Miracle-dz/UniFAR-FTUs huggingface dataset:
Intravenous omeprazole in critically ill patients: A randomized, crossover study comparing 40 with 80 mg plus 8 mg/hour on intragastric pH

ObjectiveTo compare intravenous omeprazole 40-mg single dose with 8 mg/hr after an 80-mg bolus injection on 24-hr intragastric pH in intensive care unit (ICU) ventilated patients. DesignProspective, randomized crossover study. SettingA 42-bed medicosurgical ICU in a university hospital PatientsMedicosurgical ventilated patients at risk of gastrointestinal bleeding. InterventionsAfter baseline determination of intragastric pH, patients were randomly allocated to have a 40-mg iv omeprazole bolus injection (arm I) or 80 mg bolus, followed by 8 mg/hr continuous infusion for 24 hrs (arm II). After a 24-hr washout period, the opposite regimen was given in a crossover design. Intragastric pH was determined at regular intervals during the treatment period. ResultsIn ten patients completing the protocol, the intragastric pH was similar for the two regimens for the first 12 hrs. The area under the pH curve was 5.51 ± 0.48 for arm I compared with 6.02 ± 0.33 for arm II (NS). Time to reach a pH of 4 or 6 was not significantly different for the two regimens. Time spent with a pH greater than 4 and 6 for the first 12 hrs was 10.11 ± 1.14 and 8.31 ± 1.16 hrs vs. 10.11 ± 0.75 and 7.43 ± 1.19 hrs for arm I and arm II, respectively (NS). When the first 24 hrs are considered, the area under the pH curve was 5.17 ± 0.49 for arm I vs. 6.36 ± 0.25 for arm II (p < .05). Time spent with a pH greater than 4 and 6 was 17.2 ± 2.4 hrs and 12.63 ± 2.22 vs. 23 ± 0.41 and 19.48 ± 1.63 in arm I and arm II, respectively (p < .05 and .01). An intragastric pH above 6 for all determinations was only observed in arm II. ConclusionsIn critically ill patients, intravenous omeprazole 40 mg single dose is as effective as 8 mg/hr after an 80-mg bolus injection on mean intragastric pH, time spent with a pH greater than 4 and 6, but only for the first 12 hrs. If an intragastric pH greater than 6 has to be maintained for 24 hrs in all patients, an 80-mg bolus followed by 8 mg/hr iv omeprazole is to be given. Our data suggest that in several critically ill patients, a single 40-mg iv omeprazole bolus injection may be able to achieve stress ulcer prophylaxis and that 40 mg twice daily should be compared with 8 mg/hr after an 80-mg bolus injection in bleeding ulcers.
Research designs for studies evaluating the effectiveness of change and improvement strategies

The methods of evaluating change and improvement strategies are not well described. The design and conduct of a range of experimental and non-experimental quantitative designs are considered. Such study designs should usually be used in a context where they build on appropriate theoretical, qualitative and modelling work, particularly in the development of appropriate interventions. A range of experimental designs are discussed including single and multiple arm randomised controlled trials and the use of more complex factorial and block designs. The impact of randomisation at both group and individual levels and three non-experimental designs (uncontrolled before and after, controlled before and after, and time series analysis) are also considered. The design chosen will reflect both the needs (and resources) in any particular circumstances and also the purpose of the evaluation. The general principle underlying the choice of evaluative design is, however, simple—those conducting such evaluations should use the most robust design possible to minimise bias and maximise generalisability.
Feature selection and fast training of subspace based support vector machines

In this paper, we propose two methods for subspace based support vector machines (SS-SVMs) which are subspace based least squares support vector machines (SSLS-SVMs) and subspace based linear programming support vector machines (SSLP-SVMs): 1) optimum selection of the dictionaries of each class subspace from the standpoint of classification separability, and 2) speeding up training SS-SVMs. In method 1), for SSLS-SVMs, we select the dictionaries with optimized weights, and for SSLP-SVMs, we select the dictionaries without non-negative constraints. In method 2), the empirical feature space is obtained by using only the training data belonging to a class instead of using all the training data. Thus the dimension of the empirical feature space and training cost become lower. We demonstrate the effectiveness of the proposed methods over the conventional method for two-class bench mark datasets.
A Complete Description of the QoS Feasibility Region in the Vector Broadcast Channel

We characterize the complete quality-of-service (QoS) feasibility region and present a simple feasibility test for given QoS requirements in the Gaussian vector broadcast channel. While most contributions in the literature recast the QoS constraints into requirements for the signal-to-interference-and-noise ratios (SINRs), we convert them into upper bounds for the minimum mean square errors (MMSEs) instead and test feasibility in the MMSE domain. Our main contribution is a complete description of the feasible MMSE region. Its closure is shown to be a polytope and we find the complete set of its bounding half-spaces noniteratively after a finite number of steps. The polytope can easily be converted into any other QoS domain like SINR or rate. However, the simple geometry of the MMSE domain is lost in other domains. Once the bounding half-spaces are determined, any target MMSE tuple can quickly be checked for feasibility by verifying its membership to the interior of the polytope. For nondegenerate channels, the only relevant bounding half-space is essentially the lower bound on the sum mean square error. No further computations are necessary contrary to existing feasibility checks which iteratively solve eigenproblems in an alternating optimization framework for every single QoS requirement to test. For two particular user/antenna configurations, we find a noniterative closed form solution for the optimum power allocation of the signal-to-interference ratio (SIR) balancing.
Measuring the local and global evaporation rate of fast evaporating droplets with interferometry

In the current work, digital holographic interferometry is used to measure the refractive index field surrounding evaporating droplets. From this measurement, several key quantities can be extracted. These are the vapour mole fraction distribution surrounding the droplet, the temperature and local evaporation rate all along the interface of the droplet and finally, the global evaporation rate. All these measurements can be extracted from a single image. This novel technique is applied to an evaporating pending droplet deposited on a silicon wafer. As the chosen liquid (HFE-7000) has a very heavy vapour, the resulting vapour plume is shown to be heavily modified due to natural diffusion. This convectional motion is here shown to boost the total evaporation rate by a factor 4. This work was recently published in Langmuir [6].
A step towards high quality one-class Collaborative Filtering using online social relationships

Current available recommender systems mostly predict the target user's preferences using the traditional method, Collaborative Filtering (CF), which relies on people who share similar interests with the target user. Unfortunately, CF may lead to an invalid recommendation due to the lack of explicit feedback or item ratings from users in the real-world systems. One-class Collaborative Filtering (OCCF) became more realistic since it takes only positive examples or implicit feedback into consideration to provide better recommendations. The emergence of online social networking services which are growing at an explosive rate and the generate-and-share contents on countless number of news updates, opinions, interests and reviews lead to the social networking based recommendation approaches. Therefore, we wished to take advantage of social networking services to improve OCCF. In this paper, we propose a novel method for OCCF using online social relationships to increase a prediction accuracy of the recommendations. It is believed that social-relationship data can reflect the social influence, in other words, the interests of a user are similar to that of his/her friends in an online social network. Non-negative Matrix Factorization (NMF) method was applied with social influence weighting scheme to the one-class problem. Based on the experimental evaluation and two decision-support measures, our method presented proved to provide higher quality of recommendation results than the other baseline methods.
A method for estimation of polymer melt temperature fluctuation in a single screw extrusion process

A method for estimating the polymer melt extrudate temperature fluctuation in the single screw extrusion process is proposed. Predictions of the melt temperature fluctuation is feasible if the extrusion process parameters are known. The method is superior to these in the literature because it incorporates effects of the melting process on the temperature fluctuation. The method has been verified experimentally.
Improved DVQ algorithm for speech recognition: a new adaptive learning rule with neurons annihilation

In this paper, three techniques are introduced to improve the DVQ algorithm. The rst one consists in an automatic algorithm to determine the threshold , a function of the minimum class variance, by a cross validation procedure. The second improvement consists in a new adaptive learning rule based on a spatial geometry considerations. The algorithm is proposed to reduce an instability phenomenon which may appear during learning. Finally a criterion of neurons annihilation is proposed to remove unnecessary elements from the system to ensure network stability. Some experiments on real speech data are presented to show the eeects of these three techniques on the network properties, including the learning time duration , the number of references and the recognition rate in each case.
Intrahepatic Vascular Anatomy in Rats and Mice—Variations and Surgical Implications

Introduction The intra-hepatic vascular anatomy in rodents, its variations and corresponding supplying and draining territories in respect to the lobar structure of the liver have not been described. We performed a detailed anatomical imaging study in rats and mice to allow for further refinement of experimental surgical approaches. Methods LEWIS-Rats and C57Bl/6N-Mice were subjected to ex-vivo imaging using μCT. The image data were used for semi-automated segmentation to extract the hepatic vascular tree as prerequisite for 3D visualization. The underlying vascular anatomy was reconstructed, analysed and used for determining hepatic vascular territories. Results The four major liver lobes have their own lobar portal supply and hepatic drainage territories. In contrast, the paracaval liver is supplied by various small branches from right and caudate portal veins and drains directly into the vena cava. Variations in hepatic vascular anatomy were observed in terms of branching pattern and distance of branches to each other. The portal vein anatomy is more variable than the hepatic vein anatomy. Surgically relevant variations were primarily observed in portal venous supply. Conclusions For the first time the key variations of intrahepatic vascular anatomy in mice and rats and their surgical implications were described. We showed that lobar borders of the liver do not always match vascular territorial borders. These findings are of importance for the design of new surgical procedures and for understanding eventual complications following hepatic surgery.
Regulation of short-term associative memory by calcium-dependent protein kinase

Neural and behavioral correlates of an associative memory in Hermissenda were examined during induction and/or formation of the memory. Hermissenda received either light (conditioned stimulus or CS) and rotation (unconditioned stimulus or US) paired (i.e., Pavlovian conditioning), light and rotation unpaired (pseudoconditioning), or no exposure to light and rotation. Following 9 pairings in a 6 min session, conditioned animals exhibited a contraction of the foot in response to a test CS presented 2 min after the last conditioning trial, whereas pseudoconditioned and untreated animals exhibited a foot extension to the same CS. In addition, both an associative and a nonassociative reduction in light-induced locomotion was observed. To examine neural correlates of this learning within minutes of acquisition, the isolated nervous system of the Hermissenda (containing the visual and vestibular organs) was trained with stimulus conditions identical to those used for the intact animal. Prior isolation and preparation of the nervous system permitted immediate intracellular recording following the final conditioning trial. Relative to pseudoconditioned and untreated animals, the B photoreceptors in conditioned nervous systems were found to have elevated input resistance (inversely related to K+ channel conductance and positively related to excitability) and exhibited increased steady-state depolarization in response to the light CS, as well as a prolonged depolarization after the CS offset. These neural correlates of the associative memory were attenuated if the protein kinase inhibitor H7 was present in the extracellular bath during conditioning, demonstrating in the reduced preparation that antagonism of protein kinase activity blocks the induction of membrane alterations of identified neurons that correlate with memory storage. (ABSTRACT TRUNCATED AT 250 WORDS)
A Scalable Kernel-Based Algorithm for Semi-Supervised Metric Learning

In recent years, metric learning in the semisupervised setting has aroused a lot of research interests. One type of semi-supervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale up well with the data set size. In this paper, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.
Adaptive subjective triggers for opinionated document retrieval

This paper proposes a novel application of a statistical language model to opinionated document retrieval targeting weblogs (blogs). In particular, we explore the use of the trigger model---originally developed for incorporating distant word dependencies---in order to model the characteristics of personal opinions that cannot be properly modeled by standard n-grams. Our primary assumption is that there are two constituents to form a subjective opinion. One is the subject of the opinion or the object that the opinion is about, and the other is a subjective expression; the former is regarded as a triggering word and the latter as a triggered word. We automatically identify those subjective trigger patterns to build a language model from a corpus of product customer reviews. Experimental results on the TREC Blog Track test collections show that, when used for reranking initial search results, our proposed model significantly improves opinionated document retrieval by over 20% in MAP. In addition, we report on an experiment on dynamic adaptation of the model to a given query, which is found effective for most of difficult queries categorized under politics and organizations.
A capacitive sensor for 2,4-D determination in water based on 2,4-D imprinted polypyrrole coated pencil electrode

A capacitive sensor for 2,4-dichloro phenoxy acetic acid(2,4-D) determination in drinking water has been developed using molecularly imprinted polypyrrole on pencil graphite electrode (PGE). Molecular imprinted polymer (MIP) coated PGE was prepared by electropolymerization of pyrrole via chronopotentiometry in the presence of 2,4-D as the template molecule. The prepared electrodes were characterized by field emission gun-scanning electron microscopy, cyclic voltammetry, and electrochemical impedance spectroscopy (EIS). The capacitance change of MIP electrode was measured in the presence of 2,4-D using EIS. The developed capacitive sensor exhibited a linear range 0.06–1.25 µg l−1 2,4-D with limit of detection of 0.02 µg l−1 and good selectivity towards 2,4-D in water with recovery from 92 to 110%. The results suggest the viable applicability of the MIP/PGE based sensor for the determination of the 2,4-D in water samples.
Histone Deacetylase Inhibitors Improve the Replication of Oncolytic Herpes Simplex Virus in Breast Cancer Cells

New therapies are needed for metastatic breast cancer patients. Oncolytic herpes simplex virus (oHSV) is an exciting therapy being developed for use against aggressive tumors and established metastases. Although oHSV have been demonstrated safe in clinical trials, a lack of sufficient potency has slowed the clinical application of this approach. We utilized histone deacetylase (HDAC) inhibitors, which have been noted to impair the innate antiviral response and improve gene transcription from viral vectors, to enhance the replication of oHSV in breast cancer cells. A panel of chemically diverse HDAC inhibitors were tested at three different doses (<, = , and >LD50) for their ability to modulate the replication of oHSV in breast cancer cells. Several of the tested HDAC inhibitors enhanced oHSV replication at low multiplicity of infection (MOI) following pre-treatment of the metastatic breast cancer cell line MDA-MB-231 and the oHSV-resistant cell line 4T1, but not in the normal breast epithelial cell line MCF10A. Inhibitors of class I HDACs, including pan-selective compounds, were more effective for increasing oHSV replication compared to inhibitors that selectively target class II HDACs. These studies demonstrate that select HDAC inhibitors increase oHSV replication in breast cancer cells and provides support for pre-clinical evaluation of this combination strategy.
Skin Color Protection Based on Wide Gamut Display

Gamut extension algorithm transforms a picture to display in wide gamut, exerting a good performance. However, human skin color belongs to static color, if extended, it would look unnatural and affect the beauty of the image. So we presents an algorithm for protecting skin color during color gamut extension. Firstly, we initially identify skin color regions. Then, according to probabilistic model, a new method that we use it to avoid looking hair as face skin with similar color. Experimental results demonstrate that our proposed method does protect skin color and improve performance.
Selection of basic position in Refill Friction Stir Spot Welding of 2024-T3 and D16UTW aluminum alloy sheets

One of the important parameters of Refill Friction Stir Spot Welding is the so-called basic position of the tool. This is the arrangement of the pin and sleeve which occurs when the tool is plunged into the material. The basic positions can be divided into two categories. In the first category, the sleeve and the pin are above the sheet surface or below sheet surface and in the second category the pin is retracted within the sleeve or protrudes from it. The aim of the work was to test four settings of the basic position, and then determine the best setting of the basic position, without changing the other welding parameters. Joints made of an aluminum alloy 2024-T3 sheet having a thickness of 1.0 mm and an aluminum alloy D16UTW sheet having a thickness of 0.6 mm were analysed. The best setting of the basic position was determined based on assessment of the force carried in shear test, macrostructure and weld face of the joints.
A novel fiber-tip micro-cavity sensor for high temperature application

A low cost fiber-optic micro-cavity interferometric sensor is presented. The micro-cavity is fabricated at the fiber tip by splicing a silica capillary to a single mode fiber and then heating/melting the capillary to form a microsphere with an internal air cavity. The sensor has small size and good mechanical strength, and may be used for pressure and temperature measurement in high temperature environment.
Nuclear Radiation Detectors Based on 4H-SiC p+-n Junction

Silicon carbide (SiC) radiation detectors were realized by 10B implantation into the metal contact in order to avoid implantation-related defects within the sensitive area of the 4H-SiC pn junction. No post implantation annealing was performed. Such detectors respond to thermal neutrons showing consistent counting rates as function of external reverse bias voltages and radiation intensity.
Cluster-based failure detection service for large-scale ad hoc wireless network applications

The growing interest in ad hoc wireless network applications that are made of large and dense populations of lightweight system resources, calls for scalable approaches to fault tolerance. Moreover, the nature of these systems creates significant challenges for the development of failure detection services (FDSs), because their quality often depends heavily on reliable communication. In particular, ad hoc wireless networks are notoriously vulnerable to message loss, which precludes deterministic guarantees for the completeness and accuracy properties of FDSs. To meet the challenges, we propose an FDS based on the notion of clustering. Specifically, we use a cluster-based communication architecture to permit the FDS to be implemented in a distributed manner via intra-cluster heartbeat diffusion and to allow a failure report to be forwarded across clusters through the upper layer of the communication hierarchy. In doing so, we extensively exploit the message redundancy that is inherent in ad hoc wireless settings to mitigate the effects of message loss on the accuracy and completeness properties of failure detection. As shown by our mathematical analysis, the resulting FDS is able to provide satisfactory probabilistic guarantees for the desired properties.
Integrated many-to-many multicast addressing and access control method

IP multicast is an efficient method for distributing multimedia content to a large number of receivers while saving the network bandwidth and reducing processing overhead on the source side. However, current IP multicast deployment figure is still far away behind the expectations of both internet service and content providers due to several deployment complexities. In particular, multicast routers cannot trigger automatically a unidirectional or a bidirectional multicast routing protocol unless they are manually configured to use a specific routing protocol for a predetermined pool of IP multicast addresses. To limit flooding multicast content, each multicast group is identified by a specific scope. With such scope, the access control rights of senders and receivers access are not properly defined. To ease multicast router dynamic auto-configuration and access control check, we propose a new integrated multicast addressing and access control method1. In our new method, we define a new expanded scope filed for IPv6, which enables a plurality of hierarchical distribution scopes to be embedded simultaneously within the multicast address. In addition, in the new scope format, the access rights are encoded for each distribution scope with respect to sending and receiving permissions.