Accounting-based variables as an early warning indicator of financial distress in crisis and non-crisis periods

Financial integration in the Association of Southeast Asian Nations (ASEAN) region is a key focus of the ASEAN Economic Community. Whereas many studies focus on modelling corporate default, this paper identifies early warning indicators of financial distress before a default, using multiple discriminant analysis (MDA) models with a sample of listed and delisted companies in the ASEAN region. The analysis examines 720 companies in 10 different industries across six ASEAN countries from 1997 to 2016. The study constructs individual models for each country as well as an overall model for the entire region, using both in-sample and out-of-sample approaches. This overall model could be useful for an integrated banking system. To ensure robustness, the study also separately examines the predictive performance of the MDA models across different economic crises: the Asian financial crisis (AFC) from 1997 to 2000, the global financial crisis (GFC) from 2007 to 2009 and their pre- and post-crisis periods. We find that profitability ratios are the best indicators of financial distress in the ASEAN region, followed by liquidity and leverage ratios. In addition, our findings reveal common indicators that can be used to predict financial distress across ASEAN countries. The single model performs reasonably well in predicting financial distress 1 year ahead. In addition, the model is extended to incorporate a market-based indicator into the MDA models, the distance to default. However, the inclusion of this indicator does not significantly improve the accuracy of the models in predicting financial distress at listed firms in the ASEAN region

Tournament-Based Incentives and Mergers and Acquisitions

This research examines the relation between tournament-based incentives, which are proxied by the difference between a firm’s CEO pay and the median pay of the senior managers, and mergers and acquisitions (M&As). We find that tournament-based incentives are positively related to firm acquisitiveness and acquiring firms’ stock and operating performance. Further analysis indicates that positive acquisition performance increases the likelihood of the CEO being promoted from inside the acquiring firm. Our evidence is consistent with the view that tournament-based incentives motivate acquiring firms’ managers to make greater efforts and take more risk that result in superior acquisition performance

Defect-engineered metal-organic frameworks (MOF-808) towards the improved adsorptive removal of organic dyes and chromium (vi) species from water

In this work, two defective zirconium-based metal-organic frameworks (Zr-MOFs), MOF-808-OH and MOF-808-NH2, were synthesized by partially replacing the 1,3,5-benzenetricarboxylate building block with 5-hydroxyisophthalate and 5-aminoisophthalate, respectively. The structural features of the defective materials were analyzed by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), nitrogen physisorption at 77 K, and thermogravimetric analysis (TGA). Importantly, the number of defect sites determined via proton nuclear magnetic resonance (1H-NMR) analysis of the digested materials was approximately 7 mol% for MOF-808-OH and 3 mol% for MOF-808-NH2. The presence of the defect sites increased the number of acidic centers on Zr-clusters originating from missing-linker nodes which accounted for a remarkable adsorption capacity towards various anionic organic dyes and chromium (vi) species. Compared to standard MOF-808, the defect-engineered ones showed significant increments by 30-60% in trapping capacity for anionic contaminants including sunset yellow, quinoline yellow, methyl orange, and potassium dichromate, while they exhibited modest improvements by 5-15% in the removal of cationic dyes, namely malachite green and methylene blue

iCONTRA: Toward Thematic Collection Design Via Interactive Concept Transfer

Creating thematic collections in industries demands innovative designs and cohesive concepts. Designers may face challenges in maintaining thematic consistency when drawing inspiration from existing objects, landscapes, or artifacts. While AI-powered graphic design tools offer help, they often fail to generate cohesive sets based on specific thematic concepts. In response, we introduce iCONTRA, an interactive CONcept TRAnsfer system. With a user-friendly interface, iCONTRA enables both experienced designers and novices to effortlessly explore creative design concepts and efficiently generate thematic collections. We also propose a zero-shot image editing algorithm, eliminating the need for fine-tuning models, which gradually integrates information from initial objects, ensuring consistency in the generation process without influencing the background. A pilot study suggests iCONTRA's potential to reduce designers' efforts. Experimental results demonstrate its effectiveness in producing consistent and high-quality object concept transfers. iCONTRA stands as a promising tool for innovation and creative exploration in thematic collection design. The source code will be available at: https://github.com/vdkhoi20/iCONTRA.Comment: CHI 202

Protocol for Biospecimen Collection and Analysis within the BACPAC Research Program

The Biospecimen Collection and Processing Working Group of the NIH HEAL Initiative BACPAC Research Program was charged with identifying molecular biomarkers of interest to chronic low back pain (cLBP). Having identified biomarkers of interest, the Working Group worked with the New York University Grossman School of Medicine, Center for Biospecimen Research and Development-funded by the Early Phase Pain Investigation Clinical Network Data Coordinating Center-to harmonize consortium-wide and site-specific efforts for biospecimen collection and analysis. Biospecimen collected are saliva, blood (whole, plasma, serum), urine, stool, and spine tissue (paraspinal muscle, ligamentum flavum, vertebral bone, facet cartilage, disc endplate, annulus fibrosus, or nucleus pulposus). The omics data acquisition and analyses derived from the biospecimen include genomics and epigenetics from DNA, proteomics from protein, transcriptomics from RNA, and microbiomics from 16S rRNA. These analyses contribute to the overarching goal of BACPAC to phenotype cLBP and will guide future efforts for precision medicine treatment

The Back Pain Consortium (BACPAC) Research Program Data Harmonization: Rationale for Data Elements and Standards

ObjectiveOne aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses.MethodsConsortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium.ResultsClinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC.ConclusionsBACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs

Development of a standardized histopathology scoring system using machine learning algorithms for intervertebral disc degeneration in the mouse model—An ORS spine section initiative

Mice have been increasingly used as preclinical model to elucidate mechanisms and test therapeutics for treating intervertebral disc degeneration (IDD). Several intervertebral disc (IVD) histological scoring systems have been proposed, but none exists that reliably quantitate mouse disc pathologies. Here, we report a new robust quantitative mouse IVD histopathological scoring system developed by building consensus from the spine community analyses of previous scoring systems and features noted on different mouse models of IDD. The new scoring system analyzes 14 key histopathological features from nucleus pulposus (NP), annulus fibrosus (AF), endplate (EP), and AF/NP/EP interface regions. Each feature is categorized and scored; hence, the weight for quantifying the disc histopathology is equally distributed and not driven by only a few features. We tested the new histopathological scoring criteria using images of lumbar and coccygeal discs from different IDD models of both sexes, including genetic, needle-punctured, static compressive models, and natural aging mice spanning neonatal to old age stages. Moreover, disc sections from common histological preparation techniques and stains including H&E, SafraninO/Fast green, and FAST were analyzed to enable better cross-study comparisons. Fleiss\u27s multi-rater agreement test shows significant agreement by both experienced and novice multiple raters for all 14 features on several mouse models and sections prepared using various histological techniques. The sensitivity and specificity of the new scoring system was validated using artificial intelligence and supervised and unsupervised machine learning algorithms, including artificial neural networks, k-means clustering, and principal component analysis. Finally, we applied the new scoring system on established disc degeneration models and demonstrated high sensitivity and specificity of histopathological scoring changes. Overall, the new histopathological scoring system offers the ability to quantify histological changes in mouse models of disc degeneration and regeneration with high sensitivity and specificity

Enzyme-linked immunoassay for dengue virus IgM and IgG antibodies in serum and filter paper blood

BACKGROUND: The reproducibilty of dengue IgM and IgG ELISA was studied in serum and filter paper blood spots from Vietnamese febrile patients. METHODS: 781 pairs of acute (t0) and convalescent sera, obtained after three weeks (t3) and 161 corresponding pairs of filter paper blood spots were tested with ELISA for dengue IgG and IgM. 74 serum pairs were tested again in another laboratory with similar methods, after a mean of 252 days. RESULTS: Cases were classified as no dengue (10 %), past dengue (55%) acute primary (7%) or secondary (28%) dengue. Significant differences between the two laboratories' results were found leading to different diagnostic classification (kappa 0.46, p < 0.001). Filter paper results correlated poorly to serum values, being more variable and lower with a mean (95% CI) difference of 0.82 (0.36 to 1.28) for IgMt3, 0.94 (0.51 to 1.37) for IgGt0 and 0.26 (-0.20 to 0.71) for IgGt3. This also led to differences in diagnostic classification (kappa value 0.44, p < 0.001) The duration of storage of frozen serum and dried filter papers, sealed in nylon bags in an air-conditioned room, had no significant effect on the ELISA results. CONCLUSION: Dengue virus IgG antibodies in serum and filter papers was not affected by duration of storage, but was subject to inter-laboratory variability. Dengue virus IgM antibodies measured in serum reconstituted from blood spots on filter papers were lower than in serum, in particular in the acute phase of disease. Therefore this method limits its value for diagnostic confirmation of individual patients with dengue virus infections. However the detection of dengue virus IgG antibodies eluted from filter paper can be used for sero-prevalence cross sectional studies

Noble Metal Nanoparticles for Biosensing Applications

In the last decade the use of nanomaterials has been having a great impact in biosensing. In particular, the unique properties of noble metal nanoparticles have allowed for the development of new biosensing platforms with enhanced capabilities in the specific detection of bioanalytes. Noble metal nanoparticles show unique physicochemical properties (such as ease of functionalization via simple chemistry and high surface-to-volume ratios) that allied with their unique spectral and optical properties have prompted the development of a plethora of biosensing platforms. Additionally, they also provide an additional or enhanced layer of application for commonly used techniques, such as fluorescence, infrared and Raman spectroscopy. Herein we review the use of noble metal nanoparticles for biosensing strategies—from synthesis and functionalization to integration in molecular diagnostics platforms, with special focus on those that have made their way into the diagnostics laboratory

The impacts of the COVID-19 lockdowns on the work of academic staff at higher education institutions: an international assessment

The COVID-19 pandemic severely disrupted the life of millions of people around the world and brought changes in many contexts. In higher education institutions, teaching staff had to quickly adapt their teaching and research practices and revisit learning and student engagement strategies. In this context, this paper aimed to report on how the lockdowns influenced the work and lives of academic staff at universities. The methodology consisted of an online survey that collected 201 responses across 39 countries worldwide, and the results were explored using descriptive and exploratory modelling analyses. The findings reveal that the main positive aspect of the work-from-home experience during the lockdowns was the reduction of time spent on commuting, while the inability to disconnect and difficulties in work–life balance were the most commonly indicated negative aspects. The principal component analysis indicated that the pandemic had a moderate power in boosting academic staff towards sustainability, and an important potential of revising academic curricula and teaching–learning relationships. Based on the evidence gathered, recommendations to allow academic staff to better cope with the influence of future pandemics include the increased use of digital resources and new teaching styles, curricula revision for encouraging educators to include more issues related to sustainable development in their teaching and greater institutional support to reduce stressful conditions and improve productivity