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Equity research analysts and investors remain divided on the treatment of stock-based compensation (SBC) in firm valuation, particularly in discounted cash flow (DCF) and earnings multiples techniques. Many firms and analysts exclude SBC, viewing it as a non-cash expense, while others argue this leads to overvaluation. SBC usage is especially high in the tech sector. This study examines five large semiconductor firms, analyzing SBC levels, its treatment in adjusted earnings, and its impact on share dilution, valuation multiples, and free cash flow calculations. Findings indicate that SBC treatment significantly affects valuation, particularly within the semiconductor industry.
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We develop a mechanistic model that classifies individuals both in terms of epidemiological status (SIR) and vaccination attitude (Willing or Unwilling/Unable), with the goal of discovering how disease spread is influenced by changing opinions about vaccination. Analysis of the model identifies the existence and stability criteria for both disease-free and endemic disease equilibria. The analytical results, supported by numerical simulations, show that attitude changes induced by disease prevalence can destabilize endemic disease equilibria, resulting in limit cycles.
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The STAR experiment reports new, high-precision measurements of the transverse single-spin asymmetries for π^{±} within jets, namely the Collins asymmetries, from transversely polarized p^{↑}p collisions at sqrt[s]=510 GeV. The energy-scaled distribution of jet transverse momentum, x_{T}=2p_{T,jet}/sqrt[s], shows a remarkable consistency for Collins asymmetries of π^{±} in jets between sqrt[s]=200 GeV and 510 GeV. This indicates that the Collins asymmetries are nearly energy independent, with, at most, a very weak scale dependence in p^{↑}p collisions. These results extend to high-momentum scales (Q^{2}≤3400 GeV^{2}) and enable unique tests of evolution and universality in the transverse-momentum-dependent formalism, thus providing important constraints for the Collins fragmentation functions.
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The rapid expansion of digital platforms has significantly influenced consumer purchasing behaviors, particularly in the agri-food sector. Therefore, this paper investigates the key factors driving customers’ intention to use green agri-food delivery apps (GAFDAs) by integrating trust and electronic word of mouth (eWOM) into the Theory of Planned Behavior (TPB) framework. Additionally, this study examines gender as a moderating variable, assessing whether its influence alters the relationships between key determinants and behavioral intention. Data were collected from 252 Algerian consumers, and the proposed model was tested using SmartPLS 4 and SPSS 26.0. The results confirm that attitude, subjective norms, perceived behavioral control (PBC), trust, and eWOM positively and significantly influence the intention to use GAFDAs, with PBC emerging as the strongest predictor. Moreover, gender moderates the effect of trust on behavioral intention, with trust significantly influencing men’s adoption decisions but not those of females. In contrast, subjective norms and PBC are stronger predictors for female consumers. These findings highlight the importance of gender-specific marketing strategies to enhance GAFDA adoption. This study contributes to the literature by extending TPB with trust, eWOM, and gender moderation, offering valuable insights for marketers, policymakers, and app developers promoting sustainable food consumption.
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Facultatively symbiotic corals provide important experimental models to explore the establishment, maintenance, and breakdown of the mutualism between corals and members of the algal family Symbiodiniaceae. Here, we report the de novo chromosome-scale genome assembly and annotation of the facultatively symbiotic, temperate coral Astrangia poculata. Though widespread segmental/tandem duplications of genomic regions were detected, we did not find strong evidence of a whole-genome duplication event. Comparison of the gene arrangement between As. poculata and the tropical coral Acropora millepora revealed considerable conserved colinearity despite ∼415 million years of divergence. Gene families related to sperm hyperactivation and innate immunity, including lectins, were found to contain more genes in Ac. millepora relative to As. poculata. Sperm hyperactivation in Ac. millepora is expected given the extreme requirements of gamete competition during mass spawning events in tropical corals, while lectins are important in the establishment of coral-algal symbiosis. By contrast, gene families involved in sleep promotion, feeding suppression, and circadian sleep/wake cycle processes were expanded in As. poculata. These expanded gene families may play a role in As. poculata's ability to enter a dormancy-like state (winter quiescence) to survive freezing temperatures at the northern edges of the species' range.
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The increasing volume of suspicious emails, commonly known as spam, has created a critical need for more reliable and robust anti-spam filters. These suspicious emails can be dangerous and can lead to the loss of personal information, underscoring the necessity for an effective spam filtering system. The application of machine learning methods has enhanced system security and improved the detection of suspicious messages. This research evaluates the effectiveness of seven machine learning algorithms for classifying suspicious email messages: random forest, support vector machine, artificial neural network, decision tree, gradient boosting classifier, and k-nearest neighbor. The primary focus of this evaluation is the accuracy achieved by each algorithm in identifying spam emails. Our analysis revealed that the random forest algorithm outperformed the other evaluated algorithms in terms of accuracy for spam email classification, achieving a remarkable 95%. The accuracy percentages of the various methods ranged from 88% to 93%. Copyright 2025. The Korean Institute of Information Scientists and Engineers.
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