Multi-output Deep-Supervised Classifier Chains for Plant Pathology

Multi-output Deep-Supervised Classifier Chains for Plant Pathology</p

Effect of hole shape on adiabatic cooling effectiveness

See paper published</p

Extrusion limits for AZ alloys with Al contents <3%

Extrusion limits for AZ alloys with Al contents <3

Cash flow sensitivities and the allocation of internal cash flow

We study how firms allocate cash flow by estimating the cash-flow sensitivities of various uses of cash flow.We decompose cash flow into a transitory and a permanent component and focus on the allocation of the transitory component, which by construction contains little information about future growth opportunities. We find that more financially constrained firms allocate more transitory cash flow to cash savings and direct less toward investment than do less constrained firms, consistent with constrained firms accumulating liquidity to buffer against future financial constraints. We also illustrate several methodological advantages of our approach over alternative methods in previous studie

The information role of advisors in mergers and acquisitions: Evidence from acquirers hiring targets’ ex-advisors

We examine the information role of financial advisors by focusing on mergers and acquisitions in which acquiring firms hire target firms’ ex-advisors. We document that by employing targets’ ex-advisors, acquirers pay lower takeover premiums and secure a larger proportion of merger synergies. The corresponding targets exhibit lower announcement returns and are less likely to be propositioned by competing bidders. These results indicate that acquirers take advantage of value-relevant information about targets through targets’ ex-advisors, and achieve bargaining advantages in deal negotiations. In contrast, we document no discernible value effects when targets hire acquirers’ ex-advisors, suggesting that the information role of acquirers’ ex-advisors hired by targets is weaker than that of targets’ ex-advisors hired by acquirers

Industry expertise, information leakage and the choice of M&A advisors

This paper examines the impacts of M&A advisors’ industry expertise on firms’choice of advisors in mergers and acquisitions. We show that an investment bank’s expertise in merger parties’ industries increases its likelihood of being chosen as an advisor, especially when the acquisition is more complex, and when a firm in M&A has less information about the merger counter party. However, due to the concerns about information leakage to industry rivals through M&A advisors, acquirers are reluctant to share advisors with rival firms in thesame industry, and they are more likely to switch to new advisors if their former advisors have advisory relationship with their industry rivals. In addition, we document that advisors with more industry expertise earn higher advisory fees and increase the likelihood of deal completion

Attention-aware upsampling-downsampling network for autonomous vehicle vision-based multitask perception

Abstract Vision-based environmental perception has demonstrated significant promise for autonomous driving applications. However, the traditional unidirectional feature flow in many perception networks often leads to inadequate information propagation, which hinders the system’s ability to comprehensively perceive complex driving environments. Issues such as similar objects, illumination variations, and scale differences aggravate this limitation, introducing noise and reducing the reliability of the perception system. To address these challenges, we propose a novel Attention-Aware Upsampling-Downsampling Network (AUDNet). AUDNet utilizes a bidirectional feature fusion structure, incorporating a multi-scale attention upsampling module (MAU) to enhance the fine details in high-level features by guiding the selection of feature information. Additionally, the multi-scale attention downsampling module (MAD) is designed to reinforce the semantic understanding of low-level features by emphasizing relevant spatial dfigureetails. Extensive experiments on a large-scale, real-world driving dataset demonstrate the superior performance of AUDNet, particularly in multi-task environment perception in complex and dynamic driving scenarios

Wine Characterisation with Spectral Information and Predictive Artificial Intelligence

Wine Characterisation with Spectral Information and Predictive Artificial Intelligence</p

Bacterial shifts during in-situ mineralization bio-treatment to non-ferrous metal(loid) tailings

Nonferrous mine tailings have caused serious problems of co-contamination with metal(loid)s. It is still a global challenge to cost-effectively manage and mitigate the effect of the mining wastes. We conducted an in-situ bio-treatment of non-ferrous metal(loid) tailings using a microbial consortium of sulfate reducing bacteria (SRB). During the bio-treatment, the transformation of metal(loid)s (such as Cu, Fe, Mn, Pb, Sb, and Zn) into oxidizable and residual fractions in the subsurface tended to be higher than that observed in the surface. As well the mineral compositions changed becoming more complex, indicating that the sulfur reducing process of bio-treatment shaped the bio-transformation of metal(loid)s. The added SRB genera, especially Desulfotomaculum genus, colonized the tailings suggesting the coalescence of SRB consortia with indigenous communities of tailings. Such observation provides new insights for understanding the functional microbial community coalescence applied to bio-treatment. PICRUSt analysis revealed presence of genes involved in sulfate reduction, both assimilatory and dissimilatory. The potential for the utilization of both inorganic and organic sulfur compounds as S source, as well as the presence of sulfite oxidation genes indicated that SRB play an important role in the transformation of metal(loid)s. We advocate that the management of microorganisms involved in S-cycle is of paramount importance for the in situ bio-treatment of tailings, which provide new insights for the implementation of bio-treatments for mitigating the effect of tailings

Characterization of LiMxFe1–xPO4 (M = Mg, Zr, Ti) Cathode Materials Prepared by the Sol-Gel Method

A series of LiMxFe12xPO4 (M 5 Mg,Zr,Ti) phosphates were synthesized via a sol-gel method. Transmission electron microscopy observations show that LiMxFe12xPO4 particles consist of nanosize crystals, ranging from 40 to 150 nm. High-resolution TEM analysis reveals that a layer of amorphous carbon was coated on the surface of the LiMxFe12xPO4 particles, which substantially increases the electronic conductivity of LiMxFe12xPO4 electrodes. The doped LiMxFe12xPO4 powders are phase pure. Near full capacity ~170 mAh/g! was achieved at the C/8 rate at room temperature for LiMxFe12xPO4 electrodes. The doped LiMxFe12xPO4 electrodes demonstrated better electrochemical performance than that of undoped LiFePO4 at high rate