Large Language Models for Semantic Monitoring of Corporate Disclosures: A Case Study on Korea's Top 50 KOSPI Companies

In the rapidly advancing domain of artificial intelligence, state-of-the-art language models such as OpenAI's GPT-3.5-turbo and GPT-4 offer unprecedented opportunities for automating complex tasks. This research paper delves into the capabilities of these models for semantically analyzing corporate disclosures in the Korean context, specifically for timely disclosure. The study focuses on the top 50 publicly traded companies listed on the Korean KOSPI, based on market capitalization, and scrutinizes their monthly disclosure summaries over a period of 17 months. Each summary was assigned a sentiment rating on a scale ranging from 1(very negative) to 5(very positive). To gauge the effectiveness of the language models, their sentiment ratings were compared with those generated by human experts. Our findings reveal a notable performance disparity between GPT-3.5-turbo and GPT-4, with the latter demonstrating significant accuracy in human evaluation tests. The Spearman correlation coefficient was registered at 0.61, while the simple concordance rate was recorded at 0.82. This research contributes valuable insights into the evaluative characteristics of GPT models, thereby laying the groundwork for future innovations in the field of automated semantic monitoring

Review on the ecotoxicological impacts of plastic pollution on the freshwater invertebrate Daphnia

The environmental impacts of plastic pollution have recently attracted universal attention, especially in the aquatic environment. However, research has mostly been focused on marine ecosystems, even though freshwater ecosystems are equally if not more polluted by plastics. In addition, the mechanism and extent to which plastic pollution affects aquatic biota and the rates of transfer to organisms through food webs eventually reaching humans are poorly understood, especially considering leaching hazardous chemicals. Several studies have demonstrated extreme toxicity in freshwater organisms such Daphnia. When such keystone species are affected by ambient pollution, entire food webs are destabilized and biodiversity is threatened. The unremitting increase in plastic contaminants in freshwater environments would cause impairments in ecosystem functions and structure, leading to various kinds of negative ecological consequences. As various studies have reported the effects on daphnids, a consolidation of this literature is critical to discuss the limitations and knowledge gaps and to evaluate the risk posed to the aquatic environment. This review was undertaken due to the evident need to evaluate this threat. The aims were to provide a meaningful overview of the literature relevant to the potential impact of plastic pollution and associated contaminants on freshwater daphnids as primary consumers. A critical evaluation of research gaps and perspectives is conducted to provide a comprehensive risk assessment of microplastic as a hazard to aquatic environments. We outlined the challenges and limitations to microplastic research in hampering better-focused investigations that could support the development of new plastic materials and/or establishment of new regulations.Peer reviewe

DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases

Keyphrase extraction from documents is useful to a variety of applications such as information retrieval and document summarization. This paper presents an end-to-end method called DivGraphPointer for extracting a set of diversified keyphrases from a document. DivGraphPointer combines the advantages of traditional graph-based ranking methods and recent neural network-based approaches. Specifically, given a document, a word graph is constructed from the document based on word proximity and is encoded with graph convolutional networks, which effectively capture document-level word salience by modeling long-range dependency between words in the document and aggregating multiple appearances of identical words into one node. Furthermore, we propose a diversified point network to generate a set of diverse keyphrases out of the word graph in the decoding process. Experimental results on five benchmark data sets show that our proposed method significantly outperforms the existing state-of-the-art approaches.Comment: Accepted to SIGIR 201

Metabolic Responses and Profiling of Bioorganic Phosphates and Phosphate Metabolites in Traumatic Brain Injury

This chapter constitutes a review of the recent literature on metabolic response and profiling of bioorganic phosphates and phosphate metabolites in disease related to traumatic brain injury (TBI). In this report we emphasize the emerging role of advanced imaging techniques in both the translational research of TBI biology and in the development of new modalities for the diagnosis and therapy of TBI-related diseases. To date, several neuroimaging techniques have been used for assessing phosphate metabolites related to TBI. These techniques include 31P-MRI/MRS imaging, magnetic resonance imaging, and incorporation of phosphate derivative hydrogels, all of which are of particular interest in identifying TBI. These advanced neuroimaging techniques are currently under investigation in an attempt to optimize properties for therapeutics purposes. In addition, this chapter also discusses the role of endogenous and exogenous phosphates related to TBI. TBI imaging is a rapidly evolving field, and a number of the recommendations presented will be updated in the future to reflect the advances in medical knowledge

Roles of Inflammatory Biomarkers in Exhaled Breath Condensates in Respiratory Clinical Fields

Background Exhaled condensates contain inflammatory biomarkers; however, their roles in the clinical field have been under-investigated. Methods We prospectively enrolled subjects admitted to pulmonology clinics. We collected exhaled breath condensates (EBC) and analysed the levels of six and 12 biomarkers using conventional and multiplex enzyme-linked immunosorbent assay, respectively. Results Among the 123 subjects, healthy controls constituted the largest group (81 participants; 65.9%), followed by the preserved ratio impaired spirometry group (21 patients; 17.1%) and the chronic obstructive pulmonary disease (COPD) group (21 patients; 17.1%). In COPD patients, platelet derived growth factor-AA exhibited strong positive correlations with COPD assessment test (ρ=0.5926, p=0.0423) and COPD-specific version of St. George’s Respiratory Questionnaire (SGRQ-C) score (total, ρ=0.6725, p=0.0166; activity, ρ=0.7176, p=0.0086; and impacts, ρ=0.6151, p=0.0333). Granzyme B showed strong positive correlations with SGRQ-C score (symptoms, ρ=0.6078, p=0.0360; and impacts, ρ=0.6007, p=0.0389). Interleukin 6 exhibited a strong positive correlation with SGRQ-C score (activity, ρ=0.4671, p=0.0378). The absolute serum eosinophil and basophil counts showed positive correlations with pro-collagen I alpha 1 (ρ=0.6735, p=0.0164 and ρ=0.6295, p=0.0283, respectively). In healthy subjects, forced expiratory volume in 1 second (FEV1)/forced vital capacity demonstrated significant correlation with CC chemokine ligand 3 (CCL3)/macrophage inflammatory protein 1 alpha (ρ=0.3897 and p=0.0068). FEV1 exhibited significant correlation with CCL11/eotaxin (ρ=0.4445 and p=0.0017). Conclusion Inflammatory biomarkers in EBC might be useful to predict quality of life concerning respiratory symptoms and serologic markers. Further studies are needed

A fluorescence-based assay for measuring the redox potential of 5-lipoxygenase inhibitors.

The activities and side effects of 5-lipoxygenase (5-LO) inhibitors can be predicted by identifying their redox mechanisms. In this study, we developed a fluorescence-based method to measure the redox potential of 5-LO inhibitors and compared it to the conventional, absorbance-based method. After the pseudo-peroxidase reaction, the amount of remaining lipid peroxide was quantified using the H2DCFDA (2',7'-dichlorodihydrofluorescein diacetate) fluorescence dye. Our method showed large signal windows and provided comparable redox potential values. Importantly, the redox mechanisms of known inhibitors were accurately measured with the fluorescence assay, whereas the conventional, absorbance-based method showed contradictory results. Our findings suggest that our developed method is a better alternative for classifying the redox potential of 5-LO inhibitors, and the fluorescence assay can be effectively used to study the mechanisms of action that are related to redox cycling

Femtosecond Laser Micromachining of Zirconia Green Bodies

1

Real nerve agent study assessing pyridyl reactivity: Selective fluorogenic and colorimetric detection of Soman and simulant

Herein, a chemical probe is tested with live agents for the purpose of benchmarking fluorescent pyridyl-containing systems with actual nerve agents and simulants together. The molecule showed selective fluorogenic and colorimetric detection of Soman (GD) and its simulant over other G-series nerve agents and their simulants. H-1 and P-31 NMR spectroscopy and TD-DFT calculations help reveal the origin of the colorimetric and fluorogenic changes in the reacted system. (C) 2016 Elsevier B.V. All rights reserved1661sciescopu