Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Aneurysm Occlusion Classification after the Impact of Flow Modification

SUMMARY: A new classification is proposed for cerebral aneurysms treated with any endovascular technique, for example, coiling with or without adjunctive devices, flow diversion, intrasaccular flow modifiers, or any combination of the above. Raymond-Roy Occlusion Classification is expanded with novel subgroups such as class 1 represents complete occlusion and is subdivided if a branch is integrated to, or originated from, the aneurysm sac; class 2 represents neck filling; class 3 represents incomplete occlusion with aneurysm filling as in the previous classification; and class 4 describes the immediate postoperative status after extra- or intrasaccular flow modification treatment. A new concept, “stable remodeling,” is included as class 5, which represents filling in the neck region that stays unchanged or reduced, as shown with at least 2 consecutive control angiographies, at least 6 months apart, for not <1 year, or the remodeled appearance of a dilated and/or tortuous vessel in continuation with the parent artery without sac filling.
The Arecibo Galaxy Environment Survey II: a H I view of the Abell cluster 1367 and its outskirts

We present 21 cm H i line observations of 5 × 1 deg2 centred on the local Abell cluster 1367 obtained as part of the Arecibo Galaxy Environment Survey. One hundred sources are detected (79 new H i measurements and 50 new redshifts), more than half belonging to the cluster core and its infalling region. Combining the H i data with Sloan Digital Sky Survey (SDSS) optical imaging, we show that our H i selected sample follows scaling relations similar to the ones usually observed in optically selected samples. Interestingly, all galaxies in our sample appear to have nearly the same baryon fraction independently of their size, surface brightness and luminosity. The most striking difference between H i and optically selected samples resides in their large-scale distribution: whereas optical and X-ray observations trace the cluster core very well, in H i there is almost no evidence of the presence of the cluster. Some implications on the determination of the cluster luminosity function and H i distribution for samples selected at different wavelength are also discussed.
Asymptotic Improvements to the Lower Bound of Certain Bipartite Turán Numbers

We show that there are graphs with n vertices containing no K5,5 which have about n7/4 edges, thus proving that ex(n, K5,5) ≥ (1 + o(1))n7/4. This bound gives an asymptotic improvement to the known lower bounds on ex(n, Kt, s) for t = 5 when 5 ≤ s ≤ 12, and t = 6 when 6 ≤ s ≤ 8.
N = 4 SYM on S3 with near critical chemical potentials

We study the = 4 theory at weak coupling, on a three sphere in the grand canonical ensemble with R symmetry chemical potentials. We focus attention on near critical values for the chemical potentials, above which the classical theory has no ground state. By computing a one loop effective potential for the light degrees of freedom in this regime, we show the existence of flat directions of complex dimension N, 2N and 3N for one, two and three critical chemical potentials respectively; these correspond to one half, one quarter and one-eighth BPS states becoming light respectively at the critical values. At small finite temperature we show that the chemical potentials can be continued beyond their classical limiting values to yield a deconfined metastable phase with lifetime diverging in the large N limit. Our low temperaure analysis complements the high temperature metastability found by Yamada and Yaffe. The resulting phase diagram at weak coupling bears a striking resemblance to the strong coupling phase diagram for charged AdS black holes. Our analysis also reveals subtle qualitative differences between the two regimes.
Energy exchange and wave action conservation for magnetohydrodynamic (MHD) waves in a general, slowly varying medium

Magnetohydrodynamic (MHD) waves in the solar wind and magnetosphere are propagated in a medium whose velocity is comparable to or greater than the wave velocity and which varies in both space and time. In the approximation where the scales of the time and space variation are long compared with the period and wavelength, the ray-tracing equations can be generalized and then include an additional first-order differential equation that determines the variation of frequency. In such circumstances the wave can exchange energy with the background: wave energy is not conserved. In such processes the wave action theorem shows that the wave action, defined as the ratio of the wave energy to the frequency in the local rest frame, is conserved. In this paper we discuss ray-tracing techniques and the energy exchange relation for MHD waves. We then provide a unified account of how to deal with energy transport by MHD waves in non-uniform media. The wave action theorem is derived directly from the basic MHD equations for sound waves, transverse Alfven waves, and the fast and slow magnetosonic waves. The techniques described are applied to a number of illustrative cases. These include a sound wave in a medium undergoing a uniform compression, an isotropic Alfven wave in a steady-state shear layer, and a transverse Alfven wave in a simple model of the magnetotail undergoing compression. In each case the nature and magnitude of the energy exchange between wave and background is found.
Online power auction for spectrum sharing in cognitive radio networks

In this paper, we investigate the power allocation for spectrum sharing with constraints of energy consumption in a fixed period. The proposed online power auction is designed according to the pricing discipline of non-cooperative game. Though avoiding abusing energy while interference is great at some time steps, the regret of OPA is acceptable. Numerical results showed that OPA is close to be optimal.
BP neural network MRAC applied to slip gain adjusting

Asynchronous machine with indirect vector control is very popular in industrial applications. However, it is sensitive to rotor slip gain. In this paper, model reference adaptive system combined with PI controller based on BP neural network, then Electromagnetic torque of asynchronous motor could be online estimated by model reference adaptive system, BP neural network controller could adaptively adjust the parameters according to the error between the reference model and adaptive model, then steady-state and dynamic performance of the system could achieve good performance. Basic principles and schematic diagram are described. Simulation and experiment results confirm the validity of the proposed method.
APE: End User Development for Emergency Management Training

Serious games are pedagogical tools used in many domains and considered a viable solution to professional training. Core elements for the construction of effective serious games are the Non-Player Characters (NPCs) which, depending on the quality of the Artificial Intelligence (AI), can make the training scenarios more realistic and engaging. One of the main issues with existing games concerns the limited possibility to edit their content. These tools are usually delivered as closed products with no, or minimal, customization features. The modification of the virtual environment is strongly constrained and the behavior of NPCs is fixed to a predefined set of actions. Therefore it becomes hard for trainers to adapt the training according to different requirements. In this paper we propose a solution for the customization of AIs, aimed at allow non-technical users to edit complex behavioral models through a new high-level approach. The Actors' Programming Environment (APE) has been developed on the base of a user-centered design and a preliminary evaluation was conducted with eight experts in computer science and interaction design, serving as evaluators. The results suggest that the approach is suitable for this context and might prove to be a good basis for future developments.
Fault Detection and Diagnosis Based on KPCA-LSSVM Model

Although Kernel Principle Component Analysis¿KPCA¿has been used to monitoring nonlinear processes, it is not well suited for fault diagnosis. In order to solve this problem, a new method of fault detection and diagnosis for nonlinear processes based on KPCA and Least Squares Support Vector Machine(LSSVM) is proposed. The KPCA is used to monitor faults and extract feature and LSSVM model is used to diagnose fault, LSSVM model is constructed based on nonlinear principle component scores of various known faults. The applications in TE process illustrate the efficiency of the proposed approach.
Effects of Adaptation of In vitro Rumen Culture to Garlic Oil, Nitrate, and Saponin and Their Combinations on Methanogenesis, Fermentation, and Abundances and Diversity of Microbial Populations

This study investigated the effects of garlic oil (0.25 g/L), nitrate (5 mM), and quillaja saponin (0.6 g/L), alone and in binary or ternary combinations, on methanogenesis, rumen fermentation, and abundances of select microbial populations using in vitro rumen cultures. Potential adaptation to these compounds was also examined by repeated transfers of the cultures on alternate days until day 18. All treatments except saponin alone significantly decreased methanogenesis. Ternary combinations of garlic oil, nitrate, and saponin additively/synergistically suppressed methane production by 65% at day 2 and by 40% at day 18. Feed digestion was not adversely affected by any of the treatments at day 2, but was decreased by the combinations (binary and ternary) of garlic oil with the other inhibitors at days 10 and 18. Saponin, alone or in combinations, and garlic oil alone lowered ammonia concentration at day 2, while nitrate increased ammonia concentration at days 10 and 18. Total volatile fatty acid concentration was decreased by garlic oil alone or garlic oil-saponin combination. Molar proportions of acetate and propionate were affected to different extents by the different treatments. The abundances of methanogens were similar among treatments at day 2; however, garlic oil and its combination with saponin and/or nitrate at day 10 and all treatments except saponin at day 18 significantly decreased the abundances of methanogens. All the inhibitors, either alone or in combinations, did not adversely affect the abundances of total bacteria or Ruminococcus flavefaciens. However, at day 18 the abundances of Fibrobacter succinogenes and Ruminococcus albus were lowered in the presence of garlic oil and saponin, respectively. The results suggest that garlic oil-nitrate-saponin combination (at the doses used in this study) can effectively decreases methanogenesis in the rumen, but its efficacy may decrease while inhibition to feed digestion can increase over time.
Systematic Dissection and Trajectory-Scanning Mutagenesis of the Molecular Interface That Ensures Specificity of Two-Component Signaling Pathways

Two-component signal transduction systems enable bacteria to sense and respond to a wide range of environmental stimuli. Sensor histidine kinases transmit signals to their cognate response regulators via phosphorylation. The faithful transmission of information through two-component pathways and the avoidance of unwanted cross-talk require exquisite specificity of histidine kinase-response regulator interactions to ensure that cells mount the appropriate response to external signals. To identify putative specificity-determining residues, we have analyzed amino acid coevolution in two-component proteins and identified a set of residues that can be used to rationally rewire a model signaling pathway, EnvZ-OmpR. To explore how a relatively small set of residues can dictate partner selectivity, we combined alanine-scanning mutagenesis with an approach we call trajectory-scanning mutagenesis, in which all mutational intermediates between the specificity residues of EnvZ and another kinase, RstB, were systematically examined for phosphotransfer specificity. The same approach was used for the response regulators OmpR and RstA. Collectively, the results begin to reveal the molecular mechanism by which a small set of amino acids enables an individual kinase to discriminate amongst a large set of highly-related response regulators and vice versa. Our results also suggest that the mutational trajectories taken by two-component signaling proteins following gene or pathway duplication may be constrained and subject to differential selective pressures. Only some trajectories allow both the maintenance of phosphotransfer and the avoidance of unwanted cross-talk.
Architecture and applications of the Connection Machine

The concept of data-parallel computers is explained, and their architecture of the Connection Machine (CM), which implements this approach, is described. It provides 64 K physical processing elements, millions of virtual processing elements with its virtual processor mechanism, and general-purpose, reconfigurable communications networks. The evolution of the CM architecture is examined, and the software environment, engineering and physical characteristics, and performance of the current embodiment (the CM-2) are discussed. Applications of the CM to molecular dynamics, VLSI design and circuit simulation, and computer vision are described. <<ETX>>
Time Series Classification Challenge Experiments

This paper describes a comparison of approaches for time series classification. Our comparisons included two different outlier removal methods (discords and reverse nearest neighbor), two different distance measures (Euclidean distance and dynamic time warping), and two different classification algorithms (k nearest neighbor and support vector machines). An algorithm for semi-supervised learning was evaluated as well. While dynamic time warping and support vector machines performed pretty well overall, there was no single approach that worked best for all data sets.
HIDEF: a Data Exchange Format for Information Collected in Honeypots and Honeynets

The deployment of honeypots is one of the methods used to collect data about attack trends in computer networks. The lack of a standard format for data representation makes the exchange and central- ization of data generated by different technologies difficult. This also restricts the correlation and analysis of this information. This paper presents the HIDEF (Honeypots Information and Data Exchange Format), a proposal for a format to enable the representation and exchange of data and information produced by organizations using honeypots and honeynets.
FAST: Fast Autonomous System Traceback

The defense against distributed denial of service (DDoS) attacks is one of the primary concerns on the Internet today. IP spoofing makes it difficult for the victim to determine the packet's origin. There is a need for a mechanism that could enable realtime traceback of the origins of the attacks. In this paper, we propose a novel protocol, fast autonomous system traceback (FAST) to traceback to the attack originating autonomous systems (AS). The multifold advantages of FAST include reconstruction requires just around 5 to 10 packets and reconstruction takes just a few seconds. We validate the performance through extensive simulations over the datasets obtained from traceroute.
Distributed, Robust, and Self-Organizing Bluetooth Scatternet Formation

Bluetooth is a promising low-cost low-power short-range radio technology for wireless personal area networks. The basic network unit in Bluetooth is a centralized master-slave topology named piconet. The piconets can be further interconnected to form a multi-hop ad hoc network known as a scatternet. The properties of scatternets pose new challenges for constructing an efficient topology. In this paper, we present a novel distributed approach for scatternet formation which works efficiently even when all the devices are not in range of each other. We validate the efficiency of our approach through simulations demonstrating that the scatternet formed has fast connection establishment time and O(log n) diameter for a network of n devices. For the case of all-in-range devices, our protocol achieves close to the the minimum number of piconets. Based on the implicit fault-tolerant nature of our protocol, we extend it with a self-healing mechanism to work well under mobile environments. Our simulation results indicate the robust nature of the formed scatternet when nodes join and leave arbitrarily. To the best of our knowledge, this is a first attempt that addresses scatternet formation for dynamic environments as well as when all the devices are not in communication range of each other.
Reverse engineering for Web data: from visual to semantic structures

Despite the advancement of XML, the majority of documents on the Web is still marked up with HTML for visual rendering purposes only, thus building a huge amount of legacy data. In order to facilitate querying Web based data in a way more efficient and effective than just keyword based retrieval, enriching such Web documents with both structure and semantics is necessary. We describe a novel approach to the integration of topic specific HTML documents into a repository of XML documents. In particular, we describe how topic specific HTML documents are transformed into XML documents. The proposed document transformation and semantic element tagging process utilizes document restructuring rules and minimum information about the topic in the form of concepts. For the resulting XML documents, a majority schema is derived that describes common structures among the documents in the form of a DTD. We explore and discuss different techniques, and rules for document conversion and majority schema discovery. We finally demonstrate the feasibility and effectiveness of our approach by applying it to a set of resume HTML documents gathered by a Web crawler.
Quantum Monte Carlo studies of electronic systemsR

We review our recent work on developing and applying quantum Monte Carlo (QMC) methods to electronic systems. The \special k-points" method is introduced into QMC calculations as a method for reducing \independent par-ticle" nite size eeects. We also explain our new formulation of the Coulomb interaction which virtually eliminates so-called Coulomb nite size eeects. The importance of these advances for future applications of QMC techniques to electronic systems is stressed.
Tetramer-Guided Analysis of TCR β-Chain Usage Reveals a Large Repertoire of Melan-A-Specific CD8+ T Cells in Melanoma Patients1

The assessment of the TCR repertoire expressed by tumor-specific CD8+ T lymphocytes has been hampered to date by the difficulty of targeting the analysis to lymphocytes directed against a single epitope. In the present study we have used fluorescent A2/Melan-A tetramers in conjunction with anti-CD8 and anti-TCR β-chain variable (BV) mAbs to analyze by flow cytometry the BV segment usage by Melan-A-specific CD8+ T cells in tumor-infiltrated lymph nodes (TILN) and tumor-infiltrating lymphocytes (TIL) from A2 melanoma patients. Analysis of TILN populations revealed small proportions of A2/Melan-A tetramer+ cells expressing many different BV together with over-representation of A2/Melan-A tetramer+ cells expressing certain BVs. The BV usage by A2/Melan-A tetramer+ lymphocytes in TIL was more restricted than that in TILN. Moreover, the predominant BV segments were quite distinct in populations derived from different patients. A2/Melan-A tetramer+ cells expressing the dominant BVs found in TILN could also be found in the corresponding peptide-stimulated autologous PBMC, although A2/Melan-A tetramer+ lymphocytes expressing additional BVs were also identified. Together, these results suggest that a large and diverse repertoire of Melan-A-specific T cells using different BV TCR segments is available in A2 melanoma patients.
Autonomous Navigation in Dynamic Environments with Reinforcement Learning and Heuristic

Researchers have created machines which operate autonomously in complex and changing environments. An important problem that has been widely studied is that of autonomous navigation systems, through which attempts have been made to create mechanisms with their own decision making in complex environments. Ideally, an autonomous navigation agent must have an ability to learn while working in its environment. This acquisition of knowledge may be based on a history of actions taken to make decisions without the guidance of a tutor. The performance of the agent may depend on its ability to learn and adapt. This paper presents a reinforcement learning-based method applied to a navigation problem. Using a Q-Learning algorithm, we propose a model to provide autonomous navigation with a policy modified by information from a greedy heuristic. The model aims to improve the performance of the agent with regard to its navigation task.
Secure inter cloud data migration

Cloud computing services are becoming more and more popular. However, the high concentration of data and services on the clouds make them attractive targets for various security attacks, including DoS, data theft, and privacy attacks. Additionally, cloud providers may fail to comply with service level agreement in terms of performance, availability, and security guarantees. Therefore, it is of paramount importance to have secure and efficient mechanisms that enable users to transparently copy and move their data from one provider to another. In this paper, we explore the state-of-the-art inter-cloud migration techniques and identify the potential security threats in the scope of Hadoop Distributed File System HDFS. We propose an inter-cloud data migration mechanism that offers better security guarantees and faster response time for migrating large scale data files in cloud database management systems. The performance of the proposed approach is validated by measuring its impact on response time and throughput, and comparing the performance to that of other techniques in the literature. The results show that our approach significantly improves the performance of HDFS and outperforms its counterparts.
Hybrid Monitoring of Offshore Compression Systems

Abstract In this work a hybrid methodology based on statistical approach and phenomenological modeling was developed aiming the monitoring of the performance of compression equipment in an offshore oil platform. A rigorous model was employed in order to estimate thermodynamic based values of the performance of the compression system, given by the polytropic efficiency and head. Residuals were generated by comparing the model values with the ones which were calculated from manufacturer's curves using process data (suction and discharge pressures and temperatures, turbine rotation and suction flow). Even though the monitoring technique developed is essentially multivariable and dynamic, the results are displayed using typical univariate process control charts, providing a friendly interface for the operator and allowing the clear detection of process faults.
When and why mimicry is facilitated and attenuated

Although people tend to mimic others automatically, mimicry is facilitated or attenuated depending on the specific context. In the current paper, the authors discuss when mimicry is facilitated and attenuated depending on characteristics of situations, targets, and observers. On the basis of the review, the authors propose a new model – the Associated Reactions to Actions in Context model (ARAC) – to explain why and when mimicry is facilitated and attenuated. ARAC proposes that when people observe an action, reaction-to-action neurons fire. Which reaction is elicited depends on the (learned or innate) association with an action in that context. Thus, when mimicry is rewarding in a specific context, this response is facilitated. When mimicry is damaging, this response is attenuated, and another reaction may be facilitated instead. The authors discuss the added value of the ARAC model compared to other models explaining the elicitation of behavioral reactions