Miracle-dz/UniFAR-FTUs huggingface dataset:
Fragmentation-aware Routing, Space, and Spectrum Assignment using Ant Colony Optimization

Space division multiplexing (SDM) allows for capacity expansion in the Elastic Optical Network (EON) by providing different spatial paths in the same link for the lightpaths. Thus, in addition to the Routing and Spectrum Assignment (RSA) problem, the Space sub-problem must be tackled during the allocation of resources in an SDM-EON environment. In this work, we propose a fully distributed provisioning algorithm based on the Ant Colony optimization (ACO) metaheuristics with a crankback mechanism to solve the Routing, Space, and Spectrum Assignment (RSSA) problem. The proposed algorithm can mitigate the blocking by taking into consideration the fragmentation caused by the dynamic establishment and release of lightpaths. The obtained simulation results demonstrate the effectiveness of the proposed approach when compared to fragmentation-aware algorithms that rely on the OSPF-TE protocol to gather the network state information while maintaining much lower levels of control overhead.
Comparison of deep and shallow graph representation learning algorithms for detecting modules in molecular networks

Graphs provide ubiquitous powerful representations of interacting components in many complex systems. In molecular biology, graphs are used to represent interactions between molecular components; for example, protein-protein interactions represent interactions between proteins, while gene regulatory networks describe interactions between transcription factor proteins and genes. A common property of graphs for complex systems, including molecular networks, is the presence of community structures or modules, defined by groups of densely interacting nodes. In protein-protein interaction networks, such modules often correspond to key biological processes needed for cells to accomplish different tasks [1]. Disruptions to module connectivity have been implicated in many diseases [13]. Therefore, the accurate detection of these modules is a key problem in the analysis of molecular networks [14]. Graph representation learning [15], which aims to embed graph nodes in a d-dimensional space (Fig 1), offers a powerful framework for performing machine learning tasks on graphs, including clustering. Both deep and shallow graph representation algorithms exist; however, deep representation learning methods have been designed and tested on social networks, citation networks and recommendation systems. Therefore, it is unclear if deep representation learning methods are beneficial for module detection of molecular networks. In this work, we compare several state-of-the-art shallow and deep learning frameworks on both real molecular networks and synthetic benchmark networks.
The Acquisition and Application of ECG in Wearable Devices

Electrocardiogram (ECG) is a technique that captures electric signals existing in the body. After the amplification, a waveform representing heart functions would be generated for observations. Based on the analysis of its waveform, ECG played an important role in cardiac diagnosis. But the formal ECG is time-consuming, which indicates it may not be appliable in emergencies. As such, ECG on the wearable device is the best solution for diagnoses in emergencies that could generate the waveform as soon as possible or even warn the patient before the emergency. But the ECG needs to match a standard of accuracy that any tiny abnormal waveform may result in miscellaneous diseases. This requires a clear signal captured by ECG and lowers the noise gained in the amplification circuit. With the improvement in the technology, many types of wearable ECG devices appeared in the market with their own identity. This paper focused on certain techniques and the applicability of the device. Specifically, the ECG equipped on the wearable devices was introduced here from the perspective of the waveform, circuit amplifier, and current application. This work also gave an in-depth discussion about these techniques to provide an insight into the development of the wearable ECG.
Phase Detection Methods for Alzheimer's disease Based on Improved Convolutional Neural Network Fine-tuning

Alzheimer's disease (AD) is a prominent neurodegenerative disease that can cause memory loss and cognitive impairment. Accurate early diagnosis greatly reduces treatment costs and slows progression. Traditional detection methods are complex, expensive, and less accurate. In this study, an Alzheimer's phase detection method based on improved convolution neural network fine-tuning was proposed to diagnose the severity of Alzheimer's disease. The method was trained and tested on Alzheimer's Dataset (4 classes of Images), which classified the patient condition into four stages: MildDemented, VeryMildDemented, NonDemented, and ModerateDemeneted. According to the research results, the classification accuracy on the test set can reach 99.30%. Under the Weighted Average evaluation index, the precision rate of the model is 99.08%, the recall rate is 99.08%, and the F1 value of the model is 99.08%
The Symmetrised Maxwell-Garnett Approximation for Magneto-Optical Spectra of Ferromagnetic Composites

We develop the symmetrised Maxwell-Garnett (SMG) approximation for magneto-optical spectra calculations by introducing an average over two following random units: inclusion of A coated by shell of B and inclusion of B coated by shell of A. Thus the symmetrised Maxwell-Garnett approach is the modified version of both Maxwell-Garnett and Bruggeman theories for arbitrary values of ferromagnetic volume fraction. The calculated spectra of metal-metal granular alloys in Bruggeman and SMG approaches are closed to each other, but this is not the case for metal-insulator composites, especially when close to percolation threshold. It is shown that magneto-optical response of the ferromagnetic composites is extremely sensitive to the value of the percolation threshold and hence to the microstructures of the composites.
Disturbance decoupling and robustness of stability

The problem of finding a feedback compensator to cancel the effect of disturbances on the system output is known as disturbance decoupling. In this paper we investigate the interaction of disturbance decoupling requirement with the robustness of closed-loop stability in the sense of normalized coprime factor perturbations. This disturbance decoupling and the robust stabilization requirements are expressed in terms of the subspace-valued functions associated with the plant and the controller and an upper bound on robustness of stability imposed by the disturbance decoupling requirement is derived. This is then compared with the actual robustness of stability that can be achieved by a solution of the disturbance decoupling problem under some simplifying assumptions. Copyright © 2000 John Wiley & Sons, Ltd.
Limit theorems for pathwise average cost per unit time problems for controlled queues in heavy traffic

We treat the average cost per unit time problem for controlled and uncontrolled open queueing networks in heavy traffic. The usual heavy traffic theorems prove that a suitably scaled and normalized sequence of queue length processes converges weakly in the Skorohod topology to a certain reflected diffusion, as the traffic intensity goes to unity. The Skorohod topology essentially discounts the distant future, and the usual weak convergence methods are not well suited for dealing with the average cost problem over an infinite time interval. We provide a particularly strong approach to this problem via a “functional occupation measure” method. A fairly general cost functional is used. For the uncontrolled problem, it is shown that the average pathwise (i.e., no mathematical expectation is used) cost per unit time converges in probability to an ergodic cost for the limit reflected diffusion, no matter how the time goes to infinity or the traffic intensity goes to unity. The methods which are introduced are n.
Mapping tori with first Betti number at least two

We show that given a ﬁnitely presented group G with β 1 ( G ) ≥ 2 which is a mapping torus Γ θ for Γ a ﬁnitely generated group and θ an automorphism of Γ then if the Alexander polynomial of G is non-constant, we can take β 1 (Γ) to be arbitrarily large. We give a range of applications and examples, such as any group G with β 1 ( G ) ≥ 2 that is F n -by- Z for F n the non-abelian free group of rank n is also F m -by- Z for inﬁnitely many m . We also examine 3-manifold groups where we show that a ﬁnitely generated subgroup cannot be conjugate to a proper subgroup of itself.
Statistical Mid-Level Features for Building-up Area Extraction From Full Polarimetric SAR Imagery

This paper addresses the problem of designing statistical features for the extraction of building-up areas (BAs) from highresolution polarimetric synthetic aperture radar (PolSAR) imagery. The idea is to represent a building-up area by the distribution of its mid-level components, called intermediates, which are statistical patterns unsupervisedly learnt from PolSAR images. More precisely, by analyzing the structural properties and the polarimetric characteristics exhibited in various terrain types, we propose two kinds of midlevel features for small regions: the cluster based statistical feature (CSF) and the scattering mechanism based statistical feature (SMSF). In detail, for the CSF, the intermediates are the K-mean clusters with Wishart distance of the PolSAR images; for the SMSF, the intermediates are the scattering mechanism categories obtained by relying on a four-component decomposition with deorientation of the PolSAR images. In contrast with existing features for describing BAs, the proposed features, i.e., CSF and SMSF, capture more complex context information of BAs. We compare the proposed features with those based on the Gaussian Markov random field (GMRF) models, which have been proven to be suitable for BAs mapping. Experimental results on RADARSAT-2 datasets demonstrate the effectiveness of the proposed features.
Determination of single-sampling-attribute plans based on membership functions

Single-sampling-attribute plans which make the producer's risk less than or equal to α (that is,  α) and the consumer's risk less than or equal to β (that is, β) are called exact sampling plans. In using exact sampling plans, however, cases often arise in which large sample size is needlessly sought. A minimax criterion which relaxes the conditions on the risks for reducing the sample size was. introduced by Fujino and Okuno. This paper presents a design procedure for relaxing the conditions on the risks by the membership functions used in fuzzy methodologies. The proposed procedure is general because it includes sampling plans based on the minimax criterion and exact sampling plans in the special. cases.
Robust Discrimination between Single Gold Nanoparticles and Their Dimers in Aqueous Solution for Ultrasensitive Homogeneous Bioassays

We propose a robust method to distinguish isolated single gold nanoparticles (AuNP monomers) and their dimers under Brownian motion, a key for ultrasensitive homogeneous bioassays, including AuNP sandwich assays. To detect dimers and distinguish them from a larger number of monomers in aqueous solution, single-particle polarization microscopy was performed. For the accurate detection of individual particles, the optical anisotropy and rotational diffusion time are measured because a dimer is much more anisotropic than the nearly spherical monomer and the rotational diffusion time of a dimer is four times that of a monomer. By employing an autocorrelation analysis, we defined a measure of distinguishing that simultaneously enables high detection probability and low error probability. The detection platform offers homogeneous DNA hybridization assays and immunoassays at the subpicomolar level.
Poisson-distribution-based approach for salient region detection

Attention is given to the behavioural and cognitive process of selectively concentrating on one object in an image while ignoring the others. Attention-grabbing parts of the visual field are inspected with great keenness. Owing to the limited capacity of the visual system, the retina cannot process everything that falls on it. Instead, the brain relies on attention to bring salient details into focus and filter out background clutter. Salient region detection deals with finding those regions in an image that gain the viewer's attention most. An approach is proposed for salient region detection using the Poisson distribution. The proposed approach does not require any prior training and has been evaluated on the MSRA dataset. The performance is consistent in terms of recall, precision and execution time.
Enhancementofthe immune responseand protection induced by probiotic lactic acid bacteria against furunculosis in rainbow trout (Oncorhynchusmykiss )

We analysed the effect of probiotic strains on the cellular and humoral immune responses of rainbow trout (Oncorhynchus mykiss), and their capacity to prevent furunculosis during a challenge trial. Probiotic strains (Lactococcus lactis ssp. lactis CLFP 100, Leuconostoc mesenteroides CLFP 196, and Lactobacillus sakei CLFP 202) were administered orally to fish for 2 weeks at 10 CFU g 1 of feed. In comparison to untreated control fish, the phagocytic activity of head kidney leukocytes and the alternative complement activity in serum were significantly greater in all probiotic groups at the end of the second week. With the exception of the group fed with Lactobacillus sakei, superoxide anion production was also significantly increased in the probiotic groups. Analysis of lysozyme activity did not exhibit any significant difference in the probiotic and control groups. Fifteen days after the start of the probiotic feeding, fish were challenged with Aeromonas salmonicida ssp. salmonicida. The fish supplemented with probiotics exhibited survival rates ranging from 97.8% to 100%, whereas survival was 65.6% in fish not treated with the probiotics. These results demonstrate that probiotic supplementation to fish can reduce the severity of furunculosis, and suggest that this reduction may be associated with enhanced humoral and cellular immune response.
Neumann Fixed Boundary Regularity for An Elliptic Free Boundary Problem

We examine the regularity properties of solutions to an elliptic free boundary problem near a Neumann fixed boundary. Consider a nonnegative function u, defined variationally, which is harmonic where it is positive and satisfies a gradient jump condition weakly along the free boundary ∂ {u > 0}. Our main result is that u is Lipschitz continuous. Additionally, we prove various basic properties of such a minimizer near a portion of the fixed boundary on which weakly. Our results include up-to-the boundary gradient estimates on harmonic functions with Neumann boundary conditions on convex domains, which have independent interest.
Improved lattice boltzmann without parasitic currents for Rayleigh-Taylor instability

Over the last decade the Lattice Boltzmann Method (LBM) has gained significant interest as a numerical solver for multiphase flows. However most of the LB variants proposed to date are still faced with discreteness artifacts in the form of spurious currents around fluid-fluid interfaces. In the recent past, Lee et al. have proposed a new LB scheme, based on a higher order differencing of the non-ideal forces, which appears to virtually free of spurious currents for a number of representative situations. In this paper, we analyze the Lee method and show that, although strictly speaking, it lacks exact mass conservation, in actual simulations, the mass-breaking terms exhibit a self-stabilizing dynamics which leads to their disappearance in the long-term evolution. This property is specifically demonstrated for the case of a moving droplet at low-Weber number, and contrasted with the behaviour of the Shan-Chen model. Furthermore, the Lee scheme is for the first time applied to the problem of gravity-driven Rayleigh-Taylor instability. Direct comparison with literature data for different values of the Reynolds number, shows again satisfactory agreement. A grid-sensitivity study shows that, while large grids are required to converge the fine-scale details, the large-scale features of the flow settle-down at relatively low resolution. We conclude that the Lee method provides a viable technique for the simulation of Rayleigh-Taylor instabilities on a significant parameter range of Reynolds and Weber numbers.
LINE-PROFILE VARIATIONS OF LAMBDA ERIDANI IN EMISSION AND QUIESCENCE

The line-profile variations (lpv) of He I lambda-6678 in the Be star Lambda Eridani were studied from 1987 to 1992, which covered three quiescent and three emission epochs. The lpv cover a range of ± 480 km s-1 during emission but are limited to ± 380 km s-1 during quiescence. The extension of lpv to higher velocities during emission phases and the detection of identical periods of 17 and 8.5 hours (or their aliases) in both quiescence and emission -- possibly even in the extreme blue wing of the line during emission -- are consistent with the extistence of nonradial pulsations (nrp) in an accelerated equatorial region. A period of 17 hours with its first overtone implies that the surface variations are not simply sinusoidal.
Mathematical models of blood flow in the arterial network

Mathematical models of blood circulation in the human arterial network are examined in the paper. In particular, a complete two–dimensional model is proposed in the hypothesis of gradually varied flow. Vessels are considered as elastic and blood is considered as a Newtonian fluid in laminar flow. The results are compared both with those of a two–dimensional model where the radial velocity component is neglected and with those of a one–dimensional model similar to others previously proposed. The comparisons show differences due to the effect of radial convection terms in the first case, and to the more correct evaluation of resistance and longitudinal convection terms in the second case.
Experimental validation of bidirectional reflection and transmission distribution measurements of specular and scattering materials

The development of advanced materials for facades aims to achieve higher energy efficiency of buildings. Successful application of these materials depends on the availability of reliable characterization data. While data derived from integrated measurements of transmission and reflection is widely available, it does not allow to characterize the angular dependence of the performance of such materials. The Bidirectional Reflection-Transmission Distribution (BRTD) can be measured by commercially available Gonio-Photometers and, complimenting integrated transmittance and reflectance, allows the assessment of facade materials and thus supports both their development and application. Validation of the obtained data is crucial to back these measurements. Integration of validation procedures into the operation of a characterization laboratory allowing a well-defined approach to quality control is presented for a range of typical material and sample types: * consistency checks of measurement data * cross-checking of integrated material properties derived from BRTD data with integrating sphere measurements * round-robin comparison between laboratories using comparable devices The results of of these first measurements are discussed. Potential to further improve the availability of reliable angular resolved characterization data for the building sector is identified.
Computer Simulation of a Constant Velocity Contouring System Using XY Surface Motor

Two dimensional linear (surface) motors are in use for industrial applications that require positioning with more degrees of mechanical freedom. The x-y surface motor, obtained by combining two variable reluctance, permanent magnet excited synchronous (hybrid) linear motors, can travel in any direction of the x-y plane. The computer simulation of the constant velocity contouring system using such kind of motor is performed by a coupled circuit-field mathematic model. The utilized simulation method allows a wide range of design variables to be evaluated without prototyping the contouring system. Cite as: Szabó, L. ; Viorel, I.A. ; Kovács, Z. : Computer Simulation of a Constant Velocity Contouring System Using x-y Surface Motor, Proceedings of the International Conference on Power Conversion & Intelligent Motion (PCIM), Nürnberg, 1995, vol. Intelligent Motion, pp. 375-384 See attached the scan of the paper
Correction of Phase Aberrations in Medical Ultrasound Images Using Signal Redundancy

The pulse-echo technique has been widely used in medical ultrasound imaging. This technique uses an array of transducer elements to transmit a focused beam into the body, and each element then becomes a receiver to collect the echoes. The received echoes from each element are dynamically focused to form an image. Focusing on transmission and reception is performed assuming that the wave propagation speed inside the body is the same everywhere. Unfortunately, the speed inside the body is not constant; it varies from 1470 m/s to greater than 1600 m/s. This speed variation will result in increased side lobes and degraded lateral resolution. Aberration phenomena and their extent in tissue have been evaluated in many works (O'Donnell & Flax 1988; Zhu & Steinberg, 1992; Shmulewitz et al., 1993; Robinson et al., 1994; Hinkelman et al., 1998). The degradation might be tolerable if the frequency is not very high and the aperture size of the array is not very large. However, higher frequencies and larger apertures have been used to improve lateral resolution of ultrasound images. But the resolution improvement cannot be achieved beyond a certain limit, because both larger aperture and higher frequency make the system more sensitive to propagation velocity variations in the body. For example, the four transverse abdominal scan images shown in the first row of Fig.1 were formed with a 64-element linear array using four different aperture sizes (9 mm, 12 mm, 18 mm, and 27 mm) to form each single beam in the image. The array pitch was 1.0 mm and the pulse had a 3.5 MHz centre frequency and 2 MHz bandwidth. The Superior-Mesenteric-Artery (SMA) and the Aorta (A) are the main objects in these images. Because of the shape of the rectus muscles (speed ~ 1580 m/s) and the fat layers (speed ~ 1450 m/s) at this position, the distortions caused by phase aberration in these images can be easily seen. In the 9-mm aperture image, the superior-mesenteric-artery is almost doubled but the artery wall can still be recognized. When the aperture size becomes larger, the distortion becomes worse. Phase aberration is one of the most important factors that limit improvement to lateral resolution of ultrasound imaging systems. Successful correction of phase aberrations will make it possible to improve the lateral resolution of images. Phase aberration corrected images using the near-field-signal-redundancy algorithm (Li, 1997) are shown in the second row of Fig.1 and the lateral resolution is improved when the aperture size becomes larger. In this chapter, the near-field-signal-redundancy algorithm is described in details. But first, a review of some related methods developed for phase-aberration correction is given. The