Miracle-dz/UniFAR-FTUs huggingface dataset:
On the performance of DFT/MRCI-R and MR-MP2 in spin–orbit coupling calculations on diatomics and polyatomic organic molecules

ABSTRACT We have investigated the performance of different multi-reference quantum chemical methods with regard to electronic excitation energies and spin–orbit matrix elements (SOMES). Among these methods are two variants of the combined density functional theory and multi-reference configuration interaction method (DFT/MRCI and DFT/MRCI-R) and a multi-reference second-order Møller–Plesset perturbation theory (MR-MP2) approach. Two variants of MR-MP2 have been tested based on either Hartree–Fock orbitals or Kohn–Sham orbitals of the BH-LYP density functional. In connection with the MR-MP2 approaches, the first-order perturbed wave functions have been employed in the evaluation of spin–orbit coupling. To validate our results, we assembled experimental excitation energies and SOMES of eight diatomic and fifteen polyatomic molecules. For some of the smaller molecules, we carried out calculations at the complete active space self-consistent field (CASSCF) level to obtain SOMEs to compare with. Excitation energies of the experimentally unknown states were assessed with respect to second-order perturbation theory corrected (CASPT2) values where available. Overall, we find a very satisfactory agreement between the excitation energies and the SOMEs obtained with the four approaches. For a few states, outliers with regard to the excitation energies and/or SOMEs are observed. These outliers are carefully analysed and traced back to the wave function composition.
A new method for optimal expansion planning in electrical energy distribution networks with distributed generation resources considering uncertainties

The present study aims to introduce a robust model for distribution network expansion planning considering system uncertainties. The proposed method determines optimal size and placement of distributed generation resources, as well as installation and reinforcement of feeders and substations. This model is designed to minimize cost and to determine the best time for the installation of equipment in the expansion planning. In the proposed expansion planning, the fuzzy logic theory is employed to model uncertainties of loads and energy price. Also, since the proposed model is a nonlinear and nonconvex optimization problem, a tri-stage algorithm is developed to solve it. Simulation results revealed that the proposed model would be capable to improving the performance of the expansion planning in distribution networks.
Can loyalty be pursued and achieved? An extended RFD model to understand and predict user loyalty to mobile apps

Although millions of mobile apps have been published in the app store, the majority are seldom downloaded or used. This phenomenon has intensified the competition among service providers for user loyalty. There were plenty of studies investigating user loyalty in the mobile‐app context; nevertheless, most failed to identify those true loyalty users who embraced attitudinal and behavioral loyalty. To address this research gap, this study aims to understand and predict user loyalty by an extended RFD model. We propose that recency, frequency, and duration are able to reflect behavioral loyalty, while category frequency rate and category duration rate are representations of attitudinal loyalty. Using the actual data collected from a third‐party app, we calculate the weights of each variable through the entropy weight method, evaluate users' loyalty in two dimensions, and classify users into four groups (i.e., true loyalty, latent loyalty, moderate loyalty, and no loyalty). We also conduct a dynamic analysis to investigate how users move across different loyalty conditions. The results indicate that majority of users tend to stay on their initial loyalty conditions. For those who have changed their loyalty conditions, it is found that true loyalty users are more likely to become latent loyalty users.
A Preliminary Study of Aflatoxin B1 Detection in Peanut Oil by Terahertz Time-Domain Spectroscopy

Abstract. Aflatoxins are fungal secondary toxic metabolites that can cause serious health problems in animals and humans. Terahertz (THz) spectroscopy is promising as a nondestructive analytical tool for chemical and biochemical detection. In this technical note, THz time-domain spectroscopy (THz-TDS) was used for the quantitative analysis of aflatoxin B1 (AFB1) in peanut oil. Chemometrics methods including partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) were used to build quantitative models. Their performance was compared using two spectral pretreatment methods (first and second derivative). The results show that the SMLR model was more stable than the PLSR model, although its prediction precision was slightly lower. When 1.11 and 0.72 THz frequencies were used, the root mean square errors of calibration (RMSEC) and cross-validation (RMSECV) were 18.2 and 27.7 ppm, respectively, and the corresponding correlation coefficients (rc and rcv) were 0.9639 and 0.9309, respectively. The overall results indicate that THz-TDS combined with frequency selection could be applied as a rapid and nondestructive tool for the determination of AFB1 content in peanut oil.
A Simplified Finite Difference Method (SFDM) Solution via Tridiagonal Matrix Algorithm for MHD Radiating Nanofluid Flow over a Slippery Sheet Submerged in a Permeable Medium

In this paper, we turn our attention to the mathematical model to simulate steady, hydromagnetic, and radiating nanofluid flow past an exponentially stretching sheet. A numerical modeling technique, simplified finite difference method (SFDM), has been applied to the flow model that is based on partial differential equations (PDEs) which is converted to nonlinear ordinary differential equations (ODEs) by using similarity variables. For the resultant algebraic system, the SFDM uses the tridiagonal matrix algorithm (TDMA) in computing the solution. The effectiveness of numerical scheme is verified by comparing it with solution from the literature. However, where reference solution is not available, one can compare its numerical results with the results of MATLAB built-in package bvp4c. The velocity, temperature, and concentration profiles are graphed for a variety of parameters, i.e., Prandtl number, Grashof number, thermal radiation parameter, Darcy number, Eckert number, Lewis number, and Brownian and thermophoresis parameters. The significant effects of the associated emerging thermophysical parameters, i.e., skin friction coefficient, local Nusselt number, and local Sherwood numbers are analyzed and discussed in detail. Numerical results are compared from the available literature and found a close agreement with each other. It is found that the Eckert number upsurges the velocity curve. However, the dimensionless temperature declines with the Grashof number. It is also shown that the SFDM gives good results when compared with the results obtained from bvp4c and results from the literature.
First-principles prediction of rare-earth free permanent magnet: FeNi with enhanced magnetic anisotropy and stability through interstitial boron

Ab initio electronic structure calculations reveal that interstitial 2p elements (B, C, and N) have dramatic effects on the structural stability and intrinsic magnetic properties of L10-phase FeNi. Among the 3 possible interstitial impurities, only the B improves the L10-phase stability of FeNi and enhances its uniaxial magnetic anisotropy (0.7 MJ m−3) up to 2.6 MJ m−3. The underlying mechanism is elucidated in terms of single-particle energy spectra analyses along with atom- and orbital-resolved magnetocrystalline anisotropy energy, where both the Fe and Ni 3d level changes induced by charge rearrangement and 2p-3d hybridization are responsible. These findings point toward feasibility of enhancing the structural stability and energy product of 3d-only magnetic metals through the interstitial doping with 2p nonmetal elements.
A Study on Stock Graph Recognition Based on Wavelet Denoising and DTW Algorithm

The “classical pattern” of stock price formation has long been widely used in the determination of future price trends of stocks, and the identification and analysis of classical price patterns have an important guiding role in investors’ decision-making and trading. The wavelet transform is a useful tool to remove some of the noise of time series because it has the characteristic of multiresolution. In this study, we propose a method for stock price pattern recognition based on the wavelet transform and dynamic time warp (DTW). A pattern recognition method with similar quantified results is developed to obtain accurate pattern recognition results. That is, using the wavelet transform to smooth the original price graph, and then using the DTW algorithm improved in this study to find the graph with the smallest distance from the target graph under the sliding window method, the identification and analysis of the target graph can be realized. In order to improve the recognition rate of the target graph, we preprocessed the raw price sequence using the moving average convergence and divergence (MACD) algorithm based on the control experiments set up in this study. The pattern recognition method used in this study will identify the price patterns of a certain time window as a whole, thus avoiding the problem of how to objectively select the important points that constitute a price pattern and the mathematical definition of different price patterns in the previous traditional methods.
Recent Developments in the Use of Heterogeneous Semiconductor Photocatalyst Based Materials for a Visible-Light-Induced Water-Splitting System—A Brief Review

Visible-light-driven photoelectrochemical (PEC) and photocatalytic water splitting systems featuring heterogeneous semiconductor photocatalysts (oxynitrides, oxysulfides, organophotocatalysts) signify an environmentally friendly and promising approach for the manufacturing of renewable hydrogen fuel. Semiconducting electrode materials as the main constituents in the PEC water splitting system have substantial effects on the device’s solar-to-hydrogen (STH) conversion efficiency. Given the complication of the photocatalysis and photoelectrolysis methods, it is indispensable to include the different electrocatalytic materials for advancing visible-light-driven water splitting, considered a difficult challenge. Heterogeneous semiconductor-based materials with narrower bandgaps (2.5 to 1.9 eV), equivalent to the theoretical STH efficiencies ranging from 9.3% to 20.9%, are recognized as new types of photoabsorbents to engage as photoelectrodes for PEC water oxidation and have fascinated much consideration. Herein, we spotlight mainly on heterogenous semiconductor-based photoanode materials for PEC water splitting. Different heterogeneous photocatalysts based materials are emphasized in different groups, such as oxynitrides, oxysulfides, and organic solids. Lastly, the design approach and future developments regarding heterogeneous photocatalysts oxide electrodes for PEC applications and photocatalytic applications are also discussed.
Optimization Methods of MPPT Parameters for PV Systems: Review, Classification, and Comparison

To obtain efficient photovoltaic (PV) systems, optimum maximum power point tracking (MPPT) algorithms are inevitable. The efficiency of MPPT algorithms depends on two MPPT parameters, i. e. , perturbation amplitude and perturbation period. The optimization of MPPT algorithms affect both the tracking speed and steady-state oscillation. In this paper, optimization methods of MPPT parameters are reviewed and classified into fixed and variable methods. The fixed MPPT parameters are constant during MPPT performance, and a trade-off should be made between the tracking speed and steady-state oscillation. However, the variable MPPT parameters will be changed to improve both the tracking speed and the steady-state oscillations. Moreover, some of them are simulated, compared, and discussed to evaluate the real contributions of the optimization methods to the MPPT efficiency. Furthermore, significant features of the optimization methods, i.e., noise immunity, robustness, and computation effort, are investigated.
Crystal structure and molecular docking studies of benzo[8]annulenes as potential inhibitors against Mycobacterium tuberculosis

Tuberculosis is a disease caused by Mycobacterium tuberculosis. The bacterial cell wall has a characteristic low permeability, which essentially makes antibiotics ineffective. The cell wall material must be regulated so that its deposition does not compromise its structure. In this study, two new inhibitors, 2-amino-4-(4-cholorophenyl)-5,6,7,8,9,10-hexahydrobenzo[8] annulene-1,3,3(4H)-tricarbonitrile(Ia) and 2-amino-4-(4-bromophenyl)-5,6,7,8,9,10-hexahydrobenzo[8]annulene-1,3,3(4H)-tricarbonitrile(Ib) were synthesized. The crystal structures of the above compounds were determined by single crystal X-ray diffraction. The compounds C 21 H 19 Cl N 3 (Ia) and C 21 H 19 Br N 3 (Ib) were crystallized in the monoclinic and triclinic system. In both compounds, the cyclohexane ring was found to adopt a boat conformation. The cyclooctane ring of both compounds adopted a twisted chair-chair conformation. In silico analyses revealed that both compounds showed good anti-mycobacterial activities against the enoyl-acyl carrier enzyme and the N-acetyl-gamma protein, both of which are critical for bacterial survival. Synthesis, structure determination, conformation, intra, inter-molecular interactions and docking studies of both compounds are presented herein.
Design of a New Gemini Lipoaminoacid with Immobilized Lipases Based on an Eco-Friendly Biosynthetic Process

Lipoaminoacids (LAA) are an important group of biosurfactants, formed by a polar hydrophilic part (amino acid) and a hydrophobic tail (lipid). The gemini LAA structures allow the formation of a supramolecular complex with bioactive molecules, like DNA, which provides them with good transfection efficiency. Since lipases are naturally involved in lipid and protein metabolism, they are an alternative to the chemical production of LAA, offering an eco-friendly biosynthetic process option. This work aimed to design the production of novel cystine derived gemini through a bioconversion system using immobilized lipases. Three lipases were used: porcine pancreatic lipase (PPL); lipase from Thermomyces lanuginosus (TLL); and lipase from Rizhomucor miehei (RML). PPL was immobilized in sol-gel lenses. L-cystine dihydrochloride and dodecylamine were used as substrates for the bioreaction. The production of LAA was evaluated by thin layer chromatography (TLC), and colorimetric reaction with eosin. The identification and quantification was carried out by High Performance Liquid Chromatographer-Mass Spectrometry (HPLC-MS/MS). The optimization of media design included co-solvent (methanol, dimethylsulfoxide), biphasic (n-hexane and 2-propanol) or solvent-free media, in order to improve the biocatalytic reaction rates and yields. Moreover, a new medium was tested where dodecylamine was melted and added to the cystine and to the biocatalyst, building a system of mainly undissolved substrates, leading to 5 mg/mL of LAA. Most of the volume turned into foam, which indicated the production of the biosurfactant. For the first time, the gemini derived cystine lipoaminoacid was produced, identified, and quantified in both co-solvent and solvent-free media, with the lipases PPL, RML, and TLL.
Determinants Effectiveness of Information Technology Governance and IT Performance in Higher Education Institution (HEI): A Conceptual Framework

The purpose of this article is to build a conceptual framework based on literature review that will be tested in future research related to Information Technology Governance (ITG). The results of the literature review allow for the construction of hypotheses into a conceptual framework. Furthermore, the study identifies mechanism that contribute to effectiveness IT governance based on past literatures, on this domain assesses mechanism ITG the influence between information technology performance and effectiveness Information technology governance . The conceptual framework will be tested among higher Education Institution (HEI) users for future research in Indonesia.
Influence of thermal processing on the characteristics and chemical profile of ora-pro-nobis by PS/MS paper spray

This work aimed to evaluate the influence of dry and wet heat processing on the antioxidant profile and antioxidant activity in ora-pro-nobis leaves. The leaves were collected, washed, and separated into three groups for the treatments: application of moist heat (hydrothermal cooking at 100 oC / 4 minutes), application of dry heat (70 oC / 8 hours), and control (raw material). The characteristics were evaluated: total soluble solids (SST), total solids (ST), pH, phenolic compounds (CPT), flavonoids (FT), anthocyanins (AT), antioxidant activity (AA). To identify the chemical profile and the chemical profile, fingerprints were obtained using PS / MS paper spray. The content of SST and ST decreased with moist heat. The CFT content increased with wet heat (12.43 ± 0.98) and decreased with dry heat (4.25 ± 0.93 g EAG 100 g-1). There was a decrease in the FT and AT content in the leaves processed with dry heat (132.67 ± 20.28 mg 100 g-1 and 19.70 ± 3.34 mg CG 100 g-1, respectively). AA decreased in both processes, which was higher in ora-pro-nobis leaves processed with dry heat (0.82 ± 0.0033 µmol ET g-1). 26 phenolic compounds were identified in the ora-pro-nob leaves by paper spray. The chemical profile, except for the substances 4,5-dimethyl-2,6-octadiene and methyl ester linolenic acid was not affected by thermal processing. Knowing the effect of food processing is important to understand the behavior of compounds that act beneficially on human health.
HPLC-UV/FD Methods for Scopoletin and Asiatic acid: Development,Validation and Application in WHO Recommended Stability Testing of HerbalDrug Products

WHO recommended accelerated stability study was conducted on commercially available herbal products containing Shankhpushpi along with Bacopa monnieri (A) or Centella asiatica (B) at a temperature of 40 ± 2°C and 75 ± 5% RH for six months. Control sample of each product was stored at 4°C. Stability samples were withdrawn after 1, 3 and 6 months. Each control and stability sample was analysed for the content of scopoletin, asiatic acid and bacoside A by HPLC methods because such methods prove more selective, sensitive, efficient, reproducible, and accurate than spectroscopic and chemical methods. These methods also have advantages of sample handing, cost effectiveness and versatility in analyzing chemically diverse compounds over other methods like GSC and GLC. New methods developed and validated for scopoletin and asiatic acid were proved sufficiently precise, accurate and robust for analysis of scopoletin (1-500 ng/ml) and asiatic acid (10-1000 μg/ml). Bacoside A was not detected in any of the control samples of products A, indicating that B. monnieri is either absent in A or the content of Bacoside A is too low to be detectable. Content of scopoletin and asiatic acid was found to vary widely among different batches as well as products (scopoletin 165.78-206.15 ng/ml in A and 2.61-28.78 ng/ml in B, and asiatic acid 30.14-44.92 μg/ml in B), which indicate a probable variability in therapeutic efficacy of the products. The content of markers decreased significantly after 6 months of storage under accelerated conditions, which implies that therapeutic efficacy of the product may also decrease substantially with storage. These findings further suggest real time stability studies as per the WHO and ICH guidelines involving marker’s quantification and evaluation of therapeutic effects through appropriate in vitro/in vivo methods to establish actual shelf life of the products.
Participative Gatekeeping: The Intersection of News, Audience Data, Newsworkers, and Economics

Abstract The use of metrics and analytics is becoming pervasive in newsrooms the world over. However, there is a lack of consistent terminology in scholarly literature with regards to such practice and a dearth of studies that compare practice on a wider scale that prevents more holistic understanding of how audience data are being used on the newsroom floor. These issues are addressed with the development of a new participative gatekeeping model with three previously unidentified channels of gatekeeping specifically related to the use of audience data: promotional, for the type of short-term gatekeeping done on news site homepages that involves tracking real-time metrics to position content, often tied to traffic targets; developmental, or longer-term strategies that shape future coverage and are grounded in hypotheses of audience behaviour gleaned from analytics; and a third more porous channel of experimentation where such hypotheses are tested. These channels were observed in ethnographic research in six newsrooms in three different countries at media outlets with diverse sources of revenue: Norway’s public broadcaster, NRK; Canada’s subscriber-based national news agency, The Canadian Press (CP); and two local newsrooms working within larger media organizations, The Hamilton Spectator in Canada, and The Bournemouth Daily Echo in England. Through a sociological lens, this article distinguishes language to best document the complex processes interconnected with audience data, identifies similarities in practice that override media or revenue systems, and explores how the audience, through the participatory mechanisms of metrics and analytics, shapes newsroom practice.
ESG Disclosures and Stock Price Crash Risk

In this study, we investigate the relationship between environmental, social, and governance (ESG) disclosures and stock price crash risk. A stock price crash is a dreadful event for market participants. Thus, exploring stock price crash determinants is helpful for investment decisions and risk management. In this study, we use samples of major market index components in Europe, the United States, and Japan to perform regression analyses, after controlling for other potential stock price crash determinants. We estimate static two-way fixed-effect models and dynamic GMM models. We find that coefficients of firm-level ESG disclosures are not statistically significant in the static model. ESG disclosure coefficients in the dynamic model are not statistically significant in the U.S. market sample. On the other hand, coefficients of ESG disclosure scores in the dynamic model are statistically significant and negative in the European and Japanese marker sample. Our findings suggest that ESG disclosures lower future stock price crash risk; however, the effect and predictive power of ESG disclosures differ among regions.