Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameters That May Be Used for Predicting Failure during Endoscopic Retrograde Cholangiopancreatography

Aim. Endoscopic retrograde cholangiopancreatography (ERCP) is frequently used for the diagnosis and treatment of hepatic, biliary tract, and pancreatic disorders. However, failure during cannulation necessitates other interventions. The aim of this study was to establish parameters that can be used to predict failure during ERCP. Methods. A total of 5884 ERCP procedures performed on 5079 patients, between 1991 and 2006, were retrospectively evaluated. Results. Cannulation was possible in 4482 (88.2%) patients. For each one-year increase in age, the cannulation failure rate increased by 1.01-fold (P = 0.002). A history of previous hepatic biliary tract surgery caused the cannulation failure rate to decrease by 0.487-fold (P < 0.001). A tumor infiltrating the ampulla, the presence of pathology obstructing the gastrointestinal passage, and peptic ulcer increased the failure rate by 78-, 28-, and 3.47-fold, respectively (P < 0.001). Conclusions.Patient gender and duodenal diverticula do not influence the success of cannulation during ERCP. Billroth II and Roux-en-Y gastrojejunostomy surgeries, a benign or malignant obstruction of the gastrointestinal system, and duodenal ulcers decrease the cannulation success rate, whereas a history of previous hepatic biliary tract surgery increases it. Although all endoscopists had equal levels of experience, statistically significant differences were detected among them.
The Emerging Roles of Viroporins in ER Stress Response and Autophagy Induction during Virus Infection

Viroporins are small hydrophobic viral proteins that oligomerize to form aqueous pores on cellular membranes. Studies in recent years have demonstrated that viroporins serve important functions during virus replication and contribute to viral pathogenicity. A number of viroporins have also been shown to localize to the endoplasmic reticulum (ER) and/or its associated membranous organelles. In fact, replication of most RNA viruses is closely linked to the ER, and has been found to cause ER stress in the infected cells. On the other hand, autophagy is an evolutionarily conserved “self-eating” mechanism that is also observed in cells infected with RNA viruses. Both ER stress and autophagy are also known to modulate a wide variety of signaling pathways including pro-inflammatory and innate immune response, thereby constituting a major aspect of host-virus interactions. In this review, the potential involvement of viroporins in virus-induced ER stress and autophagy will be discussed.
Magnetic Nanoparticles as Mediators of Ligand-Free Activation of EGFR Signaling

Background Magnetic nanoparticles (NPs) are of particular interest in biomedical research, and have been exploited for molecular separation, gene/drug delivery, magnetic resonance imaging, and hyperthermic cancer therapy. In the case of cultured cells, magnetic manipulation of NPs provides the means for studying processes induced by mechanotransduction or by local clustering of targeted macromolecules, e.g. cell surface receptors. The latter are normally activated by binding of their natural ligands mediating key signaling pathways such as those associated with the epidermal growth factor (EGFR). However, it has been reported that EGFR may be dimerized and activated even in the absence of ligands. The present study assessed whether receptor clustering induced by physical means alone suffices for activating EGFR in quiescent cells. Methodology/Principal Findings The EGFR on A431 cells was specifically targeted by superparamagnetic iron oxide NPs (SPIONs) carrying either a ligand-blocking monoclonal anti-EGFR antibody or a streptavidin molecule for targeting a chimeric EGFR incorporating a biotinylated amino-terminal acyl carrier peptide moiety. Application of a magnetic field led to SPION magnetization and clustering, resulting in activation of the EGFR, a process manifested by auto and transphosphorylation and downstream signaling. The magnetically-induced early signaling events were similar to those inherent to the ligand dependent EGFR pathways. Magnetization studies indicated that the NPs exerted magnetic dipolar forces in the sub-piconewton range with clustering dependent on Brownian motion of the receptor-SPION complex and magnetic field strength. Conclusions/Significance We demonstrate that EGFR on the cell surface that have their ligand binding-pocket blocked by an antibody are still capable of transphosphorylation and initiation of signaling cascades if they are clustered by SPIONs either attached locally or targeted to another site of the receptor ectodomain. The results suggest that activation of growth factor receptors may be triggered by ligand-independent molecular crowding resulting from overexpression and/or sequestration in membrane microdomains.
Atlas to Image-with-Tumor Registration Based on Demons and Deformation Inpainting

This paper presents a method for nonlinear registration of images, where there exists no one-to-one correspondence in parts of the image. Such a situation occurs for instance in the case where an atlas of normal anatomy shall be matched to pathological data, such as tumors, resections or lesions. Our idea is to use local confidence weights and to model pathological regions with zero confidence. We integrate this concept into the efficient and publicly available diffeomorphic demons registration framework. Finally, we show that this process better captures deformations in high-confidence regions than without using the proposed modification. Furthermore, it is easy to implement and runs faster than previous approaches.
Cheap Talk and Secret Intentions in a Public Goods Experiment

In a public goods experiment, subjects can vary over a period of stochastic length two contribution levels: one is publicly observable (their cheap talk stated intention), while the other is not seen by the others (their secret intention). When the period suddenly stops, participants are restricted to choose as actual contribution either current alternative. Based on the two types of choice data for a partners and a perfect strangers condition, we confirm that final outcomes strongly depend on the matching protocol. As to choice dynamics, we distinguish different types of adaptations.
Embodiment and Grounding in Cognitive Neuroscience

Research in embodied and grounded cognition is defined by the types of hypotheses researchers pursue, but are all interested in the ways in which the body, brain, and environment interact to give rise to intelligent behaviour. In cognitive neuroscience, it is hypothesized that simulations in modality-specific representations, situated and embedded in a behavioral context, underlie our ability to plan actions, discuss our thoughts, and coordinate our activities with each other. In this framework, representations are powerful, predictive constructs, and the locus of phenomena that tend to integrate the brain (i.e. neural networks), body, and immediate environment. Overall, the grounded perspective encourages us to think deeply about our cognitive ontology, cognition’s relation to the brain, and the dynamic processes that underlie our most complex behaviors. In this way, embodied and grounded perspectives promise to continue shaping research in cognitive neuroscience in highly productive ways.
Protein distance constraints predicted by neural networks and probability density functions.

We predict interatomic Calpha distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taking the context of the two residues into account. These two methods are used to predict whether distances in independent test sets were above or below given thresholds. We investigate which distance thresholds produce the most information-rich constraints and, in turn, the optimal performance of the two methods. The predictions are based on a data set derived using a new threshold which defines when sequence similarity implies structural similarity. We show that distances in proteins are predicted more accurately by neural networks than by probability density functions. We show that the accuracy of the predictions can be further increased by using sequence profiles. A threading method based on the predicted distances is presented. A homepage with software, predictions and data related to this paper is available at http://www.cbs. dtu.dk/services/CPHmodels/.
Secure multipath transport for legacy Internet applications

Multi-interface mobile devices and multihomed residential Internet connections are becoming commonplace. However, standard transport protocols TCP and SCTP are unable to take advantage of several available paths so that the application using a single transport connection would receive the aggregate bandwidth of all paths. Multihoming and advanced security features make the Host Identity Protocol a good candidate to provide multipath data delivery. In this paper, we design and implement a multipath scheduler that distributes the incoming traffic among multiple available paths. Using Fastest Path First scheduling, packets from a single TCP connection could be spread to multiple paths with no reordering. Our simulations confirm effectiveness and TCP-friendliness of multipath transfer for a range of path bandwidths and in the presence of cross-traffic.1
Contextual Modeling of Personality States' Dynamics in Face-to-Face Interactions

In this paper, we investigate the effectiveness of several dynamic graphical models for the task of personality states classification in a meeting scenario. Personality states are defined in social psychology literature as specific behavioral episodes in which a given subject exposes behaviors connected to a certain personality trait. The personality states we are addressing are those corresponding to the Big Five traits.
On the interpretation of noun compounds: Syntax, semantics, and entailment

Abstract We discuss the problem of interpreting noun compounds such as colon cancer tumor suppressor protein, which pose major challenges for the automatic interpretation of English written text. We present an overview of the more general process of compounding and of noun compounds in particular, as well as of their syntax and semantics from both theoretical and computational linguistics viewpoint with an emphasis on the latter. Our main focus is on computational approaches to the syntax and semantics of noun compounds: we describe the problems, present the challenges, and discuss the most important lines of research. We also show how understanding noun compound syntax and semantics could help solve textual entailment problems, which would be potentially useful for a number of NLP applications, and which we believe to be an important direction for future research.
Probability discounting of environmental gains: do we multiply or add up?

Abstract Individuals often discount and transform risky environmental outcomes into psychological certainty equivalences (CEs) during environmental decision-making. Their preference for different alternatives is influenced by the discounting degree. Our first experiment undertook a preliminary inspection of the probability discounting of environmental gains through a matching method; whereas in Experiment 2, the discounting rule of environmental gain was compared with monetary gain by a new line-projective method, which asked participants to project their subjective value evaluation explicitly on a line of specific length. The environmental gain and its mental value-equivalent monetary gain were analogical with respect to discounting degree and process model fitting. The probability discounting of both gains was better described by an additive-utility model than the normative exponential and hyperbolic models, which means that individuals were likely to discount the risky outcome by simply adding the disutility of uncertainty to the gain’s nominal utility, rather than by multiplying the initial value by a discounting factor. It may be of great value in shedding light on the lay public evaluation of risky environmental interventions and boosting pro-environmental policy support.
SNR Maximization for Linear Multi-antenna Relay Communications

We consider a linear relaying communication system using mu ltiple antennas at a source, relay, and destination. We maximize the end-to-end Signal-to-NoiseRatio (SNR) to find the relay transformation (RT) and the source transmit covariance (STC) matrices. For any given STC matrix and to maximize the SNR, we prove that the relay has to assign all its power in t he direction of the dominant eigenmodes of the source-relay and the R-D channels. We also find the join t optimal rank one matrices for the STC and RT. We prove that this solution also maximizes the source -destination mutual information among all rank-one matrices. Furthermore, we find the optimal power bu dgets allocated to the source and relay to maximize the SNR under a constraint on the total transmit pow er in the communications system. This is a practical solution as only three positive quantities ne ed to be communicated among the nodes to calculate these optimum power budgets. Interestingly, our c mputer simulations for multiple users reveal that the sum-rate significantly increases if users selfishly maximize their own SNRs using the proposed method, instead of maximizing their own capacity. Thus, we c onclude that the SNR-maximization is spectrally efficient as it consumes only the best subspaces a nd le ves the other subspaces free.
EXPLORING RELIGION BASED PERSUASIVE FACTORS TO RATIONALISE VIOLENCE AMONG MUSLIM YOUTH IN MALAYSIA

ABSTRACT The current study presents a qualitative experimental design that combines the elements of an experiment with qualitative design to investigate the persuasive factors that rationalize violence among youth in Malaysia. Data was collected using semi-structured interviews from twenty-four participants who were exposed to an intervention of videos and PowerPoint slides to elicit their responses on a situation. This study provides a way to understand factors that could lead selected youths to rationalize extremism in a society. The findings provide insight into the role of persuasive messaging in recruiting youth towards extremist behaviours. Keywords: extremism; communication; youth; persuasion
Study Lane Curvature Estimation Algorithm Based on Radar

Identifying the feature of road line accurately is one of the most important things helps the smart driving assistant system operate effectively. So, we propose a new method to estimate the lane curvature. The method bases on the information from radar of stationary objects and target vehicle head in order to calculate the lane curvature parameter. At first, we introduce the lane curvature parameter estimation method based on the information from radar of target vehicle ahead. After that, we use weighted average fusion algorithm to conduct to combine the two methods above in order to calculate the lane curvature accurately and the estimation range of lane. At last, via Carsim and Simulink we conduct to simulate the experiment toward the proposed method above. The results of experiment prove the efficient of the method.
Performance Simulation of Multi Protocol Optical Switch (MPOS) with Multicasting Capability for Optical GRID Networks

This paper presents a novel optical switch, MPOS concept which is capable of not only handling circuit, burst and packet based traffic but also performing all optical multicasting. This switch design is based upon a wavelength routed switching matrix with the used of SOAs as wavelength converters and also to perform multicasting. Optical switches with such capabilities are essential for future optical grid networking. Physical performance of the MPOS at 10 Gbps will be presented in this paper
Tensor Field Regularisation for DT-MR Images

Thermal insulation board is made by press moulding a mixt. of 100 pts. wt. spirally rolled pieces (I) of magnetic tape and 10-50 pts. wt. thermosetting resin as binder, (I) being obtd. by heating cut pieces of magnetic tape with lengths of up to 20 mm. Also claimed are frames for concrete shells made from this mixt. and a method for making boards suitable for these frames.
O-Proteobacterial diversity from a deep-sea hydrothermal vent on the

The prokaryotic phylogenetic diversity was determined for a sample associated with an in situ growth chamber deployed for 5 days on a Mid-Atlantic Ridge hydrothermal vent (23‡22PN, 44‡57PW). The DNA was extracted from the sample and the 16S rDNA amplified by PCR. No Archaea were detected in the sample. Eighty-seven clones containing bacterial 16S rDNA inserts were selected. Based on restriction fragment length polymorphism analysis, 47 clones were unique, however, based on comparative sequence analysis some of these were very similar, and thus only 22 clones were selected for full sequence and phylogenetic analysis. The phylotypes were dominated by OProteobacteria (66%). The remainder formed a novel lineage within the Proteobacteria (33%). One clone formed a distinct deeply branching lineage, and was a distant relative of the Aquificales. This report further expands the growing evidence that O-Proteobacteria are important members in biogeochemical cycling at deep-sea hydrothermal ecosystems, participating as epibionts and free living bacteria. fl 2001 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
Arbitrary Precision Real Arithmetic: Design and Algorithms

We describe here a representation of computable real numbers and a set of algorithms for the elementary functions associated to this representation. A real number is represented as a sequence of nite B-adic numbers and for each classical function (rational, algebraic or transcendental), we describe how to produce a sequence representing the result of the application of this function to its arguments, according to the sequences representing these arguments. For each algorithm we prove that the resulting sequence is a valid representation of the exact real result. This arithmetic is the rst real arithmetic with mathematically proved algorithms.
Resource allocation for full duplex based cognitive radio network

In this paper, the joint bandwidth and power allocation in cognitive radio (CR) network based on full duplex is investigated. We first formulate the optimal problem model of the full duplex based CR (FD-CR) network, and then the bandwidth allocation for the problem subject to bandwidth constraint is derived by the dual decomposition algorithm. Moreover, the optimal power allocation scheme under power constraint is analyzed. Simulation results indicate that the feasible of the proposed resource allocation scheme for FD-CR network.
Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection

This paper proposes a novel saliency detection method by developing a deeply-supervised recurrent convolutional neural network (DSRCNN), which performs a full image-to-image saliency prediction. For saliency detection, the local, global, and contextual information of salient objects is important to obtain a high quality salient map. To achieve this goal, the DSRCNN is designed based on VGGNet-16. Firstly, the recurrent connections are incorporated into each convolutional layer, which can make the model more powerful for learning the contextual information. Secondly, side-output layers are added to conduct the deeply-supervised operation, which can make the model learn more discriminative and robust features by effecting the intermediate layers. Finally, all of the side-outputs are fused to integrate the local and global information to get the final saliency detection results. Therefore, the DSRCNN combines the advantages of recurrent convolutional neural networks and deeply-supervised nets. The DSRCNN model is tested on five benchmark datasets, and experimental results demonstrate that the proposed method significantly outperforms the state-of-the-art saliency detection approaches on all test datasets.
Experimental Investigation on Self-Compacting Concrete with Waste Carbon Black

One of the vital aspects in designing self-compacting concrete (SCC) is the amount and type of filler with respect to cement and water. These have a great impact not only on fresh SCC properties (segregation, filling, fluidity, etc.) but also on its hardened properties. In this experimental study, an attempt was conducted to diminish the pores occurrence in SCC by using carbon black as a filler, which is a waste from the rubber industry. The experimental work investigates the SCC properties when crusher dust filler from the aggregate plant was partially replaced by waste carbon black. SCC mixes of two carbon black replacement ratios (2.5% and 5%) were studied to reveal its effect on the fresh and hardened properties, through various tests. The fresh properties were investigated by means of slump flow (t500), J-ring and L-box. The compressive and splitting tensile strengths tests were implemented along with the mix density evaluation to characterize the hardened properties of SCC with black carbon. It has been found that the carbon black has a useful role for the fresh properties of SCC. Indeed, the carbon black provides superior performance for the compressive strength development than crusher dust. In contrast, it slightly worsened SCC splitting tensile strength.
Viability of highly-efficient multi-horsepower line-start permanent-magnet motors

The incremental efficiency improvements achieved with induction motors have been mostly accomplished by adding material to the designs of the prior efficiency level. In order to achieve levels beyond NEMA Premium (or beyond lE3), it has been recognized that a different technology must be employed. The working groups for IEC efficiency levels have stated that inverter-fed permanent-magnet motors are the likely technology to reach lE4 levels. Other motor technologies (such as synchronous reluctance) which also require inverters for operation have also been proposed for higher motor efficiency. This paper will discuss a technology which can be utilized without requiring an inverter, and that can achieve beyond-lE4 levels of efficiency while using less active material in the motor. This discussion is based on testing of technology demonstration prototypes in the range of 30-250 HP. Capabilities as well as limitations of this technology will be discussed.
outputs Social learning analytics : five approaches Conference Item

This paper proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. The paper introduces the broad rationale for SLA by reviewing some of the key drivers that make social learning so important today. Five forms of SLA are identified, including those which are inherently social, and others which have social dimensions. The paper goes on to describe early work towards implementing these analytics on SocialLearn, an online learning space in use at the UK’s Open University, and the challenges that this is raising. This work takes an iterative approach to analytics, encouraging learners to respond to and help to shape not only the analytics but also their associated recommendations.