Miracle-dz/UniFAR-FTUs huggingface dataset:
Suitable areas for the invasion expansion of Xylocopa bees in South America

The introduction of exotic species into native ecosystems can be a cause for concern when those species are invasive. Invasive species cause ecological problems and have socio‐cultural impacts on human health and the economy; for example, invasive bees may negatively impact their introduced ecosystem by spreading diseases or outcompeting native pollinators. Xylocopa spp. bees are diverse and distributed throughout the Neotropics. However, Xylocopa augusti (Lepeletier, 1841) and Xylocopa splendidula (Lepeletier, 1841) are not native to Mediterranean Chile. This study aimed to evaluate the invasive potential of these exotic species and predict the potential macroecological effects of their invasions. We also aimed to pinpoint possible distributions for these species throughout South America. We correlated biogeographic occurrence data with climatic variables for each species to model their potential distribution in both current and future scenarios. The models provide strong evidence that both species are changing their distributions: their ranges are expanding towards western South America, particularly Bolivia, Chile and Peru. We demonstrate an increase in niche overlap between these species and show there are new geographic areas vulnerable to the establishment of these invasive bees under current and future climate conditions. These data suggest that these bees may adapt their geographic distribution as the climate changes and pose a threat to native pollinators in new geographic areas.
Quantum Computation and Pseudotelepathic Games*

A quantum algorithm succeeds not because the superposition principle allows ‘the computation of all values of a function at once’ via ‘quantum parallelism’, but rather because the structure of a quantum state space allows new sorts of correlations associated with entanglement, with new possibilities for information‐processing transformations between correlations, that are not possible in a classical state space. I illustrate this with an elementary example of a problem for which a quantum algorithm is more efficient than any classical algorithm. I also introduce the notion of ‘pseudotelepathic’ games and show how the difference between classical and quantum correlations plays a similar role here for games that can be won by quantum players exploiting entanglement, but not by classical players whose only allowed common resource consists of shared strings of random numbers (common causes of the players’ correlated responses in a game).
Explorando Redes Neurais de Grafos para Classificação de Arritmias

Arritmia cardíaca é uma condição de risco e seu diagnóstico precoce é de fundamental importância. Por isso, a automação do processo de identificação de arritmia é desejável. Neste contexto, um modelo de classificação automática de arritmias em sinais de eletrocardiograma (ECG) é proposto baseado em Graph Neural Network (GNN) e o batimento cardíaco representado por meio de um grafo via algoritmo Visibility Graph (VG). São avaliados três modelos de redes GNN: uma rede convolutional de grafos com duas camadas (GCN-2L), outra com três camadas (GCN-3L) e GraphSAGE (GraphSAGE-4L). Sob o paradigma interpatient, o modelo GraphSAGE-4L apresentou o melhor desempenho, obtendo F1-score médio de 0,86 para as classes N, S e V.
Critical suppression of spin Seebeck effect by magnetic fields

The longitudinal spin Seebeck effect (LSSE) in $\mathrm{Pt}/{\mathrm{Y}}_{3}{\mathrm{Fe}}_{5}{\mathrm{O}}_{12}\phantom{\rule{0.28em}{0ex}}(\mathrm{YIG})$ junction systems has been investigated at various magnetic fields and temperatures. We found that the LSSE voltage in a Pt/YIG-slab system is suppressed by applying high magnetic fields and this suppression is critically enhanced at low temperatures. The field-induced suppression of the LSSE in the Pt/YIG-slab system is too large at around room temperature to be explained simply by considering the effect of the Zeeman gap in magnon excitation. This result requires us to introduce a magnon-frequency-dependent mechanism into the scenario of LSSE; low-frequency magnons dominantly contribute to the LSSE. The magnetic field dependence of the LSSE voltage was observed to change by changing the thickness of YIG, suggesting that the thermospin conversion by the low-frequency magnons is suppressed in thin YIG films due to the long characteristic lengths of such magnons.
Toward Quantitative Phase-field Modeling of Dendritic Electrodeposition

A thin-interface phase-field model of electrochemical interfaces is developed based on Marcus kinetics for concentrated solutions, and used to simulate dendrite growth during electrodeposition of metals. The model is derived in the grand electrochemical potential to permit the interface to be widened to reach experimental length and time scales, and electroneutrality is formulated to eliminate the Debye length. Quantitative agreement with zinc kinetics is achieved. Reducing the exchange current density is found to suppress the growth of dendrites. Screening electrolytes by their exchange currents and reorganization energies is suggested as a strategy for controlling dendrite growth in batteries.
Impact of Dual Connectivity and Channel Hardening in 5G Networks with Different Resource Allocation Strategies

—Considering 5G networks with multi-connectivity capability and deploying large antenna arrays operating in mmWaves, this paper performs two numerical analyses. In the first one, it is assumed that, increasing the number of antenna elements in the transmitter, the channel variations reduce, i.e., the channel “hardens”. Based on this, it is proposed a method to optimize Channel Quality Indicator (CQI) reporting based on the Channel Hardening (CH) occurrence. The proposed method, allows the aggregation of measurement reports of different resources, which simplifies Radio Resource Allocation (RRA) with almost no loss of performance. The second numerical analysis investigates the adoption of two multi-connectivity approaches: Dual Connectivity (DC) and Fast-RAT Scheduling (FS). In DC, the user plane can be simultaneously connected to two radio access technologies, while, in FS, it can be connected to only one at a time. The presented analyses show that both approaches can improve the network performance, depending on the adopted RRA strategy and key performance indicators of interest.
Ranking non-regular designs

Fractional factorial designs are commonly used in industrial and experiments to identify factors affecting a response or process. The focus of this thesis is on two-level orthogonal designs, however, the methods we consider can be generalized to nonorthogonal designs. Orthogonal designs can be classified into two broad categories: regular designs, which have a simple aliasing structure, in that any two effects are orthogonal or fully aliased; and non-regular designs which have a complex aliasing structure, in that there exist effects that are neither orthogonal nor fully aliased. This thesis focuses on the study of non-regular designs. In many industrial settings robust parameter designs are performed as a strategy for variance reduction. In these situations the experimenter is mainly interested in the estimation of control-by-noise interactions. For non-regular fractional factorial designs, the “goodness” of the design can be judged using the generalized aberration criteria. We extend the definitions of generalized aberration to emphasize the controlby-noise interactions. Theoretical results are used to show how one can construct the set of all non-isomorphic multi-factor designs from the existing set of all nonisomorphic designs. We then use the set of all non-isomorphic multi-factor designs to construct a catalog of generalized minimum aberration robust parameter designs. Next, we focus attention on factorial designs and introduce the projection estimation capacity sequence and use this new criterion to select good non-regular designs. Two theoretical results are presented that will be practically useful when searching for good designs. Based on these results, a simple search procedure is implemented to find such designs. Catalogues of designs are constructed for 20, 24 and 28 runs.
SLOW QUENCHING OF STAR FORMATION IN OMEGAWINGS CLUSTERS: GALAXIES IN TRANSITION IN THE LOCAL UNIVERSE

The star formation quenching depends on environment, but a full understanding of what mechanisms drive it is still missing. Exploiting a sample of galaxies with masses M * > 10 9.8 M ⊙ ? > , drawn from the WIde-field Nearby Galaxy-cluster Survey (WINGS) and its recent extension OMEGAWINGS, we investigate the star formation rate (SFR) as a function of stellar mass (M * ? > ) in galaxy clusters at 0.04 < z < 0.07 ? > . We use non-member galaxies at 0.02 < z < 0.09 as a field control sample. Overall, we find agreement between the SFR–M * ? > relation in the two environments, but detect a population of cluster galaxies with reduced SFRs, which is rare in the field. These transition galaxies are mainly found within the cluster virial radius (R200), but they impact on the SFR–M * ? > relation only within 0.6R200. The ratio of transition to pure star-forming galaxies strongly depends on environment, being larger than 0.6 within 0.3R200 and rapidly decreasing with distance, while it is almost flat with M*. As galaxies move downward from the SFR–M * ? > main sequence, they become redder and present older luminosity- and mass-weighted ages. These trends, together with the analysis of the star formation histories, suggest that transition galaxies have had a reduced SFR for the past 2–5 Gyr. Our results are consistent with the hypothesis that the interaction of galaxies with the intracluster medium via strangulation causes a gradual shut down of star formation, giving birth to an evolved population of galaxies in transition from being star forming to becoming passive.
A novel complex network community clustering method for fault diagnosis

The complex network, as a method for the analysis of nonlinear and non-stationary signals, overcomes the shortcomings of traditional time-frequency analysis methods and proves its effectiveness in mechanical fault diagnosis. Community clustering, a type of complex network, has made great progress in recent years. However, the existing community clustering algorithms have disadvantages in that they lack significant global extreme value and huge search spaces. Therefore, a Fast Newman algorithm based on reliability judgment is proposed. Starting from the community structure characteristics of the complex network, with the fault sample as a network node, the relationship between the samples as a connected edge and a complex network model of fault data is established. Clusters in troubleshooting are transformed into community structure discovery in the network. Firstly, the initial division of the community is obtained by measuring the distance between the samples. Then, the modularity index of the network is used as a standard function of the community division, and the bottom-up community merger is performed. The local edge density index is used for reliability determination before each combination to achieve global optimization, and the network block structure is the most obvious. Finally, with all the data merged into one community, the optimal division of the community structure is obtained, while accurate community clustering and fault diagnosis is realized. The benchmark graphs for testing community detection (Lancichinetti–Fortunato–Radicchi benchmark standard test network, LFR) and different fault data of rolling bearings under multiple operating conditions are applied to verify the effectiveness of this method; the results prove that the modified Fast Newman algorithm has better clustering effects and a higher accuracy rate than the original algorithm. Compared with K-means clustering and fuzzy clustering, the modified Fast Newman algorithm achieves higher performance in fault diagnosis of rolling bearings under multiple operating conditions.
Analysis on Irreversible Processes using the Phase-Field Variational Approach with the Entropy or Energy Functional

The variational approach usually used in phase field models (PFVA) is applied here to analyse complex irreversible processes such as thermoelectric (TE) effects and thermally driven mass transport (TDMT). Complex irreversible processes arise from the coupling effects between simple irreversible processes. Each simple irreversible process is assiciated with an entropy or energy density function. During complex irreversible processes with multiple fields present, this entropy or energy density function is assumed to be dependent on all independent field variables. Using the total entropy functionals, the TE effects and TDMT are analysed and important kinetic coefficients such as the Seebeck coefficient and the heat of transport are determined with straightforward physical contents. Using the total energy functionals, the linear irreversible processes are analysed with the Onsager approach and the nonlinear irreversible processes with PFVA. It is found both the Onsager's relations and the fluxes defined using PFVA guarantee the satisfaction of the first law of thermodynamics during the process of conversion of energies. To analyze the diffusion process under the influence of elasticity, PFVA is also modified to incorporate the reversible evolution of elastic fields. It is shown energies are conserved via both the irreversible diffusion process and the reversible evolution of the elastic fields. Finally, PFVA is generalized to study nonequilibrium thermodynamics using an extra kinetic contribution to the entropy density function. The analyses can be extended to a nonequilibrium thermodynamic system with multiple physical fields present. Thus, it is believed PFVA has the potential of not only significantly advancing our understanding of the thermodynamics of irreversible processes, but also making thermodynamics as a discipline and the study of it truly dynamic.
Charge, Lattice, and Spin Dynamics in Photoinduced Phase Transitions from Charge-Ordered Insulator to Metal in Quasi-Two-Dimensional Organic Conductors

To elucidate the different photoinduced melting dynamics of charge orders observed in the quasi-two-dimensional organic conductors θ-(BEDT-TTF) 2 RbZn(SCN) 4 and α-(BEDT-TTF) 2 I 3 [BEDT-TTF = bis(ethylenedithio)tetrathiafulvalene], we theoretically study the photoinduced time evolution of charge and spin correlation functions on the basis of exact many-electron wave functions coupled with classical phonons in extended Peierls–Hubbard models on anisotropic triangular lattices. In both salts, the so-called horizontal-stripe charge order is stabilized by nearest-neighbor repulsive interactions and electron–lattice interactions. In θ-(BEDT-TTF) 2 RbZn(SCN) 4 (abbreviated as θ-RbZn), the stabilization energy due to lattice distortion is larger, so that a larger quantity of energy needs to be absorbed to melt charge and lattice orders. The photoinduced charge dynamics shows a complex behavior owing to a substantial number of nearly degenerate eigenstates involved. This is related to the high structural symmetr.
GWO-SA: Gray Wolf Optimization Algorithm for Service Activation Management in Fog Computing

Although fog computing is a new research topic, there are robust and integrated solutions for service activation management and how to distribute IoT services over available fog computing services resources. This paper presents a multi-objective gray wolf optimization (GWO) solution for more efficient fog computing service scheduling and activation management. This solution utilizes a multi-objective function in the resource allocation process by developing and improving the proposed algorithm to check the status of resources and manage tasks. The main purpose of this study is to create a trade-off between energy consumption and task execution time. This research has presented a two-stage multi-objective approach to solve the scheduling and task offloading problem. First, the GWO algorithm is used to solve the scheduling problem, and then container migration is used to solve the task offloading problem and appropriate resource allocation. Container migration causes an idle physical server to turn off, reducing power consumption, improving imbalance, reducing latency, and improving efficiency. The proposed method has been compared with three scenarios with 700 nodes, 1000 nodes, and 5000 nodes. The proposed solution has been implemented and simulated in iFogSim and compared with five classical algorithms. The analytical results indicate the better performance of the proposed strategy with average execution time for host selection averages a reduction of 15, 20, 25, 20, and 21%, respectively, compared to Particle swarm optimization (PSO), Ant colony optimization (ACO), Grasshopper optimization algorithm (GOA), Genetic algorithm (GA), and Cuckoo optimization algorithm (COA), 12% reduction in average time required for reallocation container, and the service-level agreement (SLA) violation rate is maintained in the range of 9-10/% compared to all other solutions.
NEAR-INFRARED PHOTOMETRY OF Y DWARFS: LOW AMMONIA ABUNDANCE AND THE ONSET OF WATER CLOUDS

We present new near-infrared photometry for seven late-type T dwarfs and nine Y-type dwarfs, and lower limit magnitudes for a tenth Y dwarf, obtained at Gemini Observatory. We also present a reanalysis of H-band imaging data from the Keck Observatory Archive, for an 11th Y dwarf. These data are combined with earlier MKO-system photometry, Spitzer and WISE mid-infrared photometry, and available trigonometric parallaxes, to create a sample of late-type brown dwarfs that includes 10 T9–T9.5 dwarfs or dwarf systems, and 16 Y dwarfs. We compare the data to our models, which include updated H2 and NH3 opacity, as well as low-temperature condensate clouds. The models qualitatively reproduce the trends seen in the observed colors; however, there are discrepancies of around a factor of two in flux for the Y0–Y1 dwarfs, with Teff ≈ 350–400 K. At Teff ∼ 400 K, the problems could be addressed by significantly reducing the NH3 absorption, for example by halving the abundance of NH3 possibly by vertical mixing. At Teff ∼ 350 K, the discrepancy may be resolved by incorporating thick water clouds. The onset of these clouds might occur over a narrow range in Teff, as indicated by the observed small change in 5 μm flux over a large change in J − W2 color. Of the known Y dwarfs, the reddest in J −W2 are WISEP J182831.08+265037.8 and WISE J085510.83−071442.5. We interpret the former as a pair of identical 300–350 K dwarfs, and the latter as a 250 K dwarf. If these objects are ∼3 Gyr old, their masses are ∼10 and ∼5 Jupiter-masses, respectively.
HEPATITIS-A QUICK VIEW

Viral HepatitisEvery one of us has heard the word “hepatitis” and considered it a fatal disease. “Viral hepatitis” is the inflammation of the liver that is caused by a nasty family of viruses. Due to hepatitis, it is estimated that globally 1.34 million people died per year and it is also reported that about 80% of cases of liver cancer are only caused by hepatitis B and Hepatitis C together. The number of patients having this infection is amplifying each year, which is quite an alarming situation (1). Viral Hepatitis Modes of TransmissionHAV (Hepatitis A Virus) transmitted by the contaminated water (fecal-oral route), and for HBV (Hepatitis B Virus) and HBC (Hepatitis C Virus)There are mainly four modes of transmission, these are;1. Via blood2. Through sexually contact3. Through needle sharing during drug administration and4. From an infected mother to baby.Further, health care professionals who are dealing with the patients and their sample are also at higher risk.
A Microwave Stripline Ring Resonator Sensor Exploiting the Thermal Coefficient of Dielectric Constant for High-Temperature Sensing

A stripline transmission-line (TL)-based temperature sensor for use in harsh environments is designed to exploit the thermal coefficient of the dielectric constant (TCD) of the microwave (MW) substrate material. Rogers 3210 substrate is selected owing to its high TCD of −459 ppm/°C and a dielectric constant of 10.8. A ring resonator is designed for 2.4 GHz, with the ring selected for the simple geometric dependence of its resonant frequency on radius. TLs are gap-coupled to the ring, with widths designed for 50- $\Omega $ impedance matching and lengths optimized for a compact form factor. Upper and lower ground planes shield the dielectric, resonator, and TLs from environmental disturbances, such as debris and moisture, which could otherwise disrupt temperature measurement. Furthermore, the electric field is completely contained within the homogeneous dielectric, providing improved sensitivity compared to similar designs using microstrip technology. The fabricated sensor requires uniform compression of layers to mitigate the effects of air pockets and thermal expansion of materials. It is found that the sensor requires temperature-conditioning, approximately 70 h cycling between 30 °C and 80 °C, before its resonant frequency reaches a steady state suitable for instantaneous temperature measurement. Subsequent 10 °C- and 2 °C-step experiments are performed in the 30 °C–80 °C and 30 °C–40 °C ranges, respectively. As a result, a linear sensitivity of $\approx 500$ kHz/°C is identified. The duration of these experiments and time-based data are representative of applications where long-term temperature monitoring is required.
Localized chemical switching of the charge state of nitrogen-vacancy luminescence centers in diamond

We present a direct-write chemical technique for controlling the charge state of near-surface nitrogen vacancy centers (NVs) in diamond by surface fluorination. Fluorination of H-terminated diamond is realized by electron beam stimulated desorption of H2O in the presence of NF3 and verified with environmental photoyield spectroscopy (EPYS) and photoluminescence (PL) spectroscopy. PL spectra of shallow NVs in H- and F-terminated nanodiamonds show the expected dependence of the NV charge state on their energetic position with respect to the Fermi-level. EPYS reveals a corresponding difference between the ionization potential of H- and F-terminated diamond. The electron beam fluorination process is highly localized and can be used to fluorinate H-terminated diamond, and to increase the population of negatively charged NV centers.
Diffusion optical tomography reconstruction based on convex–nonconvex graph total variation regularization

Graph total variation (GTV) is a powerful regularization tool for diffuse optical tomography (DOT) reconstruction since it combines the powerful representation ability of graph and the edge‐preserving ability of total variation (TV) regularization. However, as everyone knows, the classical TV regularization trend underestimates the large edge values. In this paper, we propose a convex–nonconvex graph total variation (CNC‐GTV) regularization for DOT reconstruction. In particular, we construct a nonconvex regularization by subtracting the generalized Huber function from the GTV regularization. We show that the global convexity of the objective function can be guaranteed by adjusting the nonconvex control parameters. Moreover, we present an alternating direction multiplier method (ADMM) to solve the proposed DOT reconstruction model. Numerical experiments show that the proposed model outperforms existing models in visual and numerical results.