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Simple Summary: The major insect pest of European plantation forests is the large pine weevil. Traditionally, this pest has been controlled by applications of synthetic pesticides. However, because of human health and environmental concerns, there is a need to develop alternative sustainable management strategies. One such strategy is the use of biological control agents. We trialled the efficacy of wild-collected insect-killing fungi and commercial round worms (nematodes) alone and in combination against immature stages of the large pine weevil, which live under the bark of freshly cut stumps. All treatments, as assessed by monitoring emergence with specialised traps, significantly reduced the weevil populations compared to the untreated controls, and the destructive sampling of stumps revealed strong associations between treatment type and infection outcomes. We also monitored non-target insects emerging from treated and untreated stumps. There was no effect on abundance, taxon richness or community composition of the control agents, indicating that they encountered negligible negative environmental consequences. The large pine weevil (Hylobius abietis L.) is a major pest in European and Asian coniferous forests, particularly in managed plantations where clear-felling practices create ideal conditions for its population growth. Traditional management practices involving synthetic insecticides have limited efficacy in terms of reducing pest populations and pose environmental risks. This study evaluated the effectiveness of a wild entomopathogenic fungus (EPF) and the commercial entomopathogenic nematode Steinernema carpocapsae (EPN) as biological control agents (BCAs) against H. abietis in clear-felled spruce plantations in Wales and Scotland. Field trials used a randomised block design with three treatments (EPN full dose, EPF full dose and a combination of EPF+EPN at half doses each) compared to a control. Emergence trapping and destructive sampling were employed to assess treatment efficacy. All treatments significantly reduced weevil emergence, with the mixed treatment showing the greatest impact. Destructive sampling revealed strong associations between treatment type and infection outcomes in H. abietis, with a small but significant relationship between weevil developmental stages and infection types. Importantly, the treatments had no significant impact on the total abundance or taxon richness of non-target invertebrates. These findings suggest that wild EPFs alone and combined with EPNs are effective and environmentally safe alternatives to synthetic insecticides for managing H. abietis populations in managed forests. [ABSTRACT FROM AUTHOR]

Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)‐based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML‐based PairF‐Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system. Here, we further develop the PairF‐Net model to intrinsically incorporate energy conservation and couple the model to a molecular mechanical (MM) environment within the OpenMM package. The updated PairF‐Net model yields energy and force predictions and dynamical distributions in good agreement with the rMD17 dataset of ten small organic molecules in the gas‐phase. We further show that these in vacuo ML models of small molecules can be applied to force predictions in aqueous solution via hybrid ML/MM simulations. We present a new benchmark dataset for these ten molecules in solution, obtained from QM/MM simulations, which we denote as rMD17‐aq (https://zenodo.org/records/10048644); and assess the ability of PairF‐Net to reproduce the molecular energy, atomic forces and dynamical distributions of these solution conformations via ML/MM simulations. [ABSTRACT FROM AUTHOR]

U.S. generally accepted accounting principles (GAAP) allows banks to offset derivative assets against derivative liabilities with the same counterparty and report only the net amount on the balance sheet. Derivative offsetting under international financial reporting standards (IFRS) is much more restrictive, resulting in the single largest difference in balance sheet presentation between U.S. GAAP and IFRS. Two important factors dominate the standard-setting discussion on this issue: (1) whether these derivatives are informative about bank risk and (2) whether disclosing them substitutes for recognition on the balance sheet. Using a hand-collected global sample of banks, we first show that offsetable derivatives are positively associated with bank risk, based on multiple risk measures, suggesting that these derivatives are informative about bank risk. Next, exploiting the differential accounting treatment across U.S. GAAP and IFRS banks, we find that disclosure versus recognition of offsetable derivatives matters for the risk assessment of equity investors but not for that of (more sophisticated) credit default swap investors. Additional tests corroborate the inference that investor sophistication helps explain the differential investor assessment of recognized versus disclosed offsetable derivatives. Collectively, our findings suggest that offsetable derivatives convey information about bank risk and that, for less sophisticated investors, disclosing them may not substitute for recognizing them. This paper was accepted by Eric So, accounting. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4831. [ABSTRACT FROM AUTHOR]

We investigate the role of financial reporting quality in reducing a firm's over‐ and underleverage problems. While the prior literature examining reporting quality and capital structure has focused on observed capital structure, research suggests that financing frictions arising from adverse selection concerns can result in differences between observed and optimal capital structures. Using the deviation from a predicted model of optimal capital structure, we find that approximately a third of firms that have more leverage than their industry's median firm are in fact underlevered and more than 15% of firms that have less leverage than their industry's median firm are in fact overlevered. Building off a large literature that provides evidence that financial reporting quality can mitigate adverse selection concerns and reduce financing frictions, we find that a firm's deviation from the predicted model of optimal capital structure is decreasing in financial reporting quality, and these results are larger in magnitude for firms that are overlevered. [ABSTRACT FROM AUTHOR]