Miracle-dz/UniFAR-FTUs huggingface dataset:
Can proton pump inhibitors reduce rebleeding following Histoacryl sclerotherapy for gastric variceal hemorrhage?

Background/Aims: To evaluate the efficacy of proton pump inhibitors (PPIs) in reducing rebleeding and bleeding-related death rates after endoscopic gastric variceal obliteration (GVO) using N-butyl-2-cyanoacrylate (NBC). Methods: This study enrolled 341 patients who were consecutively diagnosed with and treated for bleeding gastric varices. The patients were divided into PPI and non-PPI groups, and their endoscopic findings, initial hemostasis outcomes, rebleeding and bleeding-related death rates, and treatment-related complications were analyzed. Results: The rate of initial hemostasis was 97.1%. rebleeding occurred in 2.2% of patients within 2 weeks, 3.9% of patients within 4 weeks, 18.9% of patients within 6 months, and 27.6% of patients within 12 months of the GVO procedure. A previous history of variceal bleeding (relative risk [RR], 1.955; 95% confidence interval [CI], 1.263 to 3.028; p = 0.003) and use of PPIs (RR, 0.554; 95% CI, 0.352 to 0.873; p = 0.011) were associated with rebleeding. Child-Pugh class C (RR, 10.914; 95% CI, 4.032 to 29.541; p < 0.001), failure of initial hemostasis (RR, 13.329; 95% CI, 2.795 to 63.556; p = 0.001), and the presence of red-colored concomitant esophageal varices (RR, 4.096; 95% CI, 1.320 to 12.713; p = 0.015) were associated with bleeding-related death. Conclusions: The prophylactic use of PPIs reduces rebleeding after GVO using NBC in patients with gastric variceal hemorrhage. However, prophylactic use of PPIs does not reduce bleeding-related death.
Dynamic Epistemic Logic II: Logics of Information Change

Dynamic epistemic logic, broadly conceived, is the study of logics of information change. Inference, communication and observation are typical examples of informative events which have been subjected to a logical analysis. This article will introduce and critically examine a number of dierent logical systems that have been used to reason about the knowledge and beliefs of a group of agents during the course of a social interaction or rational inquiry. The goal here is not to be comprehensive, but rather to discuss the key conceptual and technical issues that drive much of the research in this area.
Gaussian processes for learning-based indoor localization

The development of an efficient and accurate location sensing systems for indoor environments, based on the received signal strength (RSS) data, is usually a challenging task. In this paper, we discuss the feasibility of using Gaussian Processes (GPs) regression for learning based indoor localization algorithm. The GP is one of the machine learning algorithms that can be used to model a complete RSS map from few training data. We investigate the use of three different covariance functions, i.e. Squared Exponential (SE), Matérn, and Rational Quadratic (RQ), to find the suitable one for the indoor localization, and then compare their performance to the traditional weighted k-Nearest Neighbors (k-NN) algorithm. We show that GP regression can significantly outperform the k-NN, while keeping the training cost at a reasonable level. Furthermore, although, the smoothness property of SE covariance function, we demonstrate that GP-SE covariance provides better accuracy compared to GP-Matérn and GP-RQ, particularly, when a few training data are available.
A fast and efficient translational control system for conditional expression of yeast genes

A new artificial regulatory system for essential genes in yeast is described. It prevents translation of target mRNAs upon tetracycline (tc) binding to aptamers introduced into their 5′UTRs. Exploiting direct RNA–ligand interaction renders auxiliary protein factors unnecessary. Therefore, our approach is strain independent and not susceptible to interferences by heterologous expressed regulatory proteins. We use a simple PCR-based strategy, which allows easy tagging of any target gene and the level of gene expression can be adjusted due to various tc aptamer-regulated promoters. As proof of concept, five differently expressed genes were targeted, two of which could not be regulated previously. In all cases, adding tc completely prevented growth and, as shown for Nop14p, rapidly abolished de novo protein synthesis providing a powerful tool for conditional regulation of yeast gene expression.
When Individual Cultural Orientation and Mediated Portrayal of Risk Intersect: Effects of Individualism–Collectivism and Media Framing on Risk Perception and Attribution of Responsibility

Using the cultural theory of risk, this study examines the effects of individualism&#8211;collectivism and media framing on individuals&#8217; risk perception and attribution of responsibility. The findings of a between&#8208;subjects experiment suggest that media framing (episodic vs. thematic framing) is a significant moderator of the effect of individualism&#8211;collectivism on risk perception (the perceived magnitude of the risk), and that collectivists have more intense emotions and perceive a more serious risk than individualists. The results of path analysis further show that individualism&#8211;collectivism and media framing influence individuals&#8217; attribution of responsibility through emotion and the perceived magnitude of the risk. This study contributes to an increased understanding of risk perception with an emphasis on the interaction between culture and mediated portrayal of a risk.
Generalizing Dynamic Time Warping to the Multi-Dimensional Case Requires an Adaptive Approach

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress in improving DTW’s efficiency, together with multiple empirical studies showing that DTW-based classifiers at least equal (and generally surpass) the accuracy of all their rivals across dozens of datasets. Thus far, most of the research has considered only the one-dimensional case, with practitioners generalizing to the multi-dimensional case in one of two ways, dependent or independent warping. In general, it appears the community believes either that the two ways are equivalent, or that the choice is irrelevant. In this work, we show that this is not the case. The two most commonly used multi-dimensional DTW methods can produce different classifications, and neither one dominates over the other. This seems to suggest that one should learn the best method for a particular application. However, we will show that this is not necessary; a simple, principled rule can be used on a case-by-case basis to predict which of the two methods we should trust at the time of classification. Our method allows us to ensure that classification results are at least as accurate as the better of the two rival methods, and, in many cases, our method is significantly more accurate. We demonstrate our ideas with the most extensive set of multi-dimensional time series classification experiments ever attempted. Keywords—Dynamic Time Warping; Classification; Gesture Recognition; Wearable Devices
Substrate Vibrations during Courtship in Three Drosophila species

While a plethora of studies have focused on the role of visual, chemical and near-field airborne signals in courtship of Drosophila fruit flies, the existence of substrate-borne vibrational signals has been almost completely overlooked. Here we describe substrate vibrations generated during courtship in three species of the D. melanogaster group, from the allegedly mute species D. suzukii, its sister species D. biarmipes, and from D. melanogaster. In all species, we recorded several types of substrate vibrations which were generated by locomotion, abdominal vibrations and most likely through the activity of thoracic wing muscles. In D. melanogaster and D. suzukii, all substrate vibrations described in intact males were also recorded in males with amputated wings. Evidence suggests that vibrational signalling may be widespread among Drosophila species, and fruit flies may provide an ideal model to study various aspects of this widespread form of animal communication.
Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings.
Differential Effect of Right and Left Basal Ganglionic Infarctions on Procedural Learning

Objective:To assess the effect of ischemic infarctions affecting the basal ganglia (BG) region on a series of procedural learning tasks. Background:The basal ganglia hypothesis of procedural learning is a matter of debate. As most of the relevant research so far is based on examination of patients suffering from Parkinson disease, this inconsistency might reflect either lesion heterogeneity existing in this pathologic group or the heterogeneity of the procedural learning tasks. Method:Twelve patients with lesions confined to the right (BGr), 10 to the left (BGl) BG region, and 15 matched controls participated in the study. Three procedural learning tasks were used: Tower of Hanoi Puzzle, Mirror Reading, and Porteus Mazes. Declarative memory and general intelligence were also tested. Results:Verbal declarative memory was impaired in the BGl group. For each procedural learning task, baseline performance and learning rate were analyzed. Tower of Hanoi Puzzle: Baseline performance of the BGl group was impaired compared with the other groups. The BGr group was the only group that did not improve over learning trials. MR: Baseline performance of the BGr group was impaired compared with the other groups. The groups’ learning rate did not differ significantly. Porteus Mazes: Baseline performance of both patient groups was impaired compared with that of the control group. Learning rate over repetitive trials of the same maze was impaired in the BGr group. However, the transfer of procedural learning to a newly exposed maze was impaired in the BGl group. Conclusions:First, right and left basal ganglia play different roles in different procedural learning tasks. Second, procedural learning is not a unitary capacity subserved by any single neural mechanism.
Study on ann-based intelligent self-tuning PID controller

PID controllers are widely used in the military field. But the conventional PID controller is difficult to be used for the nonlinear and imprecise mathematical model system, since its parameters can only be obtained from the system with accurate mathematical model. In this paper, the intelligent self-tuning PID controller based on neural network is designed for the system which is nonlinear and does not have mathematical model. The designed neural network of the controller can identify the real-time parameters and the controller can be used in the missile engine hung in the airplane to realize the PID control. The identification is simulated. The experimental results and simulation show that the intelligent self-tuning PID controller based on neural network is feasible. One of the difficulties that design the neural network is to determine the number of the layer, the neurons in the hidden layer and the learning rate. The other is to choose MOBP or SDBP network. To this point, this article has solved the problem for the intelligent self-tuning PID controller using in the missile engine hung in the airplane.
Pressure of a Partially Ionized Hydrogen Gas: Numerical Results from Exact Low Temperature Expansions

We consider a partially ionized hydrogen gas at low densities, where it reduces almost to an ideal mixture made with hydrogen atoms in their ground‐state, ionized protons and ionized electrons. By performing systematic low‐temperature expansions within the physical picture, in which the system is described as a quantum electron‐proton plasma interacting via the Coulomb potential, exact formulae for the first.ve leading corrections to the ideal Saha equation of state have been derived [A. Alastuey, V. Ballenegger et al., J. Stat. Phys. 130, 1119 (2008)]. Those corrections account for all effects of interactions and thermal excitations up to order exp(EH /kT) included, where EH ≃ –13.6 eV is the ground state energy of the hydrogen atom. Among the.ve leading corrections, three are easy to evaluate, while the remaining ones involve suitably truncated internal partition functions of H2 molecules and H– and H2+ ions, for which no analytical formulae are available in closed form. We estimate those partitions functions at.nite temperature via a simple phenomenology based on known values of rotational and vibrational energies. This allows us to compute numerically the leading deviations to the Saha pressure along several isotherms and isochores. Our values are compared with those of the OPAL tables (for pure hydrogen) calculated within the ACTEX method (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Vagaries of the Euro: an Introduction to ARIMA Modeling

The goal of this study is to provide a detailed example of ARIMA modeling in the form of a case study that could be used for teaching and learning purposes. We present three ARIMA models using macroeconomic indicators to model the USD/EUR exchange rate. We find that over the period from January 1994 to October 2007, the monthly USD/EUR exchange rate is best modeled by a linear relationship between its past three values and the current and past three values of the difference between the log-levels of the share prices indices in the European Monetary Union and the USA.
Statistical Language Modeling of SiBN Broadcast News Text Corpus

The paper presents acquisition of the Slovenian broadcast n ews text corpus and its application in statistical language modeling. The problems encountered during the acquisition are described as well as constructing of language models for speech recogn ition purposes. Three different types of language models are built: a word-b ased 4-gram model, a class-based model with statisticallyderived class maps and an interpolated model, combining the previous two. The comparison of language models is represented in terms of e timated perplexities on one third and one tenth of overall data used i n evaluation experiments. Statistično jezikovno modeliranje tekstovnega korpusa informativnih oddaj SiBN V članku je predstavljena gradnja slovenskega besedilneg a korpusa televizijskih informativnih oddaj SiBN in njegov a uporaba pri statističnem jezikovnem modeliranju, namenjenemu samod ejnemu razpoznavanju govora. Opisana je priprava in zbiran je besedil za gradnjo korpusa ter preizkusi statističnega jezikovnega mode liranja z uporabo teh podatkov. Zgrajeni so bili trije razli čni tipi jezikovnih modelov: besedni 4-gramski model, razredni model s statistič no pridobljenimi razredi in interpolacijski model, ki je ko mbinacija prejšnjih dveh. Jezikovne modele smo primerjali med seboj na podlagi o cenjenih perpleksnosti, ki smo jih pridobili na testnem bes edilu ene tretjine in ene desetine celotne zbirke.
The Molecular Population Genetics of HIV-1 Group O

HIV-1 group O originated through cross-species transmission of SIV from chimpanzees to humans and has established a relatively low prevalence in Central Africa. Here, we infer the population genetics and epidemic history of HIV-1 group O from viral gene sequence data and evaluate the effect of variable evolutionary rates and recombination on our estimates. First, model selection tools were used to specify suitable evolutionary and coalescent models for HIV group O. Second, divergence times and population genetic parameters were estimated in a Bayesian framework using Markov chain Monte Carlo sampling, under both strict and relaxed molecular clock methods. Our results date the origin of the group O radiation to around 1920 (1890–1940), a time frame similar to that estimated for HIV-1 group M. However, group O infections, which remain almost wholly restricted to Cameroon, show a slower rate of exponential growth during the twentieth century, explaining their lower current prevalence. To explore the effect of recombination, the Bayesian framework is extended to incorporate multiple unlinked loci. Although recombination can bias estimates of the time to the most recent common ancestor, this effect does not appear to be important for HIV-1 group O. In addition, we show that evolutionary rate estimates for different HIV genes accurately reflect differential selective constraints along the HIV genome.
SINTEF REPORT TITLE Route Construction and Local Search Algorithms for the Vehicle Routing Problem with Time Windows

This report presents a survey of research on the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval, all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Both traditional heuristic route construction methods and recent local search algorithms are examined. The basic features of each method are described, and experimental results for Solomon’s benchmark test problems are presented and analyzed. Moreover, we discuss how heuristic methods should be evaluated and propose using the concept of Pareto optimality in the comparison of different heuristic approaches. The metaheuristic methods are described in Bräysy and Gendreau (2001).
RAM Design Using Quantum-Dot Cellular Automata

Quantum-dot cellular automata (QCA) is a novel and potentially attractive technology for implementing computing architectures at the nano-scale. By applying a set of simple layout rules, arbitrary circuits can be made using QCA cells. In this work, we describe the design and layout of a QCA random access memory (RAM), showing the layout of individual memory cells, as well as, a suggested layout for a 1x4 RAM. The RAM is based on a 2D grid of row addressable memory cells. Each of the memory cells in the RAM uses 158 QCA cells. Assuming that we can fabricate cells which are separated by 10nm, memory capacities of over 1.6 Gbit/cm can be achieved. Simulations on the proposed memories were carried out using QCADesigner, a layout and simulation tool for QCA, by iteratively applying an intercellular Hartree-Fock approximation.
INFLOWS AND OUTFLOWS IN THE DWARF STARBURST GALAXY NGC 5253: HIGH-RESOLUTION H i OBSERVATIONS

Very Large Array and Parkes 64 m radiotelescope 21 cm observations of the starburst dwarf galaxy NGC 5253 reveal a multi-component non-axisymmetric H i distribution. The component associated with the stellar body shows evidence for a small amount of rotational support aligned with the major axis, in agreement with optically measured kinematics and consistent with the small galactic mass. Approximately 20–30% of the H i emission is associated with a second component, an H i “plume” extending along the optical minor axis to the southeast. We consider outflow, inflow, and tidal origins for this feature. Outflow appears improbable, inflow is a possibility, and tidal debris is most consistent with the observations. Thus, kinematics of the H i that include this feature are not indicative of the dynamical mass or the local velocity dispersion of the cold gas. These H i observations also reveal a filamentary third component that includes an 800 pc diameter H i shell or bubble to the west of the nucleus, coinciding with an Hα shell. The mass of H i in the shell may be as large as ∼4 × 106 M☉. This large mass, coupled with the lack of expansion signatures in the neutral and ionized gas (v < 30 km s−1), suggests that this feature may be an example of a starburst-blown bubble stalled by interaction with a massive neutral envelope. Many other H i kinematic features closely resemble those seen in Hα emission from the ionized gas, supporting the interpretation of neutral and ionized gas outflow at velocities of ∼30 km s−1. Comparison between extinction estimates from the Balmer emission-line decrement and the H i column densities suggests a gas-to-dust ratio 2–3 times the Galactic value in this low-metallicity (Z = 1/4Z☉) galaxy.
Coarse-grained simulations of branched bilayer membranes: effects of cholesterol-dependent phase separation on curvature-driven lipid sorting

Our recent coarse-grained (CG) molecular dynamics (MD) simulations of membranes with a hemifused-ribbon (λ-shaped) geometry showed curvature-driven demixing leading to enrich ment in dioleoyl-phosphatidylethanolamine (DOPE) in a negatively-curved region (at C = –0.8 nm–1) of a DOPE/dipalmitoyl-phosphati-dylcholine (DPPC) membrane. Here we extend the analysis with respect to lipid composition and simulation time. Simulations of 12 – 20 μs effective time show that, compared with DOPE of the DOPE/DPPC system, a DPPC/dilinoleyl-PC [di(18:2)PC] membrane showed a similar degree of enrichment of di(18:2)PC in the curved region with C=–0.8 nm–1. For the latter mixture, even weak negative curvatures (C=–0.5 – 0.6 nm–1) caused significant degrees of di(18:2)PC enrichment. In agreement with recent studies of a planar bilayer, a ternary DPPC/ di(18:2)PC/cholesterol 0.42:0.28:0.3 mixture phase-separated into nanoscale raft-like liquid-ordered (Lo) and non-raft liquid-disordered (Ld) phases on a sub-microsecond time scale. The Lo domains were preferentially localized at planar portions, whereas the Ld domains were positioned mainly in curved regions of the membrane. Unlike binary dioleoylphosphatidylcho-line (DOPC)/cholesterol and DPPC/cholesterol mixtures, which showed only a slight enrich ment of cholesterol in the curved region, the ternary mixtures showed considerable migra tion of cholesterol and DPPC from the curved to the planar region. A pronounced degree of lipid segregation due to the preferential distribution of the Ld and Lo domains in the curved and planar regions, respectively, was observed even when the curvature of the fused monolayers (originally ‘cis’ leaflets) was weakened (C= –0.5 nm-1). Overall, the results are consistent with theoretical predictions based on spontaneous curvature of the constituent lipids and the difference in rigidity between the Ld and Lo domains, whereas lipid-lipid interactions, such as PE-PE or DPPC-cholesterol, as well as propensity for interleaflet colocalization (registration) of the Lo and Ld domains appear to significantly amplify curvature-induced lipid demixing in the λ system. Intriguingly, for the DPPC/ di(18:2)PC/cholesterol ternary mixtures, a Lo/Ld domain boundary often moved to the branched point of the membrane, suggesting enhanced flexibility at the domain boundary. We hypothesize that curvature-driven lipid sorting and energetically favored localization of domain boundaries at sharp bends in the membranes may collaborate to assist intracellular lipid sorting.