huge data volume or data privacy. In this paper, we are interested in learning a global cluster model by exploring data in distributed sources. A methodology based on periodic model exchange and merge is proposed and applied to hyperlinked Web pages analysis. In addition, we have tested a number of variations of the basic idea, including putting more emphasis on the privacy concern and testing the effect of having different numbers of distributed sources. Experimental results show that the proposed distributed learning scheme is effective with accuracy close to the case with all the data physically shared for the learning.
Vertical Measurements for Planning Palatal Mini-Implants in Lateral Radiography and Cone Beam Computed Tomography

Objective: To compare palatal bone height measurements in the region of first premolars for planning palatal mini-implant insertion on conventional lateral radiography (CLR), cone beam computed tomography (CBCT), and reformatted virtual lateral radiography (VLR). Materials and Methods: One hundred ten images of CLR, VLR, and CBCT from the same patient were used. Linear measurements corresponding to the relevant dimension of available bone on upper first premolar site were performed between the hard palate floor and the nasal floor. The Friedman test compared the measurements of all imaging modalities. Intraobserver and interobserver agreement was calculated with the intraclass correlation coefficient (ICC). Results: The ICC values showed excellent intraobserver and interobserver agreement. VLR examination resulted in measurements statistically different from both CBCT and CLR images (P < 0.05), being underestimated when compared with these techniques, and the values found on CLR did not show statistically significant differences from the CBCT images (P > 0.05). Conclusions: The measurements for planning palatal mini-implants at the level of first premolars are comparable on CLR and multiplanar reconstructions of CBCT, whereas underestimated in reformatted examinations (VLR).
Static Detection of Unsafe Component Loadings on Windows and Linux: A Survey

Dynamic loading is an essential mechanism for computer software development. It enables an program, the versatility to use its exported functionalities and energetically link a part. Dynamic loading is really a system by which a pc program are able to at run-time, fill a collection into memory, recall the handles of parameters and functions included in the library, run those functions or get those variables, and sell the library from recollection. This function presents a signal coverage approach called motionless binary analysis to assess and discover mistakes and weaknesses about the element. Thus the dangerous and exposed parts may be recognized previous to loading energetically into applications. This paper presents the first static binary analysis aiming at detecting all possible loading-related errors. The key challenge is how to scalably and precisely compute what components may be loaded at relevant program locations. Our main insight is that this information is often determined locally from the component loading call sites. In particular, for a given call site, we first compute its contextsensitive executable slices, one for each Execution context. Then we emulate the slices to obtain the set of components possibly loaded at call site. For evaluation, we implemented our technique to detect vulnerable and unsafe component loadings in popular software on Microsoft Windows and Linux.
Fabrication of high-performance, low-temperature solution processed amorphous indium oxide thin-film transistors using a volatile nitrate precursor

In this study, we fabricate amorphous indium oxide thin film transistors (TFTs) on a display glass substrate at various annealing temperatures from 200 °C to 300 °C. Using a volatile nitrate precursor, we were able to fabricate TFTs with excellent device performance within this annealing temperature range. Amorphous In2O3 films could be obtained by carefully controlling the film thickness and annealing temperature. TFTs based on amorphous In2O3 channel layers with an average mobility as high as 7.5 cm2 V−1 s−1, an Ion/Ioff ratio of 107, and Von = −5 V could be fabricated at 300 °C annealing temperature in air. The devices prepared at 200 °C still exhibit transistor characteristics with an average mobility of 0.04 cm2 V−1 s−1, an Ion/Ioff ratio of 105, and Von = 0 V. The temperature effects on the device performances are elucidated based on X-ray photoelectron spectroscopy and thermal gravimetric analysis characterization results of precursors and the resulting amorphous In2O3 thin films.
Target oriented tweets monitoring system during natural disasters

Twitter, Social Networking Site, becomes most popular microblogging service and people have started publishing data on the use of it in natural disasters. Twitter has also created the opportunities for first responders to know the critical information and work effective reactions for impacted communities. This paper introduces the tweet monitoring system to identify the messages that people updated during natural disasters into a set of information categories and provide user desired target information type automatically. In this system, classification is done at tweet level with three labels by using LibLinear classifier. This system intended to extract the small number of informational and actionable tweets from large amounts of raw tweets on Twitter using machine learning and natural language processing (NLP). Feature extraction of this work exploited only linguistic features, sentiment lexicon based features and especially disaster lexicon based features. The annotation system also creates disaster related corpus with new tweets collected from Twitter API and annotation is done on real time manner. The performance of this system is evaluated based on four publicly available annotated datasets. The experiments showed the classification accuracy on the proposed features set is higher than the classifier based on neural word embeddings and standard bag-of-words models. This system automatically annotated the Myanmar_Earthquake_2016 dataset at 75% accuracy on average.
Filtering Entity Centric Documents using Numerics and Temporals features within RF Classifier

This article introduces the system designed to work for the Knowledge Base Acceleration (KBA) track at Text REtrieval Conference (TREC). This is the second time this track is run with yet this year there is even more challenge. KBA is focused on keeping up to date knowledge bases (KB) such as Wikipedia1 (WP) where each KB node is considered as an entity (WP page for wikipedia example). It has been shown in (Frank et al., 2012) that the time lag between the publication date of cited news articles and the date of an edit to wikipedia article creating the citation can be really big (median 356 days) for non-popular entities. KBA is to give a chance to non-popular entities information to be updated as soon as a useful information is published on the internet. The KBA organizers have built up a stream-corpus which is a huge corpus of timestamped web documents that can be processed chronologically. Hence it is possible to simulate a real time system. The documents come from newswires, blogs, forums, review, memetracker. In addition, a set of target entities, coming from wikipedia or from twitter, has been selected for their ambiguity or unpopularity. And last but not least, more than 60,000 documents have been annotated so that systems can train on it. The train period starts on documents published from october 2011 until february 2012, and the test period starts from february 2012 to february 2013. The KBA track is divided in two tasks: CCR (Cumulative Citation Recommendation) and SSF (Streaming Slot Filling). CCR task is to filter out documents worth citing in a profile of an entity (e.g., wikipedia or freebase article). SSF task is to detect changes on given slots for each of the target entities. This article is focused only on CCR task. In CCR task, the system is to filter out documents relative to target entities out from the stream-corpus. The system must also be able to give the usefulness
Biomedical Relationship Networks Zhongmin Shi and Fred Popowich School of Computing Science

The rapidly growing volume of biological and medical scientific articles calls for automatic language processing and information extraction techniques to help people access useful information efficiently, specifically when it comes to finding relationships or interactions between molecular substances. In this paper we propose a framework of Biomedical Relationship Networks (BRNs), which aims to represent explicit and implicit biomedical relationships as well as other hidden information across the whole corpus. The knowledge contained in BRNs can be directly applied to information extraction and information retrieval tasks on the corpora of medical documents.
Vectorwise: A Vectorized Analytical DBMS

Vector wise is a new entrant in the analytical database marketplace whose technology comes straight from innovations in the database research community in the past years. The product has since made waves due to its excellent performance in analytical customer workloads as well as benchmarks. We describe the history of Vectorwise, as well as its basic architecture and the experiences in turning a technology developed in an academic context into a commercial-grade product. Finally, we turn our attention to recent performance results, most notably on the TPC-H benchmark at various sizes.
Review of Development and Construction of Uyghur Knowledge Graph

Knowledge graph technology belongs to the field of artificial intelligence. It is widely used in semantic search and intelligent question answering. Construction of Uyghur's knowledge graph has the great value of Uyghur information processing and Uyghur application software development. Firstly, this paper describes the definition and structure of the knowledge graph, then it reviews the related research and construction process of the Uyghur's knowledge graph, and analyses the characteristics of word formation of Uighur entities in depth, focuses on the related concepts and methods of knowledge extraction, knowledge fusion, and knowledge update, Introduced the Uyghur semantic disambiguation technology in detail, Finally, looking forward to the future works.
Geostrophic Eddies, Abyssal Recirculations, and Zonal Jets

Abstract : A characteristic property of geostrophic turbulence is that energy undergoes an inverse cascade to large spatial scales, whereas potential enstrophy cascades directly to small spatial scales. In the presence of weak dissipation, such as in the ocean, energy is therefore quasi-conserved whereas potential enstrophy is always dissipated. As a consequence geostrophic eddies only partially mix potential vorticity along isopycnals, with the amount of mixing being dependent on the energy available in the initial state. To illustrate these ideas, two oceanographic applications are considered: the generation of abyssal recirculations around topographic features and the formation of inertial zonal jets. A new eddy parameterization is developed that dissipates potential enstrophy subject to the constraint of conserving energy. Results obtained using the parameterization are compared with those from an eddy-resolving calculation. Possible extensions of these ideas are discussed, including the possibility of incorporating additional constraints such as conservation of angular momentum.
Magic Quadrant for Enterprise Governance , Risk and Compliance Platforms

Governance, risk and compliance (GRC) as a marketplace can be broadly divided between GRC management (GRCM) products for the oversight and operation of risk management and compliance programs, and other GRC products for the automation and monitoring of controls. For a comprehensive description of the GRC marketplace, see "A Comparison Model for the GRC Marketplace, 2011 to 2013," which addresses the enterprise GRC (EGRC) platform and its relationship to other GRCM markets, such as IT GRCM (see "MarketScope for IT Governance, Risk and Compliance Management"), operational risk management (ORM; see "A Banker's Guide to Credit, Market and Operational Risk Management Software Functionality") and financial governance (see "Q&A: Current Issues in Financial Governance").
Face Recognition Based on Features Measurement Technique

We present a new technique to infer dimensions that can be used in biometric face recognition. The methodology is centered on inferring unique dimensions from human ears which provides unique physical biometric features. The process of determining the distance is done by harvesting the real actual dimensions from 2D faces images. This is achieved by using specific point to point distances on the two ears in human face. The points chosen give dimension information which enables discrimination for face recognition. The empirical results confirm that an accuracy of 94% recognition rate is achievable. The different positions of measurement points on the ears have a powerful impact to reduce the error of face recognition. Hence, our new measurement dimensions technique is precise and nodal facial points can be reflected as a robust face recognition method.
Fast exact and approximate geodesics on meshes

The computation of geodesic paths and distances on triangle meshes is a common operation in many computer graphics applications. We present several practical algorithms for computing such geodesics from a source point to one or all other points efficiently. First, we describe an implementation of the exact "single source, all destination" algorithm presented by Mitchell, Mount, and Papadimitriou (MMP). We show that the algorithm runs much faster in practice than suggested by worst case analysis. Next, we extend the algorithm with a merging operation to obtain computationally efficient and accurate approximations with bounded error. Finally, to compute the shortest path between two given points, we use a lower-bound property of our approximate geodesic algorithm to efficiently prune the frontier of the MMP algorithm. thereby obtaining an exact solution even more quickly.
Direct Spectroscopy in Hollow Optical with Fiber-Based Optical Frequency Combs

Abstract : Toward the creation of robust, portable frequency references in the near IR, we have isolated a single tooth from a fiber laser-based optical frequency comb for nonlinear spectroscopy and thereby directly referenced the comb. An 89 MHz erbium fiber laser frequency comb is directly stabilized to the P(23) (1539.43 nm) overtone transition of 12C2H2 inside a hollow-core photonic crystal fiber. To do this, a single comb tooth is isolated and amplified from 20 nW to 40 mW with sufficient fidelity to perform saturated absorption spectroscopy. The fractional stability of the comb, 7 nm away from the stabilized tooth, is shown to be 610-12 at 100 ms gate time, which is over an order of magnitude better than that of a comb referenced to a GPS-disciplined Rb oscillator.
Applying Reliability Metrics to Co-Reference Annotation

Studies of the contextual and linguistic factors that constrain discourse phenomena such as reference are coming to depend increasingly on annotated language corpora. In preparing the corpora, it is important to evaluate the reliability of the annotation, but methods for doing so have not been readily available. In this report, I present a method for computing reliability of coreference annotation. First I review a method for applying the information retrieval metrics of recall and precision to coreference annotation proposed by Marc Vilain and his collaborators. I show how this method makes it possible to construct contingency tables for computing Cohen's Kappa, a familiar reliability metric. By comparing recall and precision to reliability on the same data sets, I also show that recall and precision can be misleadingly high. Because Kappa factors out chance agreement among coders, it is a preferable measure for developing annotated corpora where no pre-existing target annotation exists.
Discovery of point sources in the Helmholtz equation posed in unknown domains with obstacles

We consider an inverse source problem for the Helmholtz equation in domains with possibly unknown obstacles, which are much larger than the wavelength. The inverse problem is to determine the number and locations of point sources in the domain based on sparse measurements of the wave ﬁeld. Our proposed strategy relies on solving a local inverse scattering problem to obtain the incoming directions of waves passing through an observation location. We formulate the problem as an L 1 constrained minimization problem and solve it using the Bregman iterative procedure. The wave direction rays are then traced back and sources are uniquely determined at the intersection of the rays from several observing locations. We present examples in 2D, however all of the formulas and methods used have direct analogues in 3D.
Formulation of visual secret sharing schemes encrypting multiple images

Secret sharing is a method of generating multiple shares from secret information so that only a qualified set of shares can be employed to recover this secret information. Visual secret sharing (VSS) is an example of secret sharing; its decryption can be performed by using human eyes without a computer. This paper provides a formulation of encryption for multiple secret images, which is a generalization of the existing ones, and also a general method of constructing VSS schemes encrypting multiple secret images.
Stress fibers are generated by two distinct actin assembly mechanisms in motile cells

Stress fibers play a central role in adhesion, motility, and morphogenesis of eukaryotic cells, but the mechanism of how these and other contractile actomyosin structures are generated is not known. By analyzing stress fiber assembly pathways using live cell microscopy, we revealed that these structures are generated by two distinct mechanisms. Dorsal stress fibers, which are connected to the substrate via a focal adhesion at one end, are assembled through formin (mDia1/DRF1)–driven actin polymerization at focal adhesions. In contrast, transverse arcs, which are not directly anchored to substrate, are generated by endwise annealing of myosin bundles and Arp2/3-nucleated actin bundles at the lamella. Remarkably, dorsal stress fibers and transverse arcs can be converted to ventral stress fibers anchored to focal adhesions at both ends. Fluorescence recovery after photobleaching analysis revealed that actin filament cross-linking in stress fibers is highly dynamic, suggesting that the rapid association–dissociation kinetics of cross-linkers may be essential for the formation and contractility of stress fibers. Based on these data, we propose a general model for assembly and maintenance of contractile actin structures in cells.
Description of an Instructional Ontology and its Application in Web Services for Education

From an educational point of view, the potential of the Web is far from being reached. Although it offers an abundance of learning resources the search for educational resources is still tedious, and interoperability of e-learning systems only a wished-for goal. What is missing is a common ground for both human and machines. While there exist standards for describing learning resources, they fail to address the instructional purpose of a resource, for instance whether a web page provides a definition or a counter-example of a concept. However, such an explicit representation of the instructional function provides humans with a shared vocabulary and can serve as the basis for the semantic interoperability for machines. This article describes such a basis: an ontology of instructional objects (OIO) that captures the function of a learning resource. The article starts with describing several educational Web services that can benefit from it. Then, the ontology is described in detail.