Miracle-dz/UniFAR-FTUs huggingface dataset:
IVM‐based parallel branch‐and‐bound using hierarchical work stealing on multi‐GPU systems

Tree‐based exploratory methods, like Branch‐and‐Bound (B&B) algorithms, are highly irregular applications which makes their design and implementation on graphics processing unit (GPU) challenging. In this paper, we present a multi‐GPU B&B algorithm for solving large permutation‐based combinatorial optimization problems. To tackle the problem of the irregular workload, we propose a hierarchical work stealing (WS) strategy that balances the workload inside the GPU and between different GPUs and CPU cores. Our B&B is based on an Integer‐Vector‐Matrix data structure instead of a pool of permutations, and work units exchanged are intervals of factoradics instead of sets of nodes. Two variants of the algorithm, using the same hierarchical WS strategy, are proposed: one for combinatorial optimization problems where the evaluation of nodes is costly and one for fine‐grained problems. The latter variant uses a new hypercube‐based WS strategy and a trigger mechanism to balance the work load inside the GPU. The proposed approach has been extensively experimented using the flowshop scheduling, the n‐queens and the asymmetric travelling salesman problems as test‐cases. The reported results show that the proposed hierarchical WS mechanism is capable of handling fine and coarse‐grained types of workloads efficiently, reaching near‐linear speed‐up on up to four GPUs for a set of ten flowshop instances and large instances of fine‐grained problems. Copyright © 2016 John Wiley & Sons, Ltd.
The Spatial Scale of Population Fluctuations and Quasi‐Extinction Risk

Using a spatially homogeneous population model with migration (random individual dispersal) and spatially autocorrelated environmental noise, we show how migration and local density regulation affect the spatial scale of fluctuations in the log of population sizes as well as the 1‐yr differences in these. The difference between the squares of these two spatial scales of population fluctuations does not depend on the spatial scale of the noise but only on migration rate and strength of local density regulation. We also show how migration, local density regulation, and spatially correlated environmental noise affect the realized population process at a specific location. As the migration increases, the realized local density regulation and the expected population size increase, while the realized environmental noise decreases. This approach also enables us to analyze the dynamics of the total population size within quadrats of different sizes. The risk of local quasi extinction is strongly reduced by increasing quadrat size or migration rate, while an increase in environmental stochasticity or spatial correlation in the environmental noise increases the risk of quasi extinction.
Architecture Based on Dynamic Graphs for the Dynamic Reconfiguration of Farms of Computers

In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor, in a nonconcurrent form instead of being executed concurrently in a set of processors working and communicating through a network. This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies. Keywords— Dynamic network topology, resource and task allocation, parallel computing, heterogeneous computing, dynamic reconfiguration
Evaluation of relationship of inhaler technique with asthma control and quality of life

Introduction: There is a need to assess erroneous steps in the use of inhaler devices in people who have asthma. The objectives of this study were to assess the inhaler technique in patients who have asthma, the factors affecting improper technique, and the association of inhaler use with asthma control, hospital visits, and quality of life (QOL) of patients who have asthma. Methods: It was an observational, prospective, cross-sectional study conducted on patients with bronchial asthma. Patients were enrolled in the study; their history was recorded and they were asked to use inhaler in the presence of an investigator and the technique was scored. Asthma control and QOL of patients were assessed using asthma control questionnaire and Mini Asthma QOL questionnaire. Results: A total of 330 patients completed the study. Nearly 36.6% of the patients performed the steps incorrectly. Breathing normally for 30–60 min postinhaler use was the most common step done incorrectly. Patients with poorly controlled asthma (P < 0.001) and those with predicted forced expiratory volume at 1 s <70% performed the steps erroneously (P < 0.001). Conclusion: All patients, particularly those above 40 years, should be given proper instructions regarding inhaler use to obtain therapeutic advantage.
FCH domain only-2 organizes clathrin-coated structures and interacts with Disabled-2 for low-density lipoprotein receptor endocytosis

The clathrin adaptor Disabled-2 (Dab2) interacts with the F-BAR protein FCH domain only-2 (FCHO2), and this interaction is necessary for Dab2 function when AP2 levels are low. FCHO2 regulates the size of clathrin structures and plays a role in receptor recruitment. Our results indicate that FCHO2 is not essential for coated pit initiation but regulates coated pit size and function.
Mathematizing C++ concurrency

Shared-memory concurrency in C and C++ is pervasive in systems programming, but has long been poorly defined. This motivated an ongoing shared effort by the standards committees to specify concurrent behaviour in the next versions of both languages. They aim to provide strong guarantees for race-free programs, together with new (but subtle) relaxed-memory atomic primitives for high-performance concurrent code. However, the current draft standards, while the result of careful deliberation, are not yet clear and rigorous definitions, and harbour substantial problems in their details. In this paper we establish a mathematical (yet readable) semantics for C++ concurrency. We aim to capture the intent of the current (`Final Committee') Draft as closely as possible, but discuss changes that fix many of its problems. We prove that a proposed x86 implementation of the concurrency primitives is correct with respect to the x86-TSO model, and describe our Cppmem tool for exploring the semantics of examples, using code generated from our Isabelle/HOL definitions. Having already motivated changes to the draft standard, this work will aid discussion of any further changes, provide a correctness condition for compilers, and give a much-needed basis for analysis and verification of concurrent C and C++ programs.
Valuing and Hedging American Put Options Using Neural Networks

We use a neural network to non-parametrically estimate the market valuation function for American put options with real data. The neural network valuation function is twice di erentiable, and provides an instantaneous approximation of the American put option using a set of multiple state variables. We use the neural network valuation function to form hedged portfolios for American put options against changes in the stock price, the delta of the stock price, and interest rate.
Learning Personalized Query Modifications

The continuous development of the Internet has resulted in an exponential increase in the amount of available information. A popular way to access this information is by submitting queries to a search engine which retrieves a set of documents. However, search engines do not consider the specific needs of every user and they retrieve the same results for everyone. This suggests the necessity to create a profile that incorporates the search preferences of every user. We present an intelligent system that is capable of learning the search profile of a particular user given a set of queries. We represent the search profile with a probabilistic network that incorporates semantic information and create and implement a gradient-based learning algorithm to update the profile. The ultimate goal of the system is to modify original queries to improve the degree of relevance between the user’s search interests and the retrieved documents. The proposed system is a client-side application that is dependent on the search engine. We demonstrate the system by learning a search profile that is used to suggest query modifications within a specific domain of interest.
An iterative soft decision based adaptive K-best decoder without SNR estimation

This paper presents an iterative soft decision based adaptive K-best multiple-input-multiple-output (MIMO) decoding algorithm. It has the flexibility of changing the list size, K with respect to the channel condition, although the accurate measurement of signal to noise ratio (SNR) is not required. Moreover, the concept of iterative soft decision based lattice reduction (LR)-aided minimum mean square error (MMSE) extended K-best decoder is applied instead of conventional hard decision based K-best algorithm to reduce computational complexity to a great extent It is found that the ratio of the minimum path metric to the second minimum can provide reliable estimation of channel condition. Hence, in the proposed algorithm, K is changed adaptively with respect to the ratio. Using this method with less number of K, we can obtain similar performance compared to the conventional LR-aided K-best algorithm operating with maximum list size of 64. Comparing to the fourth iteration of iterative soft decision based least sphere decoding (LSD), the proposed method with less K achieves 1.6 dB improvement at the bit error rate (BER) of 10-6. Therefore, similar performance can be obtained by the proposed adaptive K-best algorithm with less computational complexity of the tree search decoder.
Challenges in the development of magnetic particles for therapeutic applications

Certain iron-based particle formulations have useful magnetic properties that, when combined with low toxicity and desirable pharmacokinetics, encourage their development for therapeutic applications. This mini-review begins with background information on magnetic particle use as MRI contrast agents and the influence of material size on pharmacokinetics and tissue penetration. Therapeutic investigations, including (1) the loading of bioactive materials, (2) the use of stationary, high-gradient (HG) magnetic fields to concentrate magnetic particles in tissues or to separate material bound to the particles from the body, and (3) the application of high power alternating magnetic fields (AMF) to generate heat in magnetic particles for hyperthermic therapeutic applications are then surveyed. Attention is directed mainly to cancer treatment, as selective distribution to tumors is well-suited to particulate approaches and has been a focus of most development efforts. While magnetic particles have been explored for several decades, their use in therapeutic products remains minimal; a discussion of future directions and potential ways to better leverage magnetic properties and to integrate their use into therapeutic regimens is discussed.
Industrial Robot : An International Journal Rao-Blackwellized visual SLAM for small UAVs with vehicle model partition

Purpose – The purpose of this paper is to present a Rao–Blackwellized particle filter (RBPF) approach for the visual simultaneous localization and mapping (SLAM) of small unmanned aerial vehicles (UAVs). Design/methodology/approach – Measurements from inertial measurement unit, barometric altimeter and monocular camera are fused to estimate the state of the vehicle while building a feature map. In this SLAM framework, an extra factorization method is proposed to partition the vehicle model into subspaces as the internal and external states. The internal state is estimated by an extended Kalman filter (EKF). A particle filter is employed for the external state estimation and parallel EKFs are for the map management. Findings – Simulation results indicate that the proposed approach is more stable and accurate than other existing marginalized particle filter-based SLAM algorithms. Experiments are also carried out to verify the effectiveness of this SLAM method by comparing with a referential global positioning system/inertial navigation system. Originality/value – The main contribution of this paper is the theoretical derivation and experimental application of the Rao–Blackwellized visual SLAM algorithm with vehicle model partition for small UAVs.
Ensemble-based Active Learning for Parse Selection

Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to be manually annotated. This can be very expensive, especially when skilled annotators are required. Active learning (AL) promises to help reduce this annotation cost. Within the complex domain of HPSG parse selection, we show that ideas from ensemble learning can help further reduce the cost of annotation. Our main results show that at times, an ensemble model trained with randomly sampled examples can outperform a single model trained using AL. However, converting the single-model AL method into an ensemble-based AL method shows that even this much stronger baseline model can be improved upon. Our best results show a reduction in annotation cost compared with single-model random sampling.
Penetration behavior of chemical grouting considering ground uncertainty

The chemical grouting is one type of ground-improvement methods. It injects liquid consolidation material into the gaps of a soft sandy ground. It is mainly used for improving a stable ground, such as by preventing liquefaction and increasing the strength of the ground. Chemical grouting has been successfully applied at many construction sites; however, the behavior of the chemical solution being injected into the ground is unclear. Furthermore, because the ground involves uncertainty, it is difficult to determine the penetration range of the chemicals (grouting materials). In this study, the authors carry out a seepage flow analysis of a chemical solution for a ground requiring improvement due to uncertainty. They then compare the difference in the behavior of the chemical solution between the case in which the ground is assumed to be heterogeneous and that in which it is assumed to be homogeneous.
Inelastic deformation of highly aligned dry-spun thermoplastic polyurethane elastomer microfibres

The present study focuses on the fabrication and mechanical responses of highly aligned thermoplastic polyurethane microfibres. A facile dry spinning assisted by an electrical field technique was used to fabricate these microfibres. The surface morphology of the microfibres were inspected under a scanning electron microscope, while their mechanical responses were probed using universal tensile machine. The mechanical tests include uniaxial monotonic, cyclic with increasing maximum strain and relaxation tensile tests using two different strain rates: 0.1 s−1 and 0.001 s−1. According to the surface morphology study, the fibres are highly aligned with the diameter of 2.80 ± 0.06 μm and without beads. As for mechanical tests, the fibres show inelastic mechanical responses such as hysteresis, stress-softening, stress relaxation and residual strain. Except for its nearly linear stress-strain response before reaching ultimate tensile strength, it appears that the thermoplastic polyurethane elastomer microfibres exhibit general features commonly found in bulk elastomers. The findings in this study are expected to provide a basis for the modelling of the mechanical behaviours of elastomer fibres in the future.
Reference-free structural health monitoring for detecting delamination in composite plates

This paper presents a new methodology that allows detection of delamination in a single wave propagation path without using prior baseline data or a predetermined decision boundary. This study shows that, if delamination exists along a wave propagation path, the first arrival anti-symmetric mode (A0) is followed by another A0 mode reflected off from the “inside” delamination. Unlike other conventional techniques, the proposed technique takes advantage of this A0 mode reflected off from the inside delamination to instantly detect the existence of delamination. First, Lamb wave signals are measured in a pitch-catch mode using a dual PZT composed of concentric ring and disk PZTs for excitation and two circular PZTs for sensing. Here, the dual PZT actuator is used to extract only the A0 mode at any desired driving frequency. Then, the response time signals are measured by the two circular PZTs, and the damage sensitive feature, which is the A0 mode reflected off from the delamination, is extracted. Because the proposed technique does not require baseline signals during the entire delamination detection process, it has been demonstrated that robust delamination detection can be achieved even under varying temperature conditions.
Multi-Hop Distance Estimation: How Far are You?

Several access control systems are based on the users’ physical location/proximity to the access point. DistanceBounding (DB) protocols constitute a classical solution to calculate the distance between a trusted verifier (e.g., an access point) and an untrusted prover (e.g., a pervasive device). The main limitation of DB is that the prover and the verifier need to lie in each other’s communication range. In this paper, we introduce the concept of Multi-Hop Distance-Estimation (MHDE) protocols, which enable a verifier to authenticate a possibly far-away prover and estimate its distance to this prover, when they are not in the communication range of each other, using an ad-hoc network of pervasive devices. More precisely, our contributions are three-fold, since we provide: (1) a formal definition for MHDE; (2) a threat model for MHDE that considers a powerful and distributed adversary; and (3) implementation of MHDE protocols with different settings. Additionally, we demonstrate our protocol to be secure in the considered threat model, and we provide a performance analysis regarding the accuracy of the distance estimation and the tolerance of limited mobility of the nodes. The results are promising in order to adopt MHDE in a distributed setting.
Feature Optimization for Long-Range Visual Homing in Changing Environments

This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.
AT-Angle: A distributed method for localization using angles in sensor networks

Determining where a given sensor is physically located is a challenging issue. In this paper, we address the localization problem where, initially, a certain number of sensors called anchors are aware of their positions. Our goal is to localize all sensors with high accuracy, while using a limited number of anchors. So, we focus on localization techniques based on angle of arrival information between neighbor nodes. This paper proposes an original angle-based localization technique, called AT-Angle, which allows to verify two important properties: first, a sensor node can eliminate wrong received information about its position; second, it deduces if its estimated position is closed to its real position. In this last case, the sensor node becomes an estimated anchor and contributes to the positioning of others nodes. Simulations show that AT-Angle achieves good precision for located nodes despite the introduction of position errors and the small number of anchors.
Methamphetamine induces the release of endothelin

Methamphetamine is a potent psychostimulant drug of abuse that increases release and blocks reuptake of dopamine, producing intense euphoria, factors that may contribute to its widespread abuse. It also produces severe neurotoxicity resulting from oxidative stress, DNA damage, blood–brain barrier disruption, microgliosis, and mitochondrial dysfunction. Intracerebral hemorrhagic and ischemic stroke have been reported after intravenous and oral abuse of methamphetamine. Several studies have shown that methamphetamine causes vasoconstriction of vessels. This study investigates the effect of methamphetamine on endothelin‐1 (ET‐1) release in mouse brain endothelial cells by ELISA. ET‐1 transcription as well as endothelial nitric oxide synthase (eNOS) activation and transcription were measured following methamphetamine treatment. We also examine the effect of methamphetamine on isolated cerebral arteriolar vessels from C57BL/6 mice. Penetrating middle cerebral arterioles were cannulated at both ends with a micropipette system. Methamphetamine was applied extraluminally, and the vascular response was investigated. Methamphetamine treatment of mouse brain endothelial cells resulted in ET‐1 release and a transient increase in ET‐1 message. The activity and transcription of eNOS were only slightly enhanced after 24 hr of treatment with methamphetamine. In addition, methamphetamine caused significant vasoconstriction of isolated mouse intracerebral arterioles. The vasoconstrictive effect of methamphetamine was attenuated by coapplication of the endothelin receptor antagonist PD145065. These findings suggest that vasoconstriction induced by methamphetamine is mediated through the endothelin receptor and may involve an endothelin‐dependent pathway. © 2015 Wiley Periodicals, Inc.