Miracle-dz/UniFAR-FTUs huggingface dataset:
Models of optical emission lines to investigate Narrow-Line Seyfert 1 galaxies in spectroscopic databases

Thanks to the execution of extensive spectroscopic surveys that have covered large fractions of the sky down to magnitudes as faint as $i \approx 19$, it has been possible to identify several narrow-line Seyfert 1 galaxies (NLS1s) and to investigate their properties over a large range of the electro-magnetic spectrum. The interpretation of their nature, however, is still hampered by the statistical uncertainties related to the way in which NLS1 candidates are selected. In this contribution, we present a study to detect and to model emission lines in optical spectra extracted from the Sloan Digital Sky Survey (SDSS), adopting the most proper strategy to identify the source of line excitation and to produce a detailed model with measurements of several emission-line parameters. We demonstrate the application of this technique to explore fundamental questions, such as the presence of gas and dust around the core of AGNs and the spectral energy distribution of their ionizing radiation. We compare the spectral properties of NLS1s with those of other type 1 active galaxies and we summarize the potential of this approach to identify NLS1s in present day and future spectroscopic surveys. We finally consider the implications of multi-frequency data analysis in the debate concerning the intrinsic nature of NLS1s.
Osun Worshipers in Osogbo: An Analysis of the Factors Influencing Participations of the Osun Festival in Southwestern Nigeria

This study investigates the factors influencing the Osun festival participation in southwestern Nigeria. Primary data was collected through questionnaire administration on members of the host communities. Secondary data on the number of buildings were obtained from the high-resolution satellite imagery and maps sourced from the Cooperative Information Network (COPINE) of the National Space Research and Development Agency (NASRDA). A systematic sampling procedure was adopted to select 3% of the estimated 10,913 buildings within the designated zones in Osogbo based on the degree of homogeneity of the inhabitants. In this case, 327 respondents were sampled in Osogbo. Data collected were analyzed using Mean Index (MI) and Factor analysis (Principal component analysis). Findings revealed that 45 out of the 49 variables subjected to factor analysis contributed to explaining 79.8% variation of factors influencing participation in the Osun festival. They are categorized under four factors: Sociodemographic, Psychosocial, Basic Facilities/Amenities, and Environmental /Mobility Factors.
Visualizing the Motion of a Unicycle on a Sphere

Abstract The kinematics, dynamics, and control of a unicycle (with yaw and roll inputs) moving without slip on a planar surface has been studied extensively in the geometric mechanics and nonholonomic literature. This paper considers the kinematic extension to the case of a unicycle moving on a nonplanar surface: specifically, a spherical surface and the associated visualization, including use of computer-aided design (CAD) software packages (e.g., SolidWorks® & MATLAB®). Such a scenario allows one to move closer to an understanding of the motion of an actual multiwheeled vehicle traversing nonplanar surfaces that may be approximated as spherical surface patches as well the realistic portrayal of virtual vehicles in computer graphics environments, in addition to other applications, such as those that employ kinematic inversion (e.g., industrial web handling). Differential equations of motion are derived based on the nonholonomic no-slip constraint and spherical trigonometry from which the associated Lie algebra is revealed and a related example foliation formulation is illustrated that offers further generalization. For a fixed body yaw rate it is shown that a circular trajectory of a specific radius results — this can also form the basis of an instantaneous centre integration (ICI) algorithm. Numerical studies designed to exercise the equations of motion (using MATLAB® and SIMULINK®) were performed based on combinations of several different types of input trajectories: constant, non-infinitesimal Lie bracket manoeuvres, sinusoidal, and that induced by a prescribed contact point trajectory. Finally, the resulting interesting motions were plotted in 2D and 3D and provide a source of qualitative corroboration of the equations in addition to computer-generated artwork.
Duration of Daytime Napping Is Related to Physical Fitness among Chinese University Students

Reportedly, daytime napping affects the physical fitness of athletes. However, results of these studies are conflicting, and may not be generalizable to all populations. Early adulthood is an important period linking adolescents and adults, during which building good physical fitness is crucial for their remaining lives. Thus, we investigated whether daytime napping duration is associated with physical fitness among Chinese university students. This study was based on an annual physical health examination for all university students and included 11,199 participants (6690 males; 4509 females). The daytime napping duration was assessed using a self-report questionnaire. Physical fitness was measured with a 50 m sprint; 1000 m (for males) and 800 m (for females) runs; standing long jump, sit-and-reach, pull-up (for males), and sit-up (for females) tests; and vital capacity. The adjusted association was evaluated using analysis of covariance. Of the participants, 86% napped regularly. After covariate adjustment was performed, significant V-shaped associations were observed between the daytime napping duration and the 50 m sprint and 800 m run results in males and females. Inverted V-shaped associations were observed between the daytime napping duration and the sit-and-reach, standing long jump, and pull-up test performances and vital capacity in males and between the daytime napping duration and the standing long jump test performance in females. Daytime napping for <30 min may have beneficial effects on physical fitness among university students.
Challenges in Business Analytics Implementation: A Comprehensive Review Using Toe Framework

Business analytics are changing how firms treat data. Using analytics, firms possess the capability to capture greater insights and predict the future, hence better decision-making process. However, the implementation of analytics in business has to be carried within the complexity of organization, technology, and environment. Given the complexity, this study aims to identify the challenge faced by firms across industries. The TOE framework is utilized to construct a more comprehensive framework of the challenges. Past studies related to implementation of business analytics are gathered and processed using literature review method. This study helps Asian firms to be more anticipative by providing a holistic and clearer view of challenges in adopting business analytics.
Design of an auxiliary system for quality review of wind turbine operation and maintenance based on deep learning image recognition

The cost of operation and maintenance(O&M) has been one of the central budgets in the wind turbines' life cycle. In the final stage of the O&M work, the administrators must manually review the on-site photos to ensure the O&M is qualified, which is time-consuming and ineffective. To improve the efficiency and quality of O&M reviewing work while reducing its costs, we propose an auxiliary reviewing system to optimize the reviewing process. Our system architecture consists of data collection, analysis, and presentation modules. During day times, the data collection module will handle storing and organizing the photos of O&M. The data analysis module will perform duplicate image detection using the MessageDigest Algorithm 5(MD5) and missed image detections through the pre-trained ResNet50 deep learning model. The review results from the analysis module will be fully updated to the database after the analyzing process and rendered into graphs or tables on the webpage when required by the reviewers. Analyses are done in this paper to visualize the functions of each module of the proposed system. The experiment evaluates the performance of three deep learning models, including AlexNet, VGG16, and ResNet50, based on authentic on-site inspection images data from our "first annual inspection" dataset to determine which model yields the best image classification performance. The experimental result reveals that ResNet50 can reach the highest accuracy at 96.2% on the test dataset. Thus, we choose ResNet50 to train the image classifier of our data analysis module.
Proteomic Analysis of the Predatory Venom of Conus striatus Reveals Novel and Population-Specific κA-Conotoxin SIVC

Animal venoms are a rich source of pharmacological compounds with ecological and evolutionary significance, as well as with therapeutic and biotechnological potentials. Among the most promising venomous animals, cone snails produce potent neurotoxic venom to facilitate prey capture and defend against aggressors. Conus striatus, one of the largest piscivorous species, is widely distributed, from east African coasts to remote Polynesian Islands. In this study, we investigated potential intraspecific differences in venom composition between distinct geographical populations from Mayotte Island (Indian Ocean) and Australia (Pacific Ocean). Significant variations were noted among the most abundant components, namely the κA-conotoxins, which contain three disulfide bridges and complex glycosylations. The amino acid sequence of a novel κA-conotoxin SIVC, including its N-terminal acetylated variant, was deciphered using tandem mass spectrometry (MS/MS). In addition, the glycosylation pattern was found to be consisting of two HexNAc and four Hex for the Mayotte population, which diverge from the previously characterized two HexNAc and three Hex combinations for this species, collected elsewhere. Whereas the biological and ecological roles of these modifications remain to be investigated, population-specific glycosylation patterns provide, for the first time, a new level of intraspecific variations in cone snail venoms.
Nucleosynthesis Constraints on the Explosion Mechanism for Type Ia Supernovae

Observations of type Ia supernovae (SNe Ia) include information about the characteristic nucleosynthesis associated with these thermonuclear explosions. We consider observational constraints from iron-group elemental and isotopic ratios, to compare with various models obtained with the most realistic recent treatment of electron captures (ECs). The nucleosynthesis is sensitive to the highest white-dwarf central densities. Hence, nucleosynthesis yields can distinguish high-density Chandrasekhar-mass models from lower-density burning models such as white-dwarf mergers. We discuss new results of post-processing nucleosynthesis for two spherical models (deflagration and/or delayed-detonation models) based upon new EC rates. We also consider cylindrical and 3D explosion models (including deflagration, delayed-detonation, or a violent merger model). Although there are uncertainties in the observational constraints, we identify some trends in the observations and the models. We make a new comparison of the models with elemental and isotopic ratios from five observed supernovae and three supernova remnants. We find that the models and data tend to fall into two groups. In one group, low-density cores such as in a 3D merger model are slightly more consistent with the nucleosynthesis data, while the other group is slightly better identified with higher-density cores such as in single-degenerate 1D–3D deflagration models. Hence, we postulate that both types of environments appear to contribute nearly equally to observed SN Ia. We also note that observational constraints on the yields of 54Cr and 54Fe, if available, might be used as a means to clarify the degree of geometrical symmetry of SN Ia explosions.
Resilience of Hybrid Casper Under Varying Values of Parameters

Hybrid Casper is the new Ethereum blockchain protocol that uses both Proof of Work and Proof of Stake to reach a consensus between nodes. Here, we analyse the protocol using PRISM+ , an extension of the probabilistic model checker PRISM with primitives for expressing blockchain data types. First, we extend PRISM+ to include data types and operations for modelling and analysing Proof of Stake-based consensus protocols. Then, we model Hybrid Casper in PRISM+ as a parallel composition of stochastic processes, thus precisely describing the behaviour of the protocol and highlighting its corner cases. PRISM+ is therefore used to rapidly and automatically analyse the resilience of Hybrid Casper when tuning, up or down, several basic parameters of the protocol, such as the rates of creating blocks, and the strategies for determining penalties. Finally, we study the robustness of Hybrid Casper to two well known attacks: the Eclipse attack and the majority attack.
CONSTRAINING ALTERNATIVE THEORIES OF GRAVITY BY GRAVITATIONAL WAVES FROM PRECESSING COMPACT BINARIES

rst time. We perform Monte Carlo simulations and by using the Fisher analysis, we estimate the determination accuracy of binary parameters including the Brans-Dicke parameter and the graviton Compton wavelength. By using LISA, although the constraint on BransDicke theory is several times weaker than the current strongest one, the constraint on the mass of graviton is four orders of magnitude stronger than the one obtained by the solar system experiment.
3D Model Classification Based on GCN and SVM

3D model classification is an important task. Now, 3D model is usually expressed as point cloud. Disorder of point cloud brings great difficulty into 3D model classification. In order to classify 3D model correctly, a new classification method combining Graph Convolution Network (GCN) and Support Vector Machine (SVM) is proposed in this paper. Point cloud is sampled. K-Nearest Neighbor (KNN) algorithm is used to find K nearest points of sampling point, and adjacency matrix is established for graph convolution operation. Shape features D1, D2, D3 and A3 of sampling point are computed based on its K nearest points. Coordinates and shape features of sampling point are combined as discriminative feature. 2-layer graph convolution is used to aggregate disambiguation information of 1-degree and 2-degree adjacent points of sampling point for describing point cloud comprehensively. At the same time, maximum pooling and average pooling are adopted to retain representative information. Finally, SVM is used to classify point clouds. Experimental results show that compared with GCN based on coordinates, the proposed network improves accuracy of 3D model classification by 1.67%. Global and local information can be extracted adequately when 1024 points are sampled from point cloud. When we select 20 nearest points to compute shape features D1, D2, D3, A3, local information of point can be described better. Shape features D1, D2, D3, A3 are combined with coordinates to describe shape and structure of point cloud better. 2-layer graph convolutions are adopted to aggregate information of 1-degree and 2-degree nodes for extracting effective disambiguation features.
Influence of in ovo threonine on growth performance, immunocompetence and carcass characteristics in broiler chickens

The experiment was conducted to investigate the effect of in ovo threonine (Thr) injection on 18th embryonation day at the broad end of the egg using 24G needle on growth performance, organs development, immunocompetence and carcass yield in broiler chickens. Fertile eggs (n=500) were randomly distributed to 5 groups, viz. (i) uninjected control, sham control (0.5 mL sterile water), Thr @15 mg/egg, Thr @30 mg/egg, and Thr @45 mg/egg. Hatchability was better in chicks treated with 45 mg Thr/egg compared to other Thr-injected groups. In ovo Thr injection had quadratic effect on weight gain (WG) and production index at the 2nd and 3rd weeks. Chicks fed 45 mg Thr/egg had better feed conversion ratio (FCR) at 2nd week compared to other groups while feed intake (FI) was not affected. Thr injected chicks had higher thymus weight (d0), bursa weight (d3), spleen weight (d3 and d7) whereas quadratic effect were observed on weights of bursa, thymus and spleen at d21. In ovo Thr administration improved (group-wise, linear or quadratic) the relative weights of gizzard, intestine, and liver at hatch, proventriculus at d7, as well as intestine and liver at d21. No significant difference was recorded for humoral and cell mediated immune response following in ovo Thr injection. Carcass traits of broiler chickens were not influenced by in ovo Thr administration, except breast meat which slightly differs, among the treatment groups. The results of this study suggested that in ovo Thr can improve growth performance, digestive and immune organs development at the early age.
Disrupted Asteroid P/2016 G1. II. Follow-up Observations from the Hubble Space Telescope

After the early observations of the disrupted asteroid P/2016 G1 with the 10.4 m Gran Telescopio Canarias (GTC) and modeling of the dust ejecta, we have performed a follow-up observational campaign of this object using the Hubble Space Telescope (HST) during two epochs (2016 June 28 and July 11). The analysis of these HST images with the same model inputs obtained from the GTC images revealed a good consistency with the predicted evolution from the GTC images, so that the model is applicable to the entire observational period from 2016 late April to early July. This result confirms that the resulting dust ejecta was caused by a relatively short-duration event with onset about 350 days before perihelion and spanning about 30 days (HWHM). For a size distribution of particles with a geometric albedo of 0.15, having radii limits of 1 μm and 1 cm, and following a power-law with index −3.0, the total dust mass ejected is ∼2 × 107 kg. As was the case with the GTC observations, no condensations in the images that could be attributed to a nucleus or fragments released after the disruption event were found. However, the higher limiting magnitude reachable with the HST images in comparison to those from GTC allowed us to impose a more stringent upper limit to the observed fragments of ∼30 m.
Tests of dynamical scaling in three-dimensional spinodal decomposition

We simulate late-stage coarsening of a 3-D symmetric binary fluid. With reduced units l,t (with scales set by viscosity, density and surface tension) our data extends two decades in t beyond earlier work. Across at least four decades, our own and others' individual datasets (< 1 decade each) show viscous hydrodynamic scaling (l ~ a + b t), but b is not constant between runs as this scaling demands. This betrays either the unexpected intrusion of a discretization (or molecular) lengthscale, or an exceptionally slow crossover between viscous and inertial regimes.
Glassy dynamics of kinetically constrained models

We review the use of kinetically constrained models (KCMs) for the study of dynamics in glassy systems. The characteristic feature of KCMs is that they have trivial, often non-interacting, equilibrium behaviour but interesting slow dynamics due to restrictions on the allowed transitions between configurations. The basic question which KCMs ask is therefore how much glassy physics can be understood without an underlying 'equilibrium glass transition'. After a brief review of glassy phenomenology, we describe the main model classes, which include spin-facilitated (Ising) models, constrained lattice gases, models inspired by cellular structures such as soap froths, models obtained via mappings from interacting systems without constraints, and finally related models such as urn, oscillator, tiling and needle models. We then describe the broad range of techniques that have been applied to KCMs, including exact solutions, adiabatic approximations, projection and mode-coupling techniques, diagrammatic approaches and mappings to quantum systems or effective models. Finally, we give a survey of the known results for the dynamics of KCMs both in and out of equilibrium, including topics such as relaxation time divergences and dynamical transitions, nonlinear relaxation, ageing and effective temperatures, cooperativity and dynamical heterogeneities, and finally non-equilibrium stationary states generated by external driving. We conclude with a discussion of open questions and possibilities for future work.
Efficient Variational Quantum Simulator Incorporating Active Error Minimization

One of the key applications for quantum computers will be the simulation of other quantum systems that arise in chemistry, materials science, etc, in order to accelerate the process of discovery. It is important to ask: Can this be achieved using near future quantum processors, of modest size and under imperfect control, or must it await the more distant era of large-scale fault-tolerant quantum computing? Here we propose a variational method involving closely integrated classical and quantum coprocessors. We presume that all operations in the quantum coprocessor are prone to error. The impact of such errors is minimised by boosting them artificially and then extrapolating to the zero-error case. In comparison to a more conventional optimised Trotterisation technique, we find that our protocol is efficient and appears to be fundamentally more robust against error accumulation.
Microscopic theory of weak pseudogap behavior in the underdoped cuprate superconductors: General theory and quasiparticle properties

We use a solution of the spin fermion model which is valid in the quasistatic limit {pi}T{gt}{omega}{sub sf}, found in the intermediate (pseudoscaling) regime of the magnetic phase diagram of cuprate superconductors, to obtain results for the temperature and doping dependence of the single particle spectral density, the electron-spin fluctuation vertex function, and the low frequency dynamical spin susceptibility. The resulting strong anisotropy of the spectral density and the vertex function lead to the qualitatively different behavior of {ital hot} [around {bold k}=({pi},0)] and {ital cold} [around {bold k}=({pi}/2,{pi}/2)] quasiparticles seen in ARPES experiments. We find that the broad high energy features found in ARPES measurements of the spectral density of the underdoped cuprate superconductors are determined by strong antiferromagnetic (AF) correlations and incoherent precursor effects of an SDW state, with reduced renormalized effective coupling constant. Due to this transfer of spectral weight to higher energies, the low frequency spectral weight of {ital hot} states is strongly reduced but couples very strongly to the spin excitations of the system. For realistic values of the antiferromagnetic correlation length, their Fermi surface changes its general shape only slightly but the strong scattering of hot states makes the Fermi surface crossing invisible abovemore » a pseudogap temperature T{sub {asterisk}}. The electron spin-fluctuation vertex function, i.e., the effective interaction of low energy quasiparticles and spin degrees of freedom, is found to be strongly anisotropic and enhanced for hot quasiparticles; the corresponding charge-fluctuation vertex is considerably diminished. We thus demonstrate that, once established, strong AF correlations act to reduce substantially the effective electron-phonon coupling constant in cuprate superconductors. {copyright} {ital 1999} {ital The American Physical Society}« less