Miracle-dz/UniFAR-FTUs huggingface dataset:
The self-heating of damp cellulosic materials. I : High thermal conductivity and diffusivity

The effects of moisture content on the self-heating characteristics of stockpiles of cellulosic materials are analysed. The model includes the effects of oxidation, hydrolysis, and the evaporation and condensation of water. The full reaction-diffusion model for the system is derived and then the case of high thermal conductivity and diffusivity, i.e. the spatially uniform case, is closely examined. Degenerate singularity theory is used to show the model can exhibit at least twenty-five distinct bifurcation diagrams
Clinical Decision Support Framework for Segmentation and Classification of Brain Tumor MRIs Using a U-Net and DCNN Cascaded Learning Algorithm

Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development of computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic resonance imaging (MRI) has been the subject of many research papers so far. However, research in this sector is still in its early stage. The ultimate goal of this research is to develop a lightweight effective implementation of the U-Net deep network for use in performing exact real-time segmentation. Moreover, a simplified deep convolutional neural network (DCNN) architecture for the BT classification is presented for automatic feature extraction and classification of the segmented regions of interest (ROIs). Five convolutional layers, rectified linear unit, normalization, and max-pooling layers make up the DCNN’s proposed simplified architecture. The introduced method was verified on multimodal brain tumor segmentation (BRATS 2015) datasets. Our experimental results on BRATS 2015 acquired Dice similarity coefficient (DSC) scores, sensitivity, and classification accuracy of 88.8%, 89.4%, and 88.6% for high-grade gliomas. When it comes to segmenting BRATS 2015 BT images, the performance of our proposed CAD framework is on par with existing state-of-the-art methods. However, the accuracy achieved in this study for the classification of BT images has improved upon the accuracy reported in prior studies. Image classification accuracy for BRATS 2015 BT has been improved from 88% to 88.6%.
Ocean ecosystem discrete time dynamics generated by ℓ-Volterra operators

We consider a discrete-time dynamical system generated by a nonlinear operator (with four real parameters [Formula: see text]) of ocean ecosystem. We find conditions on the parameters under which the operator is reduced to a [Formula: see text]-Volterra quadratic stochastic operator mapping two-dimensional simplex to itself. We show that if [Formula: see text], then (under some conditions on [Formula: see text]) this [Formula: see text]-Volterra operator may have up to three or a countable set of fixed points; if [Formula: see text], then the operator has up to three fixed points. Depending on the parameters, the fixed points may be attracting, repelling or saddle points. The limit behaviors of trajectories of the dynamical system are studied. It is shown that independently on values of parameters and on initial (starting) point, all trajectories converge. Thus, the operator (dynamical system) is regular. We give some biological interpretations of our results.
3D geometrical modelling of tubular braids

Geometrical modelling for tubular braids of different structures is studied and a simple versatile three-dimensional model is proposed after considering the crimp of the braiding yarn together with the tubular curvature of the tubular braid structure. The proposed model is versatile and suitable not only for different braid structures, but also, with the changes in the structural parameters such as braid angle, number of yarns in a set, yarn and mandrel diameter the model is still applicable. Application and 3D drawings of the model for diamond, regular and triaxial braids are given with the aid of Visual Basic and 3DSMax Studio.
Salinity Induces Allometric Accumulation of Sulfur in Plants and Decouples Plant Nitrogen‐Sulfur Correlation in Alpine and Arid Wetlands

Salinization alters the elemental balance of wetlands and induces variations in plant survival strategies. Sulfur (S) plays vital roles in serving regulatory and catalytic functions in stress resistance of plants. Yet, how plant S and its relationships with nitrogen (N) vary across natural environmental gradients are not well documented. We collected 1,366 plant samples and 230 water and sediment samples from 230 wetlands in Tibetan Plateau and adjacent arid regions of western China, to analyze the effects of environmental variables on plant S accumulation and N‐S correlations. We found that plant S correlated with N in unimodal patterns. Salinity, rather than temperature or nutrient supply, promoted disproportionate accumulation of S but limited N uptake, inducing decoupling of N‐S correlation in plants. Toward high salinity, the faster increasing rates of total S than that of glutathione, the most abundant organic‐S compound in plant resistance, provided potential evidences explaining the decoupled plant N‐S correlation. A salinity of 3.9‰ was calculated to be a threshold at which substantial changes in plant N‐S correlation occurred. We designed a conceptual model to illustrate the mechanisms driving variations of N‐S correlation in plants and environments along salinity gradient. Furthermore, high salinity filtered out the salt‐sensitive species and reassembled the communities. In conclusion, increased salinity affected wetland plants by inducing S accumulation in plants and selecting salt‐tolerant species with high S concentrations at community level, providing evidences for plant adaptive mechanisms to salinity in arid regions.
Clustering Daerah Penyebaran Covid-19 Di Indonesia Menggunakan Algoritma K-Medoids

Tahun 2019 adalah Awal Mulanya muncul Wabah Penyakit yang Melanda Dunia Saat Ini yang disebut dengan Virus Covid-19. Virus Tersebut bermula dari Wuhan dan kini ditetapkan sebagai pandemi. Permasalahan Utama yang di angkat dalam penelitian ini adalah bagaimana mengetahui penyebaran covid-19 di Indonesia berdasarkan data provinsi. Karena terdapat beberapa daerah yang mempunyai kasus penyebaran yang tinggi sehingga dibutuhkan peningkatan pelayanan dan protokol kesehatan pada daerah tersebut dibandingkan dengan wilayah yang daerah penyebaran agak rendah. Sehingga dalam dalam penelitian ini dibutuhkan metode clustering untuk dapat mengelompokkan data penyebaran covid-19 di Indonesia. Adapun Algoritma yang digunakan untuk clustering adalah algoritma K-Medoids. Berdasarkan hasil penelitian yang dilakukan, maka Metode K-Medoids ini dapat Mengelompokan Daerah Penyebaran Covid 19 Di Indonesia.
The Electrical Conductivity and Mechanical Properties of Monolayer and Multilayer Nanofibre Membranes from Different Fillers: Calculated Based on Parallel Circuit

Advanced research on improving the performance of conductive polymer composites is essential to exploring their potential in various applications. Thus, in this study, the electrical conductivity of multilayer nanofibre membranes composed of polyvinyl alcohol (PVA) with different electroconductive fillers content including zinc oxide (ZnO), multiwalled carbon nanotubes (MWNTs), and Ferro ferric oxide (Fe3O4), were produced via electrospinning. The tensile property and electrical conductivity of monolayer membranes were explored. The results showed that PVA with 2 wt. % MWNTs nanofibre membrane has the best conductivity (1.0 × 10−5 S/cm) and tensile strength (29.36 MPa) compared with other fillers. Meanwhile, the combination of multilayer membrane ZnO/Fe3O4/Fe3O4/MWNTs/ZnO showed the highest conductivity (1.39 × 10−5 S/cm). The parallel circuit and calculation of parallel resistance were attempted to demonstrate the conductive mechanism of multilayer membranes, which can predict the conductivity of other multilayer films. The production of multilayer composites that enhance electrical conductivity and improve conductive predictions was successfully explored.
Current Developments in Cellular Therapy for Castration Resistant Prostate Cancer: A Systematic Review of Clinical Studies

Simple Summary Prostate cancer is one of the leading causes of cancer-related deaths among men in the United States and Europe. While conventional treatment options either have high toxicity profiles or are limited by the tumor’s ability to develop resistance, immunotherapy is specific in targeting malignant cells. It can also enable the immune system to adapt dynamically while the tumor evades the destruction process. Cellular Immunotherapy in particular is a promising approach; however, there are gaps in knowledge in the current literature on its application. To contribute to a wider understanding of cellular immunotherapy, specifically focusing on the chimeric antigen receptors (CAR) T-cells, their benefits and application in clinical settings, we conducted a comprehensive systematic review. Abstract Recently, the development of immunotherapies such as cellular therapy, monoclonal antibodies, vaccines and immunomodulators has revolutionized the treatment of various cancer entities. In order to close the existing gaps in knowledge about cellular immunotherapy, specifically focusing on the chimeric antigen receptors (CAR) T-cells, their benefits and application in clinical settings, we conducted a comprehensive systematic review. Two co-authors independently searched the literature and characterized the results. Out of 183 records, 26 were considered eligible. This review provides an overview of the cellular immunotherapy landscape in treating prostate cancer, honing in on the challenges of employing CAR T-cell therapy. CAR T-cell therapy is a promising avenue for research due to the presence of an array of different tumor specific antigens. In prostate cancer, the complex microenvironment of the tumor vastly contributes to the success or failure of immunotherapies.
Adaptive synchronization control of multimanipulator teleoperation system under constrained discrete‐time network communication

This paper addresses the synchronization control problem of uncertain single‐master multislave (SMMS) teleoperation system in which every subsystem is connected with each other via a directed constrained communication network. The data exchanges in the channel are discrete in time, intermittent in presence of irregular delays and packet loss, which make the synchronization problem more challenging and still not be well explored. We propose a new adaptive control scheme based on the virtual model and the original dynamic compensator entailing synchronization of all the subsystems under the limited communication. The most recently transmitted information is used to construct the control signal during sampling interval or the period of data loss. The validity of the control approach designed is verified by some simulation results.
Lipid Nanoparticles Delivering Constitutively Active STING mRNA to Stimulate Antitumor Immunity

Treating immunosuppressive tumors represents a major challenge in cancer therapies. Activation of STING signaling has shown remarkable potential to invigorate the immunologically “cold” tumor microenvironment (TME). However, we have shown that STING is silenced in many human cancers, including pancreatic ductal adenocarcinoma (PDAC) and Merkel cell carcinoma (MCC). In this study, we demonstrated that mRNA-lipid nanoparticle (LNP) technology could be used to efficiently deliver naturally occurring constitutively active STING mutant STINGR284S into these cancer cells to reactivate STING antitumor immunity and trigger robust killing of tumor cells. STING agonists are being actively pursued as cancer immunotherapies. However, traditional STING agonists can induce T cell cytotoxicity, counteracting the desired antitumor immune response. In addition, the antitumor efficacy of traditional STING agonists obligatorily depends on STING expression and does not work in STING-silenced cancers. Importantly, we found that STINGR284S mRNA-LNP does not introduce T cell cytotoxicity. Our studies demonstrated that mRNA-LNP delivery of STINGR284S can reactivate the antitumor response without introducing antiproliferative effects in lymphocytic immune cells, overcoming the toxicity and limitations of conventional STING agonists. Our work therefore identifies a novel therapeutic tool for reactivating antitumor immunity in an array of STING-silenced immunologically “cold” tumors that are refractory to current therapies.
A numerical method with properties of consistency in the energy domain for a class of dissipative nonlinear wave equations with applications to a Dirichlet boundary‐value problem

In this work, we present a conditionally stable finite‐difference scheme that consistently approximates the solution of a general class of (3+1)‐dimensional nonlinear equations that generalizes in various ways the quantitative model governing discrete arrays consisting of coupled harmonic oscillators. Associated with this method, there exists a discrete scheme of energy that consistently approximates its continuous counterpart. The method has the properties that the associated rate of change of the discrete energy consistently approximates its continuous counterpart, and it approximates both a fully continuous medium and a spatially discretized system. Conditional stability of the numerical technique is established, and applications are provided to the existence of the process of nonlinear supratransmission in generalized Klein‐Gordon systems and the propagation of binary signals in semi‐unbounded, three‐dimensional arrays of harmonic oscillators coupled through springs and perturbed harmonically at the boundaries, where the basic model is a modified sine‐Gordon equation; our results show that a perfect transmission is achieved via the modulation of the driving amplitude at the boundary. Additionally, we present an example of a nonlinear system with a forbidden band‐gap which does not present supratransmission, thus establishing that the existence of a forbidden band‐gap in the linear dispersion relation of a nonlinear system is not a sufficient condition for the system to present supratransmission.
Plasma boundary identification in HL-2A by means of the finite current element method

In this paper, the finite current element (FCE) method used in HL-2A is described. The calculation and test results show that the error of the reconstructed boundary given by the FCE method (<3mm) is smaller than that obtained by the current filament method used before (<6mm). Even if some current elements are located out of the plasma boundary, the FCE method can also identify the plasma boundary successfully. If the location of the finite current elements is changed in a certain area, the error of the reconstructed boundary is always very small. By employing a conventional PC (Pentium 4 2.4GHz), the calculation time of one set of plasma discharge parameters does not exceed 1ms. Thus, the FCE method can identify the diverted plasma configuration quickly and accurately. This is essential and important for real-time shape control in HL-2A.
Characteristics of electromagnetic proton cyclotron waves along auroral field lines observed by FAST in regions of upward current

Preliminary studies from FAST observations indicate that auroral ion cyclotron waves (ICWs) above the helium cyclotron frequency (ΩHe+) occur at all MLTs have amplitudes sometimes >1 V/m and often have a magnetic component even above the proton cyclotron frequency (Ωp) with amplitudes up to 2nT. Waves with transverse amplitudes greater than 100 mV/m often exhibit large spiky downward pointing field‐aligned components with amplitudes that may exceed that of transverse fluctuation. The ratio of electric to magnetic fluctuation amplitude (E1/B1) is close to c. Using the 3 dimensional electric and magnetic field measurements available from FAST it is demonstrated that these waves are in most cases polarized transverse to the ambient magnetic field (B0) and have linear polarization with wavelengths perpendicular to B0 ranging from hundreds of meters to kilometers. Calculations of the Poynting vector associated with these ICWs indicates Poynting fluxes directed downwards along B0 for waves below the local Ωp and generally upwards for waves observed close to and above this frequency with fluxes which may exceed 10% of the total field‐aligned electron beam energy flux.
Conformal invariance in random cluster models. II. Full scaling limit as a branching SLE

In the second article of this series, we establish the convergence of the loop ensemble of interfaces in the random cluster Ising model to a conformal loop ensemble (CLE) --- thus completely describing the scaling limit of the model in terms of the random geometry of interfaces. The central tool of the present article is the convergence of an exploration tree of the discrete loop ensemble to a branching SLE$(16/3,-2/3)$. Such branching version of the Schramm's SLE not only enjoys the locality property, but also arises logically from the Ising model observables.
OWR: Universal central extensions of gauge groups

map algebra as a dense subalgebra of the complexification of the gauge algebra Γ(ad(P )), with P → X R /∆ the principal Aut(g)-bundle P = X R ×∆ Aut(g). For example, let X be T n = {(~z, ~ w) ∈ C | z k + w 2 k = 1, 1 ≤ k ≤ n}, the complex n-torus. In this case, C[T ] →֒ C(T n R ,C) is injective with dense image by Fourier theory. We now look for a regular group action on T n that restricts to T n R and such that M = T n R /∆ is a manifold. Although the Bieberbach groups
Confidence Intervals for Difference Between Two Poisson Rates

In this article, we develop four explicit asymptotic two-sided confidence intervals for the difference between two Poisson rates via a hybrid method. The basic idea of the proposed method is to estimate or recover the variances of the two Poisson rate estimates, which are required for constructing the confidence interval for the rate difference, from the confidence limits for the two individual Poisson rates. The basic building blocks of the approach are reliable confidence limits for the two individual Poisson rates. Four confidence interval estimators that have explicit solutions and good coverage levels are employed: the first normal with continuity correction, Rao score, Freeman and Tukey, and Jeffreys confidence intervals. Using simulation studies, we examine the performance of the four hybrid confidence intervals and compare them with three existing confidence intervals: the non-informative prior Bayes confidence interval, the t confidence interval based on Satterthwait's degrees of freedom, and the Bayes confidence interval based on Student's t confidence coefficient. Simulation results show that the proposed hybrid Freeman and Tukey, and the hybrid Jeffreys confidence intervals can be highly recommended because they outperform the others in terms of coverage probabilities and widths. The other methods tend to be too conservative and produce wider confidence intervals. The application of these confidence intervals are illustrated with three real data sets.
Domain Decomposition Method for the $N$-body Time-Independent and Time-Dependent Schr\"odinger Equation

This paper is devoted to the derivation of a pleasingly parallel Galerkin method for the time-independent $N$-body Schr\"odinger equation, and its time-dependent version modeling molecules subject to an external electric field. In this goal, we develop a Schwarz Waveform Relaxation (SWR) Domain Decomposition Method (DDM) for the $N$-body Schr\"odinger equation. In order to optimize the efficiency and accuracy of the overall algorithm, i) we use mollifiers to regularize the singular potentials and to approximate the Schr\"odinger Hamiltonian, ii) we select appropriate orbitals, and iii) we carefully derive and approximate the SWR transmission conditions. Some low dimensional numerical experiments are presented to illustrate the methodology.
New self-adaptive bat-inspired algorithm for unit commitment problem

Bat-inspired algorithm (BA) is a new evolutionary meta-heuristics algorithm inspired by a known technique of bats for finding prey. This study presents a self-adaptive BA to solve the unit commitment (UC) problem. The applied self-adaptive technique increases the population diversity and improves the exploration power of BA which results in better solutions and higher speed of convergence in solving the UC problem. This study, also, applies simple methods to handle the minimum on-/off-time constraint and spinning reserve requirement in generation of all solutions directly and without using any penalty function. The performance of the proposed method is verified by applying 10 up to 100-unit systems as well as a Taiwan power (Taipower) 38-unit system in a 24 h scheduling horizon.
Stability and Sustainability of Resource Consumption Networks

In this paper, we examine both stability and sustainability of a network-based model of natural resource consumption. Stability is studied from a dynamical systems perspective, though we argue that sustainability is a fundamentally different notion from stability in social-ecological systems. Accordingly, we also present a criterion for sustainability that is guided by the existing literature on sustainable development. Assuming a generic social network of consuming agents' interactions, we derive sufficient conditions for both the stability and sustainability of the model as constraints on the network structure itself. We complement these analytical results with numerical simulations and discuss the implications of our findings for policy-making for sustainable resource governance.
Ferroelectric properties of Pb(Zr,Ti)O3 thin films until 40 GHz

The radio frequency characterization of Cu/TiN/Pb(Zr,Ti)O3 stack on glass is performed using coplanar transmission lines. A dielectric relaxation is evidenced around 10 GHz by the correlated decrease in the dielectric constant K together with the dielectric losses increase versus frequency. This phenomenon is attributed to domain wall relaxation. The ferroelectric nature of Pb(Zr,Ti)O3 (PZT) thin films is observed until 40 GHz with a hysteresis curve of K versus dc bias. The high K value (K∼1200) combined with a high tunability (∼35%) and moderate losses (∼1%) suggest that PZT films could be well suited for tunable devices for frequencies lower than 5 GHz.
Geometry of Horospherical Varieties of Picard Rank One

We study the geometry of smooth non-homogeneous horospherical varieties of Picard rank one. These have been classified by Pasquier and include the well-known odd symplectic Grassmannians. We focus our study on quantum cohomology, with a view towards Dubrovin’s conjecture. In particular, we describe the cohomology groups of these varieties as well as a Chevalley formula, and prove that many Gromov-Witten invariants are enumerative. This enables us to prove that in many cases the quantum cohomology is semisimple. We give a presentation of the quantum cohomology ring for odd symplectic Grassmannians. The final two sections are devoted to the derived categories of coherent sheaves on horospherical varieties. We first discuss a general construction of exceptional bundles on these varieties. We then study in detail the case of the horospherical variety associated to the exceptional group G2, and construct a full rectangular Lefschetz exceptional collection in the derived category.
Plenty of Morse functions by perturbing with sums of squares

Given a smooth function f on R^n and a submanifold M, we prove that the set of diagonal quadratic forms q such that the restriction of f+q to M is Morse is a dense set (in the n-dimensional space of diagonal quadratic forms). The standard transversality argument seems not to work and we need a more refined approach.