Empirical Library Research Articles

Estimating Stellar Atmospheric Parameters and [α/Fe] for LAMOST O-M-type Stars Using a Spectral Emulator

In this paper, we developed a spectral emulator based on the Mapping Nearby Galaxies at Apache Point Observatory Stellar Library (MaStar) and a grouping optimization strategy to estimate effective temperature (T eff), surface gravity (log g), metallicity ([Fe/H]), and the abundance of alpha elements with respect to iron ([α/Fe]) for O-M-type stars within the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-resolution spectra. The primary aim is to use a rapid spectral-fitting method, specifically the spectral emulator with the grouping optimization strategy, to create a comprehensive catalog for stars of all types within LAMOST, addressing the shortcomings in parameter estimations for both cold and hot stars present in the official LAMOST AFGKM-type catalog. This effort is part of our series of studies dedicated to establishing an empirical spectral library for LAMOST. Experimental results demonstrate that our method is effectively applicable to parameter prediction for LAMOST, with the single-machine processing time within 70 hr. We observed that the internal error dispersions for T eff, log g, [Fe/H], and [α/Fe] across different spectral types lie within the ranges of 15–594 K, 0.03–0.27 dex, 0.02–0.10 dex, and 0.01–0.04 dex, respectively, indicating a good consistency. A comparative analysis with external data highlighted deficiencies in the official LAMOST catalog and issues with MaStar parameters, as well as potential limitations of our method in processing spectra with strong emission lines and bad pixels. The derived atmospheric parameters as a part of this work are available via doi:10.12149/101402.

Library resources constraints, frustration, and user behavior: An empirical library operations study.

The lack of requisite library resources has an enormous effect on academic life in most universities. While previous studies have suggested that the lack of resources such as textbooks affects academic success, this study seeks to provide empirical evidence on the chain effect of the lack of recommended textbooks in universities. The study uses a quantitative dataset from 636 students from five public universities in Ghana collected using well-structured questionnaires. The study adopts exploratory factor analysis, confirmatory factor analysis, and partial least squares structural equation modeling (PLS-SEM) to analyze the measurement and structural models. The study concludes that limited library resources (such as recommended textbooks) frustrate library users and eventually birth antisocial behaviors such as stealing, hiding, and eroding books (or pages). This study highlights the significance of providing adequate library resources. It also guides library managers, policymakers, and scholars to manage library resources effectively.

Attention mechanism-aided model ensemble method of chiller energy consumption prediction

The chiller energy consumption prediction plays an important role in reducing the building energy consumption. Continuously improving the performance of the prediction model is the key to ensuring the accuracy of the chiller energy consumption prediction. As a result, a new improved ensemble model of the chiller energy consumption prediction is proposed, based on the idea of algorithmic ensemble aided by an attention mechanism (AM). To guarantee that the proposed model can see information from many spatial and structural viewpoints, the improved ensemble model incorporates the benefits of several base prediction methods. The suggested approach chooses crucial features to simplify the model input by utilizing AM, thereby reducing the complexity of the samples. The improved ensemble model was experimentally verified in an actual multi-chiller system, and the results showed that the established model could obtain good prediction results. Finally, the proposed model was compared with existing, well-known prediction models. To evaluate the accuracy of these models, the mean absolute error (MAE), mean absolute percentage error (MAPE), mean square error (MSE), variance accounted for (VAF), and coefficient of determination (R2) were used as the evaluation indices. With an MAE of 2.858, an MAPE of 1.2755 %, an MSE of 20.1878, a VAF of 93.6058, and an R2 of 0.9923, the findings demonstrate that the improved ensemble model has a greater prediction accuracy than the other well-known prediction methods. The suggested model enhances the variety of empirical model algorithm libraries.

Abstract 4587: Development of highly selective, potent, orally available PIM1 inhibitor BLX0631 shows a therapeutics potential in multiple myeloma models

Abstract Background: The Proto-oncogenic PIMs family are nuclear and cytoplasmic Ser/Thr kinases (PIM1, PIM2, and PIM3) that are constitutively active and play a vital role in proliferation and survival in Multiple Myeloma (MM). Activated PIM1 kinase can induce progression of the cell cycle, inhibition of apoptosis, and modulation of other signal transduction pathways. Methods: BLX-0631 and a few analogs evaluated against a panel of MM cell lines (EJM, IM-9, L-363, LP-1, MM-1R, MM.1S, MOLP-2, NCI-H929, OPM-2, RPMI8226 and U-266) and primary MM patient samples by CellTiter-Glo® (CTG) assays. Cellular apoptosis, Cell cycle analysis, Flow Cytometry, and bone marrow microenvironment experiments on the most sensitive cells were performed. PIM1 and downstream targets by western blot, cell migration, and invasion on our lead PIM1 inhibitor BLX-0631 along with, kinome selectivity, ADME-Tox, PK, and in vivo MM.1S efficacy experiments were conducted. Results: The application of our empirical MolecuLernTM fragment library, PIM1 crystal structure, scaffold hopping, and the enumeration features of MolecuLernTM in combination with 3, 6, and 7-group analysis on pyridazine, lead to a synthesizable potential new lead series, representing Med Chem tractability and developable characteristics. Further, the consensus scoring, binding energies, and MolecuLern tractability filters were applied and led to the discovery of the BLX-0631 series that inhibits the PIM1 kinase. The active compounds, with their binding modes and lead optimization strategies, lead to the synthesis and testing of over 60 novel entities as PIM1 kinase inhibitors. Thus, based on our previous chemotype series and scaffold hopping method, the impact of changing the 3, 6, and 7 positions, while retaining the pyridazine core led to the discovery of BLX-0631 and its series of compounds exhibiting <5 nM potency. BLX-0631 in CTG assay demonstrated 100% cell growth inhibition across all MM cell lines tested. The lead compound BLX-0631 is a very potent inhibitor with an IC50 of 5.0/17/5.0 nM when tested against PIM1, PIM2, and PIM3 kinases respectively, and selective against a panel of 468 kinase panels. Dosing through IV and PO delivery routes, formulations, salt forms of BLX-0631 in mice, PK properties along with ADME-Tox, P450, and hERG results will be presented. In vivo MM.1S mouse xenograft models of BLX-0631 at 15, 30 and 45 mg/Kg, p.o, QD demonstrated TGI of 16.28%, 31.81% & 35.16% dose-dependently. Conclusions: The present study demonstrates that PIM1 plays a vital role in the proliferation and survival of Multiple Myeloma. BLX-0631 induces full inhibition of all MM cell lines, suppresses cancer cell proliferation in vitro, and exhibits promising efficacy in MM tumor models. BLX-0631, a nominated IND candidate can serve as a novel targeted agent for treating Multiple Myeloma patients. Citation Format: Zhaoang li, Chenyu Lin, David J. Bearss, Hariprasad Vankayalapati. Development of highly selective, potent, orally available PIM1 inhibitor BLX0631 shows a therapeutics potential in multiple myeloma models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4587.

SPar: Estimating Stellar Parameters from Multiband Photometries with Empirical Stellar Libraries

Abstract Modern large-scale photometric surveys have provided us with multiband photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (T eff) and metallicities ([Fe/H]), absolute magnitudes (M G ), distances (d), and reddening values (E(G BP − G RP)) is fundamental to study the stellar populations, structure, kinematics, and chemistry of the Galaxy. This work constructed an empirical stellar library that maps the stellar parameters to multiband photometries from a data set with Gaia parallaxes, LAMOST atmospheric parameters, and optical to near-infrared photometry from several photometric surveys. Based on the stellar library, we developed a new algorithm, SPar (Stellar Parameters from multiband photometry), which fits the multiband stellar photometries to derive the stellar parameters (T eff, [Fe/H], M G , d, and E(G BP − G RP)) of the individual stars. The algorithm is applied to the multiband photometric measurements of a sample of stars selected from the SMSS survey, which have stellar parameters derived from the spectroscopic surveys. The stellar parameters derived from multiband photometries by our algorithm are in good agreement with those from the spectroscopic surveys. The typical differences between our results and the literature values are 170 K for T eff, 0.23 dex for [Fe/H], 0.13 mag for M G , and 0.05 mag for E(G BP − G RP). The algorithm proved to be robust and effective and will be applied to the data of future large-scale photometric surveys such as the Mephisto and CSST surveys.

The study of ionic conductivity of the Li10GeP2S12 type Solid State Electrolyte by an extrapolation method and a deep-learning method

An extrapolation method is usually applied when Ab initio molecular dynamics (AIMD) is applied to studying ionic conductivity in solid-state electrolytes in lithium-ion batteries. As the ions move slowly in solid-state electrolytes, the first-principles method typically involves computationally intensive calculations, and it can take significant time to obtain accurate results. First-principles method is too expensive for the time scale required at room temperature. The classical molecular dynamics method is typically applied to systems containing thousands of atoms and can simulate the system’s behavior over nanoseconds. During the simulation, the positions and velocities of the atoms are updated at discrete time intervals, allowing the system’s behavior to be studied over time. However, its accuracy depends on the empirical force-field libraries. Limited by the computational resource, the previous studies applied the extrapolation method to obtain the room temperature ionic conductivity, which was not accurate because the linear relationship in the Arrhenius equation was not valid in a wide range of temperatures. Deepmd-Kit is a tool that integrates these two different computational approaches. The extrapolation and Deepmd methods were applied to the materials Li10GeP2S12, Li10SiP2S12, Li10GePS12Cl, and Li10SiPS12Cl, respectively. Both methods showed that the lithium ions favor the c direction when diffusing in the LGPS-type solid-state electrolytes. The ionic conductivity is more accurate with the dependent method compared with experiments.

The Stellar Spectra Factory (SSF) Based on SLAM

An empirical stellar spectral library with large coverage of stellar parameters is essential for stellar population synthesis and studies of stellar evolution. In this work, we present Stellar Spectra Factory (SSF), a tool to generate empirical-based stellar spectra from arbitrary stellar atmospheric parameters. The relative flux-calibrated empirical spectra can be predicted by SSF given arbitrary effective temperature, surface gravity, and metallicity. SSF constructs the interpolation approach based on the Stellar LAbel Machine, using ATLAS-A library, which contains spectra covering from O type to M type, as the training data set. SSF is composed of four data-driven sub-models to predict empirical stellar spectra. Sub-model SSF-N can generate spectra from A to K type and some M giant stars, covering 3700 < T eff < 8700 K, 0 < < dex, and −1.5 < [M/H] < 0.5 dex. Sub-model SSF-gM is mainly used to predict M giant spectra with 3520 < T eff < 4000 K and −1.5 < [M/H] < 0.4 dex. Sub-model SSF-dM is for generating M dwarf spectra with 3295 < T eff < 4040 K, −1.0 < [M/H] < 0.1 dex. Sub-model SSF-B can predict B-type spectra with 9000 < T eff < 24,000 K and −5.2 < M G < 1.5 mag. The accuracy of the predicted spectra is validated by comparing the flux of predicted spectra to those with same stellar parameters selected from the known spectral libraries, MILES and MaStar. The averaged difference of flux over optical wavelength between the predicted spectra and the corresponding ones in MILES and MaStar is less than 5%. More verification is conducted between the magnitudes calculated from the integration of the predicted spectra and the observations in PS1 and APASS bands with the same stellar parameters. No significant systematic difference is found between the predicted spectra and the photometric observations. The uncertainty is 0.08 mag in the r band for SSF-gM when comparing with the stars with the same stellar parameters selected from PS1. The uncertainty becomes 0.31 mag in the i band for SSF-dM when comparing with the stars with the same stellar parameters selected from APASS.

All Spectral Type LAMOST Spectra Library (ATLAS)

We present an empirical stellar spectra library, ATLAS, with resolution R ∼ 1800 and wavelength coverage from 3800–8700 Å. These spectra are homogeneously observed by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope and have been released in its DR5. ATLAS is separated into two groups, ATLAS-A and -T. The former contains 5584 spectra covering spectral types from O- to M-type and some special types such as A supergiant, blue horizontal-branch, and carbon stars. All of the spectra have absolutely calibrated fluxes at certain characteristic wavelengths corresponding to the optical passbands with accuracy better than 2.9% by comparing with PanSTARRS1 g-, r-, and i-band photometry. In addition, greater than 1% systematic uncertainty from the fundamental calibration should be considered separately. ATLAS-A contains 5342 spectra with spectral energy distribution effective temperature, surface gravity, and metallicity and 242 spectra with only the effective temperature and surface gravity. These parameters are consistent with the spectroscopic derived parameters of the same stars. Compared to current empirical libraries, ATLAS-A contains more cool giant stars, which may play a critical role in understanding the evolution of galaxies. ATLAS-T, on the other hand, contains 1118 spectral templates averaging over spectra with similar stellar parameters from ATLAS-A. It smooths out some special features in the individual spectra and can be used as a “standard” atlas of stellar spectra. Containing stellar spectra with almost all normal types, ATLAS may not only be a complete training data set for stellar spectra parameter determination but also an ideal legacy for stellar population synthesis.

Chemical characterisation of the X-shooter Spectral Library (XSL): [Mg/Fe] and [Ca/Fe] abundances

Context. The X-shooter Spectral Library (XSL) is a large empirical stellar library used as a benchmark for the development of stellar population models. The inclusion of α-element abundances is crucial to disentangling the chemical evolution of any stellar system. Aims. The aim of this paper is to provide a catalogue of high-precision, accurate magnesium and calcium abundances from a wide variety of stars that are well distributed in the Hertzsprung-Russell (HR) diagram. Methods. We originally performed an analysis of the derived Mg and Ca abundances for medium-resolution spectra of 611 stars from the XSL Data Release 2. For this purpose, we used the GAUGUIN automated abundance estimation code to fit the ultraviolet-blue (UVB) and visible (VIS) spectra. We tested the consistency of the atmospheric parameters and chemical abundances with the Gaia DR3 and the AMBRE Project datasets. Results. We finally obtained precise [Mg/Fe] and [Ca/Fe] abundances for 192 and 217 stars, respectively, from which 174 stars have measurements in both elements. The stars cover a broad effective temperature range of 4000 &lt; Teff &lt; 6500 K, surface gravity of 0.3 &lt; log(g) &lt; 4.8 cm s−2, and metallicity of −2.5 &lt; [Fe/H] &lt; +0.4 dex. We find an excellent agreement with the abundance estimates from the AMBRE:HARPS and the Gaia-RVS (Radial Velocity Spectrometer) analysis. Moreover, the resulting abundances reproduce a plateau in the metal-poor regime followed by a decreasing trend even at supersolar metallicities, as predicted by Galactic chemical evolution models. Conclusions. This catalogue is suitable for improving the modelling of evolutionary stellar population models with empirical α enhancements, which could significantly contribute to the analysis of external galaxies’ abundances in the near future.

The Eclipsing Binaries from the LAMOST Medium-resolution Survey. III. A High-precision Empirical Stellar Mass Library

High-precision stellar masses and radii measured directly from binaries can effectively calibrate stellar models. However, such a database containing full spectral types and a large range of metallicity is still not fully established. A continuous effort of data collection and analysis is requested to complete the database. In this work, we provide a catalog containing 184 binaries with independent atmospheric parameters and accurate masses and radii as the benchmark for stellar mass and radius. The catalog contains 56 new detached binaries from the LAMOST medium-resolution spectroscopic survey and 128 detached eclipsing binaries compiled from previous studies. We obtain the orbital solutions of the new detached binaries with uncertainties of masses and radii smaller than 5%. These new samples densify the distribution of metallicity of the high-precision stellar mass library and add nine hot stars with T eff > 8000 K. Comparisons show that these samples agree well with the PARSEC isochrones in T eff–logg–mass–radius–luminosity space. We compare mass and radius estimates from isochrone and spectral energy distribution fitting, respectively, with those from the binary orbital solution. We find that the precision of the stellar-model-dependent mass estimates is >10% and the precision of the radius estimates based on atmospheric parameters is >15%. These give a general view of the uncertainty of the usual approaches to estimate stellar mass and radius.

MEGASTAR − III. Stellar parameters and data products for DR1 late-type stars

ABSTRACT MEGARA (Multi Espectrógrafo en Gran Telescopio Canarias de Alta Resolución para Astronomía) is the optical integral-field and multi-object spectrograph at the Gran Telescopio Canarias. We have created MEGASTAR , an empirical library of stellar spectra obtained using MEGARA at high resolution, $R=20\, 000$ (full width at half-maximum), available in two wavelength ranges: one centred on Hα, from 6420 to 6790 Å; and the other centred on the Ca ii triplet, from 8370 to 8885 Å (HR-R and HR-I volume phase holographic (VPH)-grating configurations). In this work, we use MEGASTAR spectra, a combination of these two short wavelength intervals, to estimate the stellar parameters, namely the effective temperature, surface gravity, and metallicity (and their associated errors), for a sample of 351 MEGASTAR members with spectral types earlier than B2. We applied a χ2-technique by comparing MEGASTAR data with theoretical stellar models. For those stars with stellar parameters derived in the literature, we obtained a good agreement between the published parameters and ours. In addition to the stellar parameters, we also provide several products, such as the rectified spectra, radial velocities, and stellar indices, for this sample of stars. In the near future, we will use MEGASTAR spectra and their derived stellar parameters to compute stellar population evolutionary synthesis models, which will contribute to a better interpretation of star cluster and galactic spectra obtained with MEGARA.

Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data.

Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

Modelling simple stellar populations in the near-ultraviolet to near-infrared with the X-shooter Spectral Library (XSL)

We present simple stellar population models based on the empirical X-shooter Spectral Library (XSL) from near-ultraviolet (NUV) to near-infrared (NIR) wavelengths. The unmatched characteristics of the relatively high resolution and extended wavelength coverage (350–2480 nm, R ∼ 10 000) of the XSL population models bring us closer to bridging optical and NIR studies of intermediate-age and old stellar populations. It is now common to find good agreement between observed and predicted NUV and optical properties of stellar clusters due to our good understanding of the main-sequence and early giant phases of stars. However, NIR spectra of intermediate-age and old stellar populations are sensitive to cool K and M giants. The asymptotic giant branch, especially the thermally pulsing asymptotic giant branch, shapes the NIR spectra of 0.5–2 Gyr old stellar populations; the tip of the red giant branch defines the NIR spectra of older populations. We therefore construct sequences of the average spectra of static giants, variable O-rich giants, and C-rich giants to be included in the models separately. The models span the metallicity range −2.2 &lt; [Fe/H] &lt; +0.2 and ages above 50 Myr, a broader range in the NIR than in other models based on empirical spectral libraries. We focus on the behaviour of colours and absorption-line indices as a function of age and metallicity. Our models can reproduce the integrated optical colours of the Coma cluster galaxies at the same level as other semi-empirical models found in the literature. In the NIR, there are notable differences between the colours of the models and Coma cluster galaxies. Furthermore, the XSL models expand the range of predicted values of NIR indices compared to other models based on empirical libraries. Our models make it possible to perform in-depth studies of colours and spectral features consistently throughout the optical and the NIR range to clarify the role of evolved cool stars in stellar populations.

Prospects of measuring a metallicity trend and spread in globular clusters from low-resolution spectroscopy

Context.The metallicity spread, or the metallicity trend along the evolutionary sequence of a globular cluster, is a rich source of information to help understand the cluster physics (e.g., multiple populations) and stellar physics (e.g., atomic diffusion). Low-resolution integral-field-unit spectroscopy in the optical with the MUSE spectrograph is an attractive prospect if it can provide these diagnostics because it allows us to efficiently extract spectra of a large fraction of the cluster stars with only a few telescope pointings.Aims.We investigate the possibilities of full-spectrum fitting to derive stellar parameters and chemical abundances at low spectral resolution (R ∼ 2000).Methods.We reanalysed 1584 MUSE spectra of 1061 stars above the turn-off of NGC 6397 using FERRE and employing two different synthetic libraries.Results.We derive the equivalent iron abundance [Fe/H]efor fixed values of [α/Fe] (solar or enhanced). We find that (i) the interpolation schema and grid mesh are not critical for the precision, metallicity spread, and trend; (ii) with the two considered grids, [Fe/H]eincreases by ∼0.2 dex along the sub-giant branch, starting from the turn-off of the main sequence; (iii) restricting the wavelength range to the optical decreases the precision significantly; and (iv) the precision obtained with the synthetic libraries is lower than the precision obtained previously with empirical libraries.Conclusions.Full-spectrum fitting provides reproducible results that are robust to the choice of the reference grid of synthetic spectra and to the details of the analysis. The [Fe/H]eincrease along the sub-giant branch is in stark contrast with the nearly constant iron abundance previously found with empirical libraries. The precision of the measurements (0.05 dex on [Fe/H]e) is currently not sufficient to assess the intrinsic chemical abundance spreads, but this may change with deeper observations. Improvements of the synthetic spectra are still needed to deliver the full possibilities of full-spectrum fitting.

The Role of Christian Education in Building Skills and Instilling Moral Values among Students in Higher Ed Institutions for National Unity and Economic Advancement in Sub-Saharan Africa

Education is more than the acquisition of knowledge. There are people in society who have acquired expertise but lack the character and skills to impact their community effectively. This situation has distorted national unity and lowered economic growth. “African graduates, especially in Sub-Saharan Africa, are victims of frequent ethnic conflicts, corruption, nepotism and industries dependent on outdated technology with low returns and low productivity” (Kigotho 2019). Many students graduate from higher ed institutions to cause unrest in their country because of a lack of skills and morals. To revolutionize the education sector in Sub-Saharan Africa requires an integration of biblical principles in the teaching and learning process to build skills and character for national advancement. The approach used in this paper is library research through critical analysis of empirical studies and library resources, both primary and secondary sources, to describe the phenomenon under study

Beginning Verb: An Analysis of Omitting Verb “Watching” in Comparison between Bima and English Language

This study is inspired by the use of verb "watching" in English language in which it can be omitted and still preserve its meaning in the sentence. The aim of this research is to find out the differences in meaning of the verb "watching" when omitted in a sentence between Bima and English language. This paper is a descriptive qualitative analysis design. It utilizes empirical data and library sources to complete it. This paper also used qualitative method analysis because the data are in the form of words instead of numbers. To analyze the data, the writer used Dixon’s theory on Beginning verbs. In terms of Bima language, the process of omission verb is proven to be quite complicated. The one that makes it complicated is simply because the speaker is accustomed to say the verb and not familiar with the process of omission. Although it is limited in terms of its data, time, and sources, this paper could be well developed if others want to concern more on the Bima language in terms of its tradition or the culture. The culture of the language seems to be more complex and the native speaker is really having a hard time explaining it.

Optimizing experimental design for genome sequencing and assembly with Oxford Nanopore Technologies.

High quality reference genome sequences are the core of modern genomics. Oxford Nanopore Technologies (ONT) produces inexpensive DNA sequences, but has high error rates, which make sequence assembly and analysis difficult as genome size and complexity increases. Robust experimental design is necessary for ONT genome sequencing and assembly, but few studies have addressed eukaryotic organisms. Here, we present novel results using simulated and empirical ONT and DNA libraries to identify best practices for sequencing and assembly for several model species. We find that the unique error structure of ONT libraries causes errors to accumulate and assembly statistics plateau as sequence depth increases. High-quality assembled eukaryotic sequences require high-molecular-weight DNA extractions that increase sequence read length, and computational protocols that reduce error through pre-assembly correction and read selection. Our quantitative results will be helpful for researchers seeking guidance for de novo assembly projects.

IMPLEMENTASI KEPEMIMPINAN PROFETIK DI ERA NEW NORMAL

Abstrak&#x0D; This research is to find out the implementation of leadership in Indonesia in the new normal era with the approach of prophetic character values of the prophet Muhammad saw. Data analysis is done through description on the prophetic properties of the prophet Muhammad saw. Methods are conducted through descriptive qualitatives, with empirical data and library studies. That the leaders needed by the People of Indonesia can be categorized as 4 types, 1), loved leaders; 2), a trustworthy leader; 3), guiding leader; and 4) personality through transformational, visionary nature and high work ethic. This research can contribute as information characteristics of leaders that people want in the new normal era today.

A comparison between X-shooter spectra and PHOENIX models across the HR-diagram

Aims. The path towards robust near-infrared extensions of stellar population models involves the confrontation between empirical and synthetic stellar spectral libraries across the wavelength ranges of photospheric emission. Indeed, the theory of stellar emission enters all population synthesis models, even when this is only implicit in the association of fundamental stellar parameters with empirical spectral library stars. With its near-ultraviolet to near-infrared coverage, the X-shooter Spectral Library (XSL) allows us to examine to what extent models succeed in reproducing stellar energy distributions (SEDs) and stellar absorption line spectra simultaneously. Methods. As a first example, this study compares the stellar spectra of XSL with those of the Göttingen Spectral Library, which are based on the PHOENIX synthesis code. The comparison was carried out both separately in the three arms of the X-shooter spectrograph known as UVB, VIS and NIR, and jointly across the whole spectrum. We did not discard the continuum in these comparisons; only reddening was allowed to modify the SEDs of the models. Results. When adopting the stellar parameters published with data release DR2 of XSL, we find that the SEDs of the models are consistent with those of the data at temperatures above 5000 K. Below 5000 K, there are significant discrepancies in the SEDs. When leaving the stellar parameters free to adjust, satisfactory representations of the SEDs are obtained down to about 4000 K. However, in particular below 5000 K and in the UVB spectral range, strong local residuals associated with intermediate resolution spectral features are then seen; the necessity of a compromise between reproducing the line spectra and reproducing the SEDs leads to dispersion between the parameters favored by various spectral ranges. We describe the main trends observed and we point out localized offsets between the parameters preferred in this global fit to the SEDs and the parameters in DR2. These depend in a complex way on the position in the Hertzsprung–Russell diagram (HRD). We estimate the effect of the offsets on bolometric corrections as a function of position in the HRD and use this for a brief discussion of their impact on the studies of stellar populations. A review of the literature shows that comparable discrepancies are mentioned in studies using other theoretical and empirical libraries.

SMILES: a library of semi-empirical MILES stellar spectra with variable [α/Fe] abundances

ABSTRACT We present a new library of semi-empirical stellar spectra that is based on the empirical Medium resolution Isaac Newton Library of Empirical Spectra (MILES) library. A new, high-resolution library of theoretical stellar spectra is generated that is specifically designed for use in stellar population studies. We test these models across their full wavelength range against other model libraries and find reasonable agreement in their predictions of spectral changes due to atmospheric α-element variations, known as differential corrections. We also test the models against the MILES and MaStar libraries of empirical stellar spectra and also find reasonable agreements, as expected from previous work. We then use the abundance pattern predictions of the new theoretical stellar spectra to differentially correct MILES spectra to create semi-empirical MILES (sMILES) star spectra with abundance patterns that differ from those present in the Milky Way. The final result is five families of 801 sMILES stars with [α/Fe] abundances ranging from −0.20 to 0.60 dex at MILES resolution (FWHM = $2.5\,$Å) and wavelength coverage ($3540.5\!-\!7409.6\,$Å). We make the sMILES library publicly available.