Miracle-dz/UniFAR-FTUs huggingface dataset:
A GLOBAL PHYSICAL MODEL FOR CEPHEIDS

We perform a global fit to ∼5000 radial velocity and ∼177, 000 magnitude measurements in 29 photometric bands covering 0.3 μm to 8.0 μm distributed among 287 Galactic, Large Magellanic Cloud, and Small Magellanic Cloud Cepheids with P > 10 days. We assume that the Cepheid light curves and radial velocities are fully characterized by distance, reddening, and time-dependent radius and temperature variations. We construct phase curves of radius and temperature for periods between 10 and 100 days, which yield light-curve templates for all our photometric bands and can be easily generalized to any additional band. With only four to six parameters per Cepheid, depending on the existence of velocity data and the amount of freedom in the distance, the models have typical rms light and velocity curve residuals of 0.05 mag and 3.5 km s−1. The model derives the mean Cepheid spectral energy distribution and its derivative with respect to temperature, which deviate from a blackbody in agreement with metal-line and molecular opacity effects. We determine a mean reddening law toward the Cepheids in our sample, which is not consistent with standard assumptions in either the optical or near-IR. Based on stellar atmosphere models, we predict the biases in distance, reddening, and temperature determinations due to the metallicity and quantify the metallicity signature expected for our fit residuals. The observed residuals as a function of wavelength show clear differences between the individual galaxies, which are compatible with these predictions. In particular, we find that metal-poor Cepheids appear hotter. Finally, we provide a framework for optimally selecting filters that yield the smallest overall errors in Cepheid parameter determination or filter combinations for suppressing or enhancing the metallicity effects on distance determinations. We make our templates publicly available.
SHORT- AND LONG-TERM RADIO VARIABILITY OF YOUNG STARS IN THE ORION NEBULA CLUSTER AND MOLECULAR CLOUD

We have used the Karl G. Jansky Very Large Array (VLA) to carry out multi-epoch radio continuum monitoring of the Orion Nebula Cluster (ONC) and the background Orion Molecular Cloud (OMC; 3 epochs at Q band and 11 epochs at Ka band). Our new observations reveal the presence of 19 radio sources, mainly concentrated in the Trapezium Cluster and the Orion Hot Core (OHC) regions. With the exception of the Becklin–Neugebauer object and source C (which we identify here as dust emission associated with a proplyd) the sources all show radio variability between the different epochs. We have found tentative evidence of variability in the emission from the massive object related to source I. Our observations also confirm radio flux density variations of a factor >2 on timescales of hours to days in five sources. One of these flaring sources, OHC-E, has been detected for the first time. We conclude that the radio emission can be attributed to two different components: (i) highly variable (flaring) non-thermal radio gyrosynchrotron emission produced by electrons accelerated in the magnetospheres of pre-main-sequence low-mass stars and (ii) thermal emission due to free–free radiation from ionized gas and/or heated dust around embedded massive objects and proplyds. Combining our sample with other radio monitoring at 8.3 GHz and the X-ray catalog provided by Chandra, we have studied the properties of the entire sample of radio/X-ray stars in the ONC/OMC region (51 sources). We have found several hints of a relation between the X-ray activity and the mechanisms responsible for (at least some fraction of) the radio emission. We have estimated a radio flaring rate of ∼0.14 flares day−1 in the dense stellar cluster embedded in the OHC region. This suggests that radio flares are more common events during the first stages of stellar evolution than previously thought. The advent of improved sensitivity with the new VLA and ALMA will dramatically increase the number of stars in young clusters detected at radio wavelengths, which will help us improve our understanding of the origin and nature of the radio emission.
Optimization of the Ultrasound Operating Conditions for Extraction and Quantification of Fructooligosaccharides from Garlic (Allium sativum L.) via High-Performance Liquid Chromatography with Refractive Index Detector

Dietary interventions have captured the attention of nutritionists due to their health-promoting aspects, in addition to medications. In this connection, supplementation of nutraceuticals is considered as a rational approach to alleviating various metabolic disorders. Among novel strategies, prebiotic-supplemented foods are an encouraging trend in addressing the issue. In the present investigation, prebiotic fructooligosaccharides (FOS) were extracted from garlic (Allium sativum L.) powder using ultrasound-assisted extraction (UAE). The response surface methodology (RSM) was used to optimize the independent sonication variables, i.e., extraction temperature (ET, 80, 90, and 100 °C), amplitude level (AL, 70, 80, and 90%) and sonication time (ST, 10, 15 and 20 min). The maximum FOS yield (6.23 ± 0.52%) was obtained at sonication conditions of ET (80 °C), AL (80%) and ST (10 min), while the minimum yield of FOS was obtained at high operating temperatures and time. The optimized FOS yield (7.19%) was obtained at ET (80 °C), AL (73%) and ST (15 min) after model validation. The influence of sonication parameters, i.e., ET, AL and ST, on FOS yield was evaluated by varying their coded levels from −1 to +1, respectively, for each independent variable. High-performance liquid chromatography with refractive index detector (HPLC-RID) detection and quantification indicated that sucrose was present in high amounts (2.06 ± 0.10 g/100 g) followed by fructose and glucose. Total FOS fractions which included nystose present in maximum concentration (526 ± 14.7 mg/100 g), followed by 1-kestose (428 ± 19.5 mg/100 g) and fructosylnystoses (195 ± 6.89 mg/100 g). Conclusively, garlic is a good source of potential prebiotics FOS and they can be extracted using optimized sonication parameters using ultrasound-assisted techniques with maximum yield percentage.
Nonclassical Nucleation of Zinc Oxide from a Physically Motivated Machine-Learning Approach

Observing non-classical nucleation pathways remains challenging in simulations of complex materials with technological interests. This is because it requires very accurate force fields that can capture the whole complexity of their underlying interatomic interactions and an advanced structural analysis. Here, we first report the construction of a machine-learning force field for zinc oxide interactions using the Physical LassoLars Interaction Potentials approach which allows us to be predictive even for untrained structures. Then, we carried out freezing simulations from a liquid and observed the crystal formation with atomistic precision. Our results, which are analyzed using a data-driven approach based on bond order parameters, demonstrate the presence of both prenucleation clusters and two-step nucleation scenarios thus retrieving seminal predictions of non-classical nucleation pathways made on much simpler models.
Multi-Object Detection Method in Construction Machinery Swarm Operations Based on the Improved YOLOv4 Model

To handle the problem of low detection accuracy and missed detection caused by dense detection objects, overlapping, and occlusions in the scenario of complex construction machinery swarm operations, this paper proposes a multi-object detection method based on the improved YOLOv4 model. Firstly, the K-means algorithm is used to initialize the anchor boxes to improve the learning efficiency of the depth features of construction machinery objects. Then, the pooling operation is replaced with dilated convolution to solve the problem that the pooling layer reduces the resolution of feature maps and causes a high missed detection rate. Finally, focus loss is introduced to optimize the loss function of YOLOv4 to improve the imbalance of positive and negative samples during the model training process. To verify the effectiveness of the above optimizations, the proposed method is verified on the Pytorch platform with a self-build dataset. The experimental results show that the mean average precision(mAP) of the improved YOLOv4 model for multi-object detection of construction machinery can reach 97.03%, which is 2.16% higher than that of the original YOLOv4 detection network. Meanwhile, the detection speed is 31.11 fps, and it is reduced by only 0.59 fps, still meeting the real-time requirements. The research lays a foundation for environment perception of construction machinery swarm operations and promotes the unmanned and intelligent development of construction machinery swarm operations.
Exploring the Potential Tourism Objects in the Small City of Heritage Lasem

Lasem is a small town that has the potential to be a tourist destination. Located on the northern coast of Java, Lasem has three types of landscapes, namely coastal landscapes, topographical landscapes, and mountainous landscapes. The purpose of this paper is to explore the potential of tourist objects that can be developed for tourists who have an interest in visiting Lasem. The method used is descriptive qualitative with field observations and direct interviews with visitors. There are several potential tourist objects that have been explored, such as potential natural attractions, potential cultural attractions, potential social attractions, and potential attractions that are built. The results of this study are the potential natural attractions obtained from the Lasem city landscape, such as the Lasem riverbank, Caruban beach tourism, Dasun, Karangjahe, Binangun, and Watu Layar. Potential cultural attractions such as ancient buildings are the result of cultural products in the past. The products of these buildings include places of worship (three ancient pagodas, Ratanava Arama monastery, Jami' mosque, etc.) and houses with Chinese, Indies, and Javanese architecture. In addition, there is the potential of Lasem batik, which can be featured as a product of Lasem culture and the Lasem carnival festival. For potential social appeal, several community activities can be found in Lasem, namely New Year celebrations and Cap Go Meh, Ceng Beng celebrations, and others. While the potential attraction that was built is the Jami' mosque complex, where in it there is the main building, pawestren, porch, tomb complex, additional foyer, and also the Nusantara museum. Of the three existing landscapes, the topographical landscape that has the most potential is visited because, in this landscape, there is potential for cultural attraction, the potential for social attraction, and potential for an attraction that is built.
The Effects of Varied and Non-Varied Praise on Student On-Task Behaviors

Research has demonstrated that behavior specificity is a salient characteristic of teacher praise efficacy. Praise variety may also be an important characteristic to reinforce desired student behavior based on research about the quality of reinforcers. In this study, we used an alternating treatments design to examine the effects of varied and non-varied behavior-specific praise (BSP) on two first-grade students’ on-task behaviors in U.S. general education classrooms. Visual and statistical analyses suggest both varied and non-varied BSP increased on-task behavior, with varied BSP resulting in marginally higher levels of on-task behavior. There was no functional relationship between varied and non-varied BSP conditions. Findings from this study contribute to teacher praise literature as the first to empirically investigate the effects of praise variety on student behavior. We discuss the implications of this preliminary research and encourage future inquiry into additional characteristics of praise.
Synthesis of Zinc Oxide (ZnO)-Titanium Dioxide (TiO2)-Chitosan-Farnesol Nanocomposites and Assessment of Their Anticancer Potential in Human Leukemic MOLT-4 Cell Line

Leukemia is the most prevalent cancer in children and one of the most common and deadly cancers that affect adults. Several metal oxide nanoparticles, biopolymers, and phytochemicals have been discovered to target cancer cells selectively while inflicting low to no damage to healthy cells. Among the existing nanoparticle synthesis methodologies, biologically synthesized nanoparticles using phytochemicals have emerged as a straightforward, economical, and environmentally sound strategy. The synergistic antitumor potential of ZnO-TiO2-chitosan-farnesol nanocomposites (NCs) against leukemia MOLT-4 cells was investigated in the current study. After synthesizing the NCs, characterization of the same was carried out using XRD, DLS, FESEM, TEM, PL, EDX, and FTIR spectroscopy. To analyze its anticancer activity, MOLT-4 cells were cultured and treated at diverse dosages of NCs. The cell viability upon treatment was examined by MTT assay. The morphological and nuclear modifications were observed by dual staining. ROS and MMP levels were observed by DCFH-DA staining and Rh-123 dye, respectively. Furthermore, the caspase 3, 8, and 9 levels were examined by performing ELISA. The XRD patterns exhibited a hexagonal structure of the NCs. In the DLS spectrum, the hydrodynamic diameter of the NCs was observed to be 126.2 nm. The electrostatic interface between the ZnO-TiO2-chitosan-farnesol NCs was confirmed by the FTIR spectra. A significant loss of cell viability in a dosage-dependent trend confirmed the cytotoxic effect of the NCs. An elevated ROS level and MMP depletion suggested apoptosis-associated cell death via the intrinsic pathway, which was confirmed by elevated expressions of caspase 3, 8, and 9 markers. Thus, the results showed that the synthesized NCs demonstrated a remarkable anticancer potential against leukemic cells and can be potentially valuable in cancer treatments. The findings from this study conclude that this is a new approach for modifying the physicochemical characteristics of ZnO-TiO2-chitosan-farnesol composites to increase their properties and synergistically exhibit anticancer properties in human leukemic cancer cells.
VLT/UVES observations of peculiar alpha abundances in a sub-DLA at z ~ 1.8 towards the quasar B1101-26

We present a detailed analysis of chemical abundances in a sub-damped Lyman alpha absorber at z=1.839 towards the quasar B1101-26, based on a very-high-resolution (R ~ 75,000) and high-signal-to-noise (S/N >100) spectrum observed with the UV Visual Echelle spectrograph (UVES) installed on the ESO Very Large Telescope (VLT). The absorption line profiles are resolved into a maximum of eleven velocity components spanning a rest-frame velocity range of 200 km/s. Detected ions include CII, CIV, NII, OI, MgI, MgII, AlII, AlIII, SiII, SiIII, SiIV, FeII, and possibly SII. The total neutral hydrogen column density is log N(HI) = 19.48 +/- 0.01. From measurements of column densities and Doppler parameters we estimate element abundances of the above-given elements. The overall metallicity, as traced by [OI/HI], is -1.56 +/- 0.01. For the nitrogen-to-oxygen ratio we derive an upper limit of [NI/OI] < -0.65, which suggests a chemically young absorption line system. This is supported by a supersolar alpha/Fe ratio of [SiII/FeII] ~ 0.5. The most striking feature in the observed abundance pattern is an unusually high sulphur-to-oxygen ratio of 0.69 < [SII/OI] < 1.26. We calculate detailed photoionisation models for two subcomponents with Cloudy, and can rule out that ionisation effects alone are responsible for the high S/O ratio. We instead speculate that the high S/O ratio is caused by the combination of several effects, such as specific ionisation conditions in multi-phase gas, unusual relative abundances of heavy elements, and/or dust depletion in a local gas environment that is not well mixed and/or that might be related to star-formation activity in the host galaxy. We discuss the implications of our findings for the interpretation of alpha-element abundances in metal absorbers at high redshift.
High-pressure Raman study of the charge ordering in α-(BEDT-TTF)2I3

Charge distributions in the donor layer for the paramagnetic semimetal-like and nonmagnetic insulating phases of the α-(BEDT-TTF) 2 I 3 single crystal [BEDT-TTF: bis(ethylenedithiolo)tetrathiafulvalene] were investigated under quasihydrostatic pressures up to 3.6 GPa using Raman spectroscopy. The results confirmed the appearance of charge disproportionation below the metal-insulator phase transition temperature (T M I ). The average charge-disproportionation ratio, 0.2-0.8, at ambient pressure was quite pressure sensitive and decreased by ca. 0.1e/GPa with increasing pressure. This result is ascribed to the faster increase of the transfer integrals than the intersite Coulomb repulsions under pressure. The loss of the inversion centers in the nonmagnetic insulating phase, concluded by the selection rule, suggests that the charge is ordered such that it forms a so-called horizontal stripe. Nonuniform charge distributions were also found at temperatures above T M I for the paramagnetic semimetal-like phase. The experimentally determined small charge difference among BEDT-TTF at crystallographically nonequivalent sites is consistent with the band calculations.
GeV BREAKS IN BLAZARS AS A RESULT OF GAMMA-RAY ABSORPTION WITHIN THE BROAD-LINE REGION

Spectra of the brightest blazars detected by the Fermi Gamma-ray Space Telescope Large Area Telescope cannot be described by a simple power-law model. A much better description is obtained with a broken power law, with the break energies of a few GeV. We show here that the sharpness and the position of the breaks can be well reproduced by absorption of γ-rays via photon–photon pair production on He ii Lyman recombination continuum and lines. This implies that the blazar zone lies inside the region of the highest ionization of the broad-line region (BLR) within a light-year from a super-massive black hole. The observations of γ-ray spectral breaks open a way of studying the BLR photon field in the extreme-UV/soft X-rays, which are otherwise hidden from our view.
Construction of Realistic Place-and-Route Benchmarks for Machine Learning Applications

Many design optimization methods using machine learning (ML) techniques have been investigated to reduce the number of design iterations in the physical design flow. The demand for big data to support ML research has been increasing, but the lack of place-and-route (P&R) benchmarks is one of the major problems. We propose a framework to construct realistic P&R benchmarks for use in training ML applications. The framework can organize the P&R database using an artificial netlist generator, which can create any gate-level netlist from user-specified input parameters that represent the topological characteristics of the circuit. We show that a training dataset that contains many artificial gate-level netlists can improve the generalizability of the model to predict the routability for unseen real circuits without using expensive real-world data. Compared to the model that had been trained with real-world circuits, we improved the F1 score in predicting the timing and routing failure by 26.4% and 54.5%, respectively.
Point Cloud Completion Network Applied to Vehicle Data

With the development of autonomous driving, augmented reality, and other fields, it is becoming increasingly important for machines to more accurately and comprehensively perceive their surrounding environment. LiDAR is one of the most important tools used by machines to obtain information about the surrounding environment. However, because of occlusion, the point cloud data obtained by LiDAR are not the complete shape of the object, and completing the incomplete point cloud shape is of great significance for further data analysis, such as classification and segmentation. In this study, we examined the completion of a 3D point cloud and improved upon the FoldingNet auto-encoder. Specifically, we used the encoder–decoder architecture to design our point cloud completion network. The encoder part uses the transformer module to enhance point cloud feature extraction, and the decoder part changes the 2D lattice used by the A network into a 3D lattice so that the network can better fit the shape of the 3D point cloud. We conducted experiments on point cloud datasets sampled from the ShapeNet car-category CAD models to verify the effectiveness of the various improvements made to the network.
Multiplicity Distributions in Proton-(Anti)Proton and Electron-positron Collisions with Parton Recombination

A new approach to phenomenological description of the charged particle multiplicity distributions in proton-(anti)proton and electron-positron collisions is presented. The observed features of the data are interpreted on the basis of stochastic-physical ideas of multiple production. Besides the processes of parton immigration and absorption, two and three patron incremental and decremental recombinations are considered. The complex behaviour of the multiplicity distributions at different energies is described by four parametric generalized hypergeometric distribution (GHD). Application of the proposed GHD to data measured by the CMS, ALICE, and ATLAS Collaborations suggests that soft multiparton recombination processes can manifest itself significantly in the structure of multiplicity distribution in pp interactions at very high energies.
Mixed population of competing TASEPs with a shared reservoir of particles

We introduce a mean-field theoretical framework to describe multiple totally asymmetric simple exclusion processes (TASEPs) with different lattice lengths, entry and exit rates, competing for a finite reservoir of particles. We present relations for the partitioning of particles between the reservoir and the lattices: these relations allow us to show that competition for particles can have non-trivial effects on the phase behavior of individual lattices. For a system with non-identical lattices, we find that when a subset of lattices undergoes a phase transition from low to high density, the entire set of lattice currents becomes independent of total particle number. We generalize our approach to systems with a continuous distribution of lattice parameters, for which we demonstrate that measurements of the current carried by a single lattice type can be used to extract the entire distribution of lattice parameters. Our approach applies to populations of TASEPs with any distribution of lattice parameters, and could easily be extended beyond the mean-field case. We show behavior, including extension of the shock phase to a finite region of parameter space, and “buffering” of individual currents to changes in the reservoir particle number, can emerge from the competition between lattices for particles. We further show that in these systems,
Calculation of 2D electronic band structure using matrix mechanics

We extend previous work, applying elementary matrix mechanics to one-dimensional periodic arrays (to generate energy bands), to two-dimensional arrays. We generate band structures for the square-lattice “2D Kronig-Penney model” (square wells), the “muffin-tin” potential (circular wells), and Gaussian wells. We then apply the method to periodic arrays of more than one atomic site in a unit cell, specifically to the case of materials with hexagonal lattices like graphene. These straightforward extensions of undergraduate-level calculations allow students to readily determine band structures of current research interest.