Miracle-dz/UniFAR-FTUs huggingface dataset:
Medical Image Reconstruction Using Kernel Based Methods

The image reconstruction problem consists in finding an approximation of a function f starting from its Radon transform Rf. This problem arises in the ambit of medical imaging when one tries to reconstruct the internal structure of the body, starting from its X-ray tomography. The classical approach to this problem is based on the Back-Projection Formula. This formula gives an analytical inversion of the Radon transform, provided that all the values of Rf are known. In applications only a discrete set of values of Rf is given, thus, one can only obtain an approximation of f. Another class of methods, called ART, can be used to solve the reconstruction problem. Following the ideas contained in ART, we try to apply the Hermite-Birkhoff interpolation to the reconstruction problem. It turns out that, since the Radon transform of a kernel basis function can be infinity, a regularization technique is needed. The method we present here is then based on positive definite kernel functions and it is very flexible thanks to the possibility to choose different kernels and parameters. We study the behavior of the methods and compare them with classical algorithms.
Vector space of linearizations for the quadratic two-parameter matrix polynomial

Given a quadratic two-parameter matrix polynomial Q(λ, μ), we develop a systematic approach to generating a vector space of linear two-parameter matrix polynomials. The purpose for constructing this vector space is that potential linearizations of Q(λ, μ) lie in it. Then, we identify a set of linearizations and describe their constructions. Finally, we determine a class of linearizations for a quadratic two-parameter eigenvalue problem.
IAN: Combining Generative Adversarial Networks for Imaginative Face Generation

Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-nearest neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and the set Y. Then, We introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). We conduct an objective and subjective evaluation for different IAN setups in the addressed task and show some useful applications for these IANs, like manifold traversing and creative face generation for characters' design in movies or video games.
DiffFlow: Differentiating Short and Long Flows for Load Balancing in Data Center Networks

—In current Data Center Networks (DCNs), Equal-Cost MultiPath (ECMP) is used as the de-facto routing protocol. However, ECMP does not differentiate between short and long flows, the two main categories of flows depending on their duration (lifetime). This issue causes hot-spots in the network, affecting negatively the Flow Completion Time (FCT) and the throughput, the two key performance metrics in data center networks. Previous work on load balancing proposed solutions such as splitting long flows into short flows, using per-packet forwarding approaches, and isolating the paths of short and long flows. We propose DiffFlow, a new load balancing solution which detects long flows and forwards packets using Random Packet Spraying (RPS) with help of SDN, whereas the flows with small duration are forwarded with ECMP by default. The use of ECMP for short flows is reasonable, as it does not create the out-of-order problem; at the same time, RPS for long flows can efficiently help to load balancing the entire network, given that long flows represent most of the traffic in DCNs. The results show that our DiffFlow solution outperforms both the individual usage of either RPS or ECMP, while the overall throughput achieved is maintained at the level comparable to RPS.
Candidate Chemosensory Genes Identified in the Procambarus clarkii (Decapoda: Cambaridae) by Antennules Transcriptome Analysis

a vital the reproduction of However, information is Procambarus clarkii , important aquaculture we conducted the antennules transcriptome of Procambarus clarkii and identified 26 olfactory-related genes, including nine ionotropic receptors, two ionotropic glutamate receptors, ten variant ionotropic glutamate receptors, four cytochrome P450s, and one carboxylesterase. Our study suggested that ionotropic receptors were the main odorant receptors in Procambarus clarkii . Additionally, the key genes that are responsible for olfactory transduction in Procambarus clarkii were identified in the cAMP-mediated olfactory transduction pathway, including Cyclic nucleotide-gated cation channel beta-1, Adenylyl cyclase III, Calcium/calmodulin-dependent protein kinase II and Na + /Ca 2+ exchanger. As a whole, our study laid a solid foundation for further functional elucidations of olfactory molecular mechanism in Procambarus clarkii , and provided further insight for a better understanding of olfaction molecular mechanism in crustaceans.
Improving I/O Performance via Address Remapping in NVMe Interface

Recently, flash-based solid-state drives (SSDs) are widely used in industry and academia due to their higher bandwidth and lower latency compared with traditional hard disk drives (HDDs). Furthermore, SSDs with the Non-Volatile Memory Express (NVMe) interface can provide higher performance and ultra-low latency compared with the Serial AT Attachment (SATA) SSDs. Due to their high performance, NVMe SSDs are adopted in many systems as fast storage devices. However, the performance of NVMe SSDs can be negatively affected by I/O access patterns. For example, random write access patterns can have negative impacts on performance due to the unique characteristics of SSDs such as out-of-place update and garbage collection. In this paper, we propose an address remapping scheme to improve the I/O performance of NVMe SSDs. Our proposed scheme transforms random access patterns into sequential access patterns in the NVMe device driver. This allows our scheme to improve the I/O performance of NVMe SSDs while supporting widely used file systems such as EXT4, XFS, BTRFS, and F2FS without any modification to the device. Experimental results show that our proposed scheme can improve the performance of NVMe SSD by up to 64.1% compared with the existing scheme.
Generating Very-High-Precision Frobenius Series with Apriori Estimates of Coefficients

The Frobenius method can be used to compute solutions of ordinary linear differential equations by generalized power series. Each series converges in a circle which at least extends to the nearest singular point; hence exponentially fast inside the circle. This makes this method well suited for very-high-precision solutions of such equations. It is useful for this purpose to have prior knowledge of the behaviour of the series. We show that the magnitude of its coefficients can be apriori predicted to surprisingly high accuracy, employing a Legendre transformation of the WKB approximated solutions of the equation.
Optical Manipulation of Incident Light for Enhanced Photon Absorption in Ultrathin Organic Photovoltaics

We attempted to improve the photon absorption of the photoactive layer in organic photovoltaic (OPV) devices by device engineering without changing their thickness. Soft nanoimprinting lithography was used to introduce a 1D grating pattern into the photoactive layer. The increase in photocurrent caused by the propagating surface plasmon–polariton mode was quantitatively analyzed by measuring the external quantum efficiency in transverse magnetic and transverse electric modes. In addition, the introduction of an ultrathin substrate with a refractive index of 1.34 improved photon absorption by overcoming the mismatched optical impedance at the air/substrate interface. As a result, the power conversion efficiency (PCE) of an ultrathin OPV with a 400 nm grating period was 8.34%, which was 11.6% higher than that of an unpatterned ultrathin OPV, and the PCE was 3.2 times higher at a low incident light angle of 80°, indicating very low incident light angle dependence.
A distributed control approach for heterogeneous linear multiagent systems

Abstract This paper considers an internal model-based distributed control approach to the cooperative output regulation problem of heterogeneous linear time-invariant multiagent systems over fixed directed communication graph topologies. First, a new definition of the linear cooperative output regulation problem is introduced in order to allow a broad class of functions to be tracked and rejected by a network of agents. Second, the solvability of this problem with three distributed control laws, namely dynamic state feedback, dynamic output feedback with local measurement and dynamic output feedback, is investigated by first considering a global condition and then providing an agent-wise local sufficient condition under standard assumptions. Finally, two numerical examples are provided to illustrate the selected contributions of this paper.
Sargachromenol Isolated from Sargassum horneri Attenuates Glutamate-Induced Neuronal Cell Death and Oxidative Stress through Inhibition of MAPK/NF-κB and Activation of Nrf2/HO-1 Signaling Pathway

Oxidative stress-induced neuronal cell loss is considered to be the major mechanism underlying the pathogenesis of neurodegenerative diseases, which could be induced by a high concentration of glutamate. In this study, sargachromenol (SC) was isolated from a marine brown seaweed Sargassum horneri (S. horneri) and its neuroprotective effects against glutamate-induced oxidative stress in HT22 cells were investigated. An MTT assay was applied to assess the cytotoxicity of the SC, and the efficacies of SC were determined by flow cytometry, an analysis of ROS production, quantitative Real-Time PCR, and the Western blot assay. Our results showed that the pretreatment of SC reduced glutamate-induced apoptosis in HT22 cells via inhibiting the sub-G1 population, DNA fragmentation, and nuclear condensation, as well as up-regulating anti-apoptotic protein (Bcl-2) and down-regulating apoptotic proteins (Bax, p53, cleaved-PARP, caspase-3, caspase-9, and cytochrome c). Additionally, SC attenuated glutamate-induced oxidative stress by suppressing mitogen-activated protein kinases (MAPKs;ERK, JNK, and p38) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling (IκBα and NF-κB p65), while activating nuclear factor erythroid-2-related factor 2 (Nrf2)/heme oxygenase 1 (HO-1) signaling (Nrf2; HO-1, and NQO-1). Our results suggest that SC could be used as a pharmacological candidate for the prevention and treatment of neurodegenerative diseases.
The Functions of Social Capital and Local Wisdom in Handling Covid-19 Pandemic in West Kalimantan

Covid-19 has caused anxiety in the world community. This impacts the multicultural community in West Kalimantan in response to the Covid-19 pandemic. Some efforts are made with social capital and local wisdom in the form of the Tolak Bala ritual as prevention so that the pandemic does not have a broad impact. This study aims to reveal the function of community social capital towards the values of local wisdom in the form of traditional rituals practiced by multicultural communities in pleading to prevent the spread of Covid-19. The subjects in this study were traditional leaders and people from various ethnic groups in West Kalimantan. The results show that the function of social capital and local wisdom used with different rituals and traditional ceremonies is a form of self-defense to avoid Covid-19.
MIFNN: Molecular Information Feature Extraction and Fusion Deep Neural Network for Screening Potential Drugs

Molecular property prediction is essential for drug screening and reducing the cost of drug discovery. Current approaches combined with deep learning for drug prediction have proven their viability. Based on the previous deep learning networks, we propose the Molecular Information Fusion Neural Network (MIFNN). The features of MIFNN are as follows: (1) we extracted directed molecular information using 1D-CNN and the Morgan fingerprint using 2D-CNN to obtain more comprehensive feature information; (2) we fused two molecular features from one-dimensional and two-dimensional space, and we used the directed message-passing method to reduce the repeated collection of information and improve efficiency; (3) we used a bidirectional long short-term memory and attention module to adjust the molecular feature information and improve classification accuracy; (4) we used the particle swarm optimization algorithm to improve the traditional support vector machine. We tested the performance of the model on eight publicly available datasets. In addition to comparing the overall classification capability with the baseline model, we conducted a series of ablation experiments to verify the optimization of different modules in the model. Compared with the baseline model, our model achieved a maximum improvement of 14% on the ToxCast dataset. The performance was very stable on most datasets. On the basis of the current experimental results, MIFNN performed better than previous models on the datasets applied in this paper.
Torque Prediction of Magnetic Gear considering 3D Axial Leakage Flux by Equivalent Magnetic Circuit

Since magnetic gears (MGs) can transmit torque without physical contact, which can allow low vibration and noise, and easy maintenance, it has the potential to replace reduction gears in electrical vehicles. In addition, a traction motor can be miniaturized by applying MGs to an electric propulsion system. For these reasons, much research had been conducted on the design of MGs. In the design stage, 2-dimensional (2D) finite element analysis (FEA) and 3-dimensional (3D) FEA can be used, but there are differences in torque between the two methods. Although the 3D FEA can reflect the leakage path of magnetic flux in the axial direction, it requires a lot of computational time. Therefore, in this paper, the correlation method between torque calculated by 2D and 3D FEA using an equivalent magnetic circuit is proposed. The proposed method can predict the accurate torque considering axial leakage flux, thereby reducing the computation time required for the design.
Late Holocene Anthropogenic and Climatic Impact on a Tropical Island Ecosystem of Northern Vietnam

Northern Vietnam has a long history of human occupation, warfare, and agriculture; yet, the environmental consequences of human activity are poorly understood due to limited paleoecological records. Results from a terrestrial wetland sediment core from the tropical island, Quan Lan, in Ha Long Bay provide a local record of ecosystem responses to societal shifts due to warfare/instability and climate change. A multiproxy study, including pollen, macro charcoal, fecal stanols and geochemistry, suggests that native vegetation was abundant and low-level, subsistence wet-rice agriculture and burning were in practice during a time of increased monsoon intensity between 1150 BCE and 950 CE. Between 950-1450 CE, a trading and military port was established on Quan Lan Island which served as a major hub of southeast Asian trade and protected the mainland from Mongol invasions. During this period, population near the wetland declined to undetectable levels, rice agriculture declined, burning ceased, and disturbance species expanded. A simultaneous shift toward a more arid climate, with possible extended years of drought, occurred during the Medieval Climate Anomaly based on regional climate records. Without a reliable source of freshwater, rice production declined and/or was supplemented by trade. When the mainland capital near present day Hanoi moved south to Hue after 1450 CE, the port ceased operation. During this time, climate became wetter, and precipitation and surface water more reliable than before. Population near the wetland increased as did burning and rice agriculture. The research has implications for understanding the maintenance of tropical biodiversity amidst long-term human occupation, political unrest and climate change.
Homogenisation and spectral convergence of a periodic elastic composite with weakly compressible inclusions

A two-phase elastic composite with weakly compressible elastic inclusions is considered. The homogenised two-scale limit problem is found, via a version of the method of two-scale convergence, and analysed. The microscopic part of the two-scale limit is found to solve a Stokes type problem and shown to have no microscopic oscillations when the composite is subjected to body forces that are microscopically irrotational. The composites spectrum is analysed and shown to converge, in an appropriate sense, to the spectrum of the two-scale limit problem. A characterisation of the two-scale limit spectrum is given in terms of the limit macroscopic and microscopic behaviours.
Shintani theta lifts of harmonic Maass forms

We define a regularized Shintani theta lift which maps weight $2k+2$ ($k \in \Z, k \geq 0$) harmonic Maass forms for congruence subgroups to (sesqui-)harmonic Maass forms of weight $3/2+k$ for the Weil representation of an even lattice of signature $(1,2)$. We show that its Fourier coefficients are given by traces of CM values and regularized cycle integrals of the input harmonic Maass form. Further, the Shintani theta lift is related via the $\xi$-operator to the Millson theta lift studied in our earlier work. We use this connection to construct $\xi$-preimages of Zagier's weight $1/2$ generating series of singular moduli and of some of Ramanujan's mock theta functions.
Quantum Serre theorem as a duality between quantum D-modules

We give an interpretation of quantum Serre theorem of Coates and Givental as a duality of twisted quantum D-modules. This interpretation admits a non-equivariant limit, and we obtain a precise relationship among (1) the quantum D-module of X twisted by a convex vector bundle E and the Euler class, (2) the quantum D-module of the total space of the dual bundle E∨ → X, and (3) the quantum D-module of a submanifold Z ⊂ X cut out by a regular section of E . When E is the anticanonical line bundle K−1 X , we identify these twisted quantum D-modules with second structure connections with different parameters, which arise as Fourier–Laplace transforms of the quantum D-module of X. In this case, we show that the duality pairing is identified with Dubrovin’s second metric (intersection form).
Simple transitive $2$-representations of small quotients of Soergel bimodules

In all finite Coxeter types but $I_2(12)$, $I_2(18)$ and $I_2(30)$, we classify simple transitive $2$-rep\-re\-sen\-ta\-ti\-ons for the quotient of the $2$-category of Soergel bimodules over the coinvariant algebra which is associated to the two-sided cell that is the closest one to the two-sided cell containing the identity element. It turns out that, in most of the cases, simple transitive $2$-representations are exhausted by cell $2$-representations. However, in Coxeter types $I_2(2k)$, where $k\geq 3$, there exist simple transitive $2$-representations which are not equivalent to cell $2$-representations.
Invariance of quantum rings under ordinary flops: III

The paper is Part III of our ongoing project to study a case of Crepant Transformation Conjecture: K-equivalence Conjecture for ordinary flops. In this paper we prove the invariance of quantum rings for general ordinary flops, whose local models are certain non-split toric bundles over arbitrary smooth base. An essential ingredient in the proof is a quantum splitting principle, which reduces a statement in Gromov--Witten theory on non-split bundles to the case of split bundles.
A new Machine Learning based Approach for Power System State Forecasting

State estimation in power systems is utilized to provide an ongoing data set for controlling and observing power systems' performance. There are a few traditional methods like Weighted Least Square (WLS), Weighted Least Average Value (WLAV), and settled utilizing iterative techniques, for example, Gauss-Newton methods. However, these techniques are sensitive to the operating conditions of power systems and uncertainties associated with Renewable Energy Systems (RESs). These techniques yield poor results in the presence of missing data arising out of unreliable communication networks and false data injection, as in the case of a cyber-attack. This paper proposes Bi-directional LSTM (BiLSTM) based Machine Learning method to forecast the state values of power systems. The BiLSTM model utilizes forward and backward layers, having bidirectional memory, making it capable of estimating both past and future hidden layers data. This paper investigates the performance of the proposed method studied on different test system datasets. The efficacy of the proposed method is investigated by comparing the obtained results with other Machine Learning techniques results in the literature. Further, the BiLSTM model's robustness for state estimation is analyzed in the presence of Gaussian noise and missing data points.
Cohen-Macaulay properties under the amalgamated construction

Let $A$ and $B$ be commutative rings with unity, $f:A\to B$ a ring homomorphism and $J$ an ideal of $B$. Then the subring $A\bowtie^fJ:=\{(a,f(a)+j)|a\in A$ and $j\in J\}$ of $A\times B$ is called the amalgamation of $A$ with $B$ along $J$ with respect to $f$. In this paper, we study the property of Cohen-Macaulay in the sense of ideals which was introduced by Asgharzadeh and Tousi, a general notion of the usual Cohen-Macaulay property (in the Noetherian case), on the ring $A\bowtie^fJ$. Among other things, we obtain a generalization of the well-known result that when the Nagata's idealization is Cohen-Macaulay.
Multifractal Analysis of The New Level Sets

By an appropriate definition, we divide the irregular set into level sets. Then we characterize the multifractal spectrum of these new pieces by calculating their entropies. We also compute the entropies of various intersections of the level sets of regular and irregular set which is rarely studied in the literature. Moreover, our conclusions also hold for the topological pressure. Finally, we consider the continuous case and use our results to give a description for the suspension flow.