Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of structural and electronic properties of graphene and some graphene derivatives based on orthorhombic unit cell by density functional theory

Pristine graphene and graphene derivatives have been investigated with the density functional theory (DFT). The calculations consist of structural optimization, density of states (DOS), projected density of states (PDOS) based on orthorhombic 4-atom unit cell. The obtained results are in good agreement with the experimental data. The highest deviations from the experiment are 0.35 % and 0.28 % for the lattice constant and bond length, respectively. In addition, the results of DOS, and PDOS have shed light on electronic properties of graphene. The functionalization of graphene leads to distortion of graphene sheet. New states around the Fermi level of graphene derivatives are mainly composed of 2p orbitals of carbon and oxygen atoms. Besides, structural and electronic properties of graphene and derivatives obtained from the 4-atom orthorhombic unit cell are in line with those from the traditional hexagonal 2-atom unit cell in the previous works. This result proved the reliability of the constructed orthorhombic 4-atom unit cell of graphene.
Synthesis of Glycolysis Inhibitor PFK15 and Its Synergistic Action with an Approved Multikinase Antiangiogenic Drug on Human Endothelial Cell Migration and Proliferation

Activated endothelial, immune, and cancer cells prefer glycolysis to obtain energy for their proliferation and migration. Therefore, the blocking of glycolysis can be a promising strategy against cancer and autoimmune disease progression. Inactivation of the glycolytic enzyme PFKFB3 (6-phosphofructo-2-kinase/fructose-2,6-biphosphatase) suppresses glycolysis level and contributes to decreased proliferation and migration of cancer (tumorigenesis) and endothelial (angiogenesis) cells. Recently, several glycolysis inhibitors have been developed, among them (E)-1-(pyridin-4-yl)-3-(quinolin-2-yl)prop-2-en-1-one (PFK15) that is considered as one of the most promising. It is known that PFK15 decreases glucose uptake into the endothelial cells and efficiently blocks pathological angiogenesis. However, no study has described sufficiently PFK15 synthesis enabling its general availability. In this paper we provide all necessary details for PFK15 preparation and its advanced characterization. On the other hand, there are known tyrosine kinase inhibitors (e.g., sunitinib), that affect additional molecular targets and efficiently block angiogenesis. From a biological point of view, we have studied and proved the synergistic inhibitory effect by simultaneous administration of glycolysis inhibitor PFK15 and multikinase inhibitor sunitinib on the proliferation and migration of HUVEC. Our results suggest that suppressing the glycolytic activity of endothelial cells in combination with growth factor receptor blocking can be a promising antiangiogenic treatment.
The “Folk Theorem” on effective field theory: How does it fare in nuclear physics?

This is a brief history of what I consider as very important, some of which truly seminal, contributions made by young Korean nuclear theorists, mostly graduate students working on PhD thesis in 1990s and early 2000s, to nuclear effective field theory, nowadays heralded as the first-principle approach to nuclear physics. The theoretical framework employed is an effective field theory anchored on a single scale-invariant hidden local symmetric Lagrangian constructed in the spirit of Weinberg’s “Folk Theorem” on effective field theory. The problems addressed are the high-precision calculations on the thermal np capture, the solar pp fusion process, the solar hep process — John Bahcall’s challenge to nuclear theorists — and the quenching of gA in giant Gamow-Teller resonances and the whopping enhancement of first-forbidden beta transitions relevant in astrophysical processes. Extending adventurously the strategy to a wild uncharted domain in which a systematic implementation of the “theorem” is far from obvious, the same effective Lagrangian is applied to the structure of compact stars. A surprising, unexpected, result on the properties of massive stars, totally different from what has been obtained up to day in the literature, is predicted, such as the precocious onset of conformal sound velocity together with a hint for the possible emergence in dense matter of hidden symmetries such as scale symmetry and hidden local symmetry.
Biosensor Based on Peroxidase-Mimetic Nanozyme and Lactate Oxidase for Accurate L-Lactate Analysis in Beverages

Precision analysis of the key biological metabolites such as L-lactate has great practical importance for many technological processes in food technology, including beverage production. Here we describe a new, highly selective, and sensitive biosensor for accurate L-lactate assay based on a combination of peroxidase-mimetic nanozymes with microbial lactate oxidase (LOx) immobilized onto the surface of a graphite-rod electrode (GE). The peroxidase-like nanozymes were synthesized using the debris of carbon microfibers (CFs) functionalized with hemin (H) and modified with gold nanoparticles (AuNPs) or platinum microparticles (PtMPs). The nanozyme formed with PtMPs as well as corresponding bioelectrodes based on it (LOx-CF-H-PtMPs/GE) is characterized by preferable catalytic and operational characteristics, so it was selected for the analysis of L-lactate content in real samples of grape must and red wine. The results of the L-lactate analysis obtained by the developed biosensors are highly correlated with a very selective spectrophotometric approach used as a reference. The developed biosensor, due to its high selectivity and sensitivity, is very prospective not only for the beverage industry and food technology, but also for clinical diagnostics and medicine, as well as in other applications where the accurate analysis of L-lactate is highly important.
Two Jupiter-mass Planets Discovered by the KMTNet Survey in 2017

We report two microlensing events, KMT-2017-BLG-1038 and KMT-2017-BLG-1146, that are caused by planetary systems. These events were discovered by Korea Microlensing Telescope Network survey observations from the 2017 bulge season. The discovered systems consist of a planet and host star with mass ratios of and , respectively. Based on a Bayesian analysis assuming a Galactic model without stellar remnant hosts, we find that the planet KMT-2017-BLG-1038Lb is a super-Jupiter-mass planet ( ) orbiting a mid-M dwarf host ( ) that is located at kpc toward the Galactic bulge. The other planet, KMT-2017-BLG-1146Lb, is a sub-Jupiter-mass planet ( ) orbiting a mid-M dwarf host ( ) at a distance of kpc toward the Galactic bulge. Both are potentially gaseous planets that are beyond their hosts’ snow lines. These typical microlensing planets will be routinely discovered by second-generation microlensing surveys, rapidly increasing the number of detections.
Data Collection in IoT Using UAV Based on Multi-Objective Spotted Hyena Optimizer

Today, the use of information and communication technology is very important in making the internet of things (IoT) elements distributable around the earth. With the development of IoT topics, today unmanned aerial vehicles (UAV) are utilized as a platform for gathering data from various IoT devices located worldwide. Determining the number and optimal locations of drones can minimize energy consumption in this data-collection system in the IoT. Using a promising multi-objective optimization algorithm (MOA) can achieve this goal. In this research, a bio-inspired MOA, termed the multi-objective spotted hyena optimizer (MOSHO), is employed on the data-collection platform for a group of IoT devices in a geographical area. The results of this method have been compared with other evolutionary MOAs. The analysis of the results shows that the MOSHO has a noteworthy consequence on the process of optimal energy consumption in this system, in addition to a high convergence associated with better diversity and robustness. The results of this research can be used to identify the optimization parameters in this system.
Mid-infrared interferometric variability of DG Tauri : Implications for the inner-disk structure

Context. DG Tau is a low-mass pre-main sequence star, whose strongly accreting protoplanetary disk exhibits a so-far enigmatic behavior: its mid-infrared thermal emission is strongly time-variable, even turning the 10 μ m silicate feature from emission to absorption temporarily. Aims. We look for the reason for the spectral variability at high spatial resolution and at multiple epochs. Methods. Infrared interferometry can spatially resolve the thermal emission of the circumstellar disk, also giving information about dust processing. We study the temporal variability of the mid-infrared interferometric signal, observed with the VLTI/MIDI instrument at six epochs between 2011 and 2014. We fit a geometric disk model to the observed interferometric signal to obtain spatial information about the disk. We also model the mid-infrared spectra by template fitting to characterize the profile and time dependence of the silicate emission. We use physically motivated radiative transfer modeling to interpret the mid-infrared interferometric spectra. Results. The inner disk ( r μ m absorption feature related to amorphous silicate grains. The outer disk ( r > 1−3 au) spectra show a crystalline silicate feature in emission, similar to the spectra of comet Hale-Bopp. The striking difference between the inner and outer disk spectral feature is highly unusual among T Tauri stars. The mid-infrared variability is dominated by the outer disk. The strength of the silicate feature changed by more than a factor of two. Between 2011 and 2014 the half-light radius of the mid-infrared-emitting region decreased from 1.15 to 0.7 au. Conclusions. For the origin of the absorption we discuss four possible explanations: a cold obscuring envelope, an accretion heated inner disk, a temperature inversion on the disk surface and a misaligned inner geometry. The silicate emission in the outer disk can be explained by dusty material high above the disk plane, whose mass can change with time, possibly due to turbulence in the disk.
Comparison of fully implicit and IMPES formulations for simulation of water injection in fractured and unfractured media

In this work, we compare the fully implicit (FI) and implicit pressure‐explicit saturation (IMPES) formulations for the simulation of water injection in fractured media. The system of partial differential equations is discretized within the discrete‐fracture framework using a control‐volume method. A unique feature of the methodology is that there is no need for the computation of matrix–fracture transfer terms.
Feature-Enhanced Beamforming for Underwater 3-D Acoustic Imaging

A planar array of sensors and beamforming algorithms are required for underwater 3-D acoustic imaging system. However, due to limited aperture and sensor numbers, conventional beamforming usually results in wide mainlobes and high sidelobes, which severely degrade the image quality. To date, using unconventional beamforming algorithms to improve the imaging quality of underwater 3-D acoustic systems have been rarely investigated. This article proposes a feature-enhanced beamforming (FEBF) algorithm, with the goal of improving the imaging quality by utilizing more appropriate prior knowledge that objects in the angular domain in underwater 3-D imaging scenes are generally sparse but locally dense. The proposed FEBF employs the $l_{1}$-total variation (L1-TV) mixed norm regularization. The penalized beamforming optimization is reformed into convex programming with linear constraints and solved by alternating direction method of multipliers. The results of simulation and experiment demonstrate that the proposed FEBF has the ability to effectively improve the image quality when compared with the other existing beamforming methods. This study also proposes a 2-D fast Fourier transform based acceleration strategy, which effectively reduces the computational time of the FEBF algorithm by about 4.3 × 103 times for forming 200 × 200 beams. The accelerated version of the proposed FEBF method is considered to have potential for real-time imaging systems.
Computer Simulation of the Drying of Seeds and Vegetables in a Discontinuous Fluidized Bed

A mathematical model is chosen and a finite-difference algorithm is developed to describe the drying of agro products in a batch fluidized bed. The mathematical model is discretized according to the implicit scheme for two particle geometries: sphere and chip. The system of algebraic equations is solved using the tridiagonal matrix algorithm (TDMA). Stability and convergence of the numerical algorithm are analyzed by variation of the time step and mesh size, finding computer time savings when using nonuniform space steps and boundary conditions are discretized using three nodal positions. Obtained results are compared with numerical results from the literature and experimental data of potato chips drying, concluding that the chosen model describes the phenomena correctly.
Female directors, board-gender quotas and firm performance: evidence from Norway

The opponents to board gender quotas point out the utility argu-ment, according to which, the impossibility of appointing the best candidates will have a negative impact on firm performance. Norway is the case study to investigate the impact of board gender quota regulations on firm performance. Because a gender quota was voluntary from 2004 to 2006 and mandatory afterwards, it allows us to investigate the respective impact of voluntary and mandatory gender quota regulations. The research design takes advantage of this unique research setting and implements difference-in-differences estimations. Previous studies examining the Norwegian context, however, do not differentiate between the voluntary and mandatory implementation of the quota. After controlling for several methodological issues that were unnoticed by these studies, we report sound evidence that the Norwegian quota did not have any negative impact on firm performance. Furthermore, results also suggest that when the quota was applied voluntarily, it had some positive effects on performance. These findings contradict most of the extant evidence and have interesting implications.
Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans

Future sea‐level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea‐level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea‐level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, LA. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea‐level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50‐year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans.
Footpoints of the giant molecular loops in the galactic center region

Deutsche Forschungsgemeinschaft (DFG) DGI AYA 2008-06181-C02-02 CONICYT PFB-06 MINECO AYA2010-2169-C04-01 FIS2012-39162-C06-01 ESP2013-47809-C03-01 ESP2015-65597-C4-1 Australian Government Australian Research Council
The Stellar Content of Obscured Galactic Giant H II Regions. IV. NGC 3576

We present deep, high angular resolution, near-infrared images of the obscured Galactic giant H II region NGC 3576. Our images reach objects to ∼3 M⊙. We collected high signal-to-noise K-band spectra of eight of the brightest objects, some of which are affected by excess emission and some of which follow a normal interstellar reddening law. None of them displayed photospheric features typical of massive OB-type stars. This indicates that they are still enshrouded in their natal cocoons. The K-band brightest source (NGC 3576 No. 48) shows CO 2.3 μm band head emission, and three others have the same CO feature in absorption. Three sources display spatially unresolved H2 emission, suggesting dense shocked regions close to the stars. We conclude that the remarkable object NGC 3576 No. 48 is an early B/late O star surrounded by a thick circumstellar disk/envelope. A number of other relatively bright cluster members also display excess emission in the K-band, indicative of reprocessing disks around massive stars (YSOs). Such emission appears to be common in other Galactic giant H II regions we have surveyed. The initial mass function slope of the cluster, Γ = -1.62, is consistent with Salpeter's distribution and similar to what has been observed in the Magellanic Cloud clusters and in the periphery of our Galaxy.
Mass-loss rates from mid-infrared excesses in LMC and SMC O stars

We use a combination of BVJHK and Spitzer [3.6], [5.8] and [8.0] photometry to determine infrared (IR) excesses for a sample of 58 Large Magellanic Cloud and 46 Small Magellanic Cloud O stars. This sample is ideal for determining IR excesses because the very small line-of-sight reddening minimizes uncertainties due to extinction corrections. We use the core–halo model developed by Lamers & Waters to translate the excesses into mass-loss rates and demonstrate that the results of this simple model agree with the more sophisticated CMFGEN models to within a factor of 2. Taken at face value, the derived mass-loss rates are larger than those predicted by Vink et al., and the magnitude of the disagreement increases with decreasing luminosity. However, the IR excesses need not imply large mass-loss rates. Instead, we argue that they probably indicate that the outer atmospheres of O stars contain complex structures and that their winds are launched with much smaller velocity gradients than normally assumed. If this is the case, it could affect the theoretical and observational interpretations of the ‘weak wind’ problem, where classical mass-loss indicators suggest that the mass-loss rates of lower luminosity O stars are far less than expected.
Galaxy groups in the 2dFGRS: the group-finding algorithm and the 2PIGG catalogue

The construction of a catalogue of galaxy groups from the 2-degree Field Galaxy Redshift Survey (2dFGRS) is described. Groups are identified by means of a friends-offriends percolation algorithm which has been thoroughly tested on mock versions of the 2dFGRS generated from cosmological N-body simulations. The tests suggest that the algorithm groups all galaxies that it should be grouping, with an additional 40 per cent of interlopers. About 55 per cent of the � 190000 galaxies considered are placed into groups containing at least two members of which � 29000 are found. Of these, � 7000 contain at least four galaxies, and these groups have a median redshift of 0.11 and a median velocity dispersion of 260kms 1 . This 2dFGRS Percolation-Inferred Galaxy Group (2PIGG) catalogue represents the largest available homogeneous sample of galaxy groups. It is publicly available on the WWW.
AUV Dynamic Obstacle Avoidance Method Based on Improved PPO Algorithm

Designing a reasonable obstacle avoidance method for AUV 3D path planning is difficult, and existing obstacle avoidance methods have certain drawbacks. For example, they are only applicable to 2D planar applications and cannot effectively handle dynamic obstacles. To address these problems, we design an obstacle collision prediction model (CPM). Based on the results of the simulation of obstacles’ inertial motion, the safety of the AUV navigation is evaluated to improve the model’s sensitivity to dynamic obstacles. Then, we enhance the learning ability of the sequence sample data by combining it with a long short-term memory (LSTM) network, thus improving the training efficiency and effect of the algorithm. The trained proximal policy optimization (PPO) network can output reasonable actions in order to control the AUV to avoid obstacles, forming an AUV 3D dynamic obstacle avoidance strategy based on the CPM-LSTM-PPO algorithm. The simulation results show that the proposed algorithm has good generalization in uncertain environments. Moreover, it achieves dynamic AUV obstacle avoidance in different three-dimensional unknown environments, providing theoretical and technical support for real path planning.
Modified Harris Hawks optimizer for feature selection and support vector machine kernels

The support vector machine (SVM), one of the most effective learning algorithms, has many real-world applications. The kernel type and its parameters have a significant impact on the SVM algorithm's effectiveness and performance. In machine learning, choosing the feature subset is a crucial step, especially when working with high-dimensional data sets. These crucial criteria were treated independently in the majority of earlier studies. In this research, we suggest a hybrid strategy based on the Harris Hawk optimization (HHO) algorithm. HHO is one of the lately suggested metaheuristic algorithms that has been demonstrated to be used more efficiently in facing some optimization problems. The suggested method optimizes the SVM model parameters while also locating the optimal features subset. We ran the proposed approach HHO-SVM on real biomedical datasets with 17 types of cancer for Iraqi patients in 2010-2012. The experimental results demonstrate the supremacy of the proposed HHO-SVM in terms of three performance metrics: feature selection accuracy, runtime, and number of selected features. The suggested method is contrasted with four well-known algorithms for verification: firefly (FF) algorithm, genetic algorithm (GA), grasshopper optimization algorithm (GOA), and particle swarm algorithm (PSO). The implementation of the proposed HHO-SVM approach reveals 99.967% average accuracy.
Power law distribution of discharge in ideal networks

Data for several river networks show algebraically decaying distribution functions for the mean annual discharge and the dissipation rate (Rodriguez-Iturbe et al., 1992). We derive a relation between the exponent a in the integrated mean annual discharge distribution P(Q ≥ q) ∼ q−α and the topological dimension Dt of the network, α = 1 − 1/Dt. Using the experimentally determined value Dt ≈ 1.8 (Tarboton et al., 1988) we find α ≈ 0.45, in good agreement with the data of (Rodriguez-Iturbe et al., 1992). For the random model (Shreve, 1967, 1969; Smart and Werner, 1974) we find an exponent of 1/2.