Can Corporate Governance Variables Enhance the Prediction Power of Accounting-Based Financial Distress Prediction Models?

We integrated accounting, corporate governance, and macroeconomic variables to build up a binary logistic regression model for the prediction of financially distressed firms. Debt ratio and ROA are found to be the most explanatory accounting variables while the percentage of directors controlled by the largest shareholder (which measures negative entrenchment effect), management participation, and the percentage of shares pledged for loans by large shareholders are shown to have positive contribution to the probability of financial distress. For macroeconomic sensitivities, firms with higher sensitivities to the annualized growth rates of manufacturing production index and money supply (M2) are more vulnerable to financial distress. As to the issue of sampling technique, we find that oversampling of distressed firms is subject to the problem of choice-based sample bias pointed out by Zmijewski (1984). The classification accuracy is overstated consequently. We try to include as many healthy firms as possible in our sample instead of following the traditional 1: 1 or 1: 2 matching principle. The results show that the classification accuracy is mostly significantly improved in our integrated prediction model when the sample is closest to the actual population. For the trade-off between type I and type II errors in the predicted probability classification, we maximize the sum of classification accuracy for both groups of firms (the healthy and the distressed). It is found that an estimated probability of financial distress of 0.2000 represents the optimal cutoff point for predicting financial distress. Under such a cutoff scheme, our integrated model produces an in-sample classification accuracy of 80.7% for distressed firms and 93.2% for healthy firms. For out-sample prediction, 90% of the distressed firms and 85.4% healthy firms in 2001 are correctly identified using an integrated model built upon samples from 1998 to 2000.Corporate governance, Financial distress prediction model, Choice-based sample bias

Controlled Synthesis of Organic/Inorganic van der Waals Solid for Tunable Light-matter Interactions

Van der Waals (vdW) solids, as a new type of artificial materials that consist of alternating layers bonded by weak interactions, have shed light on fascinating optoelectronic device concepts. As a result, a large variety of vdW devices have been engineered via layer-by-layer stacking of two-dimensional materials, although shadowed by the difficulties of fabrication. Alternatively, direct growth of vdW solids has proven as a scalable and swift way, highlighted by the successful synthesis of graphene/h-BN and transition metal dichalcogenides (TMDs) vertical heterostructures from controlled vapor deposition. Here, we realize high-quality organic and inorganic vdW solids, using methylammonium lead halide (CH3NH3PbI3) as the organic part (organic perovskite) and 2D inorganic monolayers as counterparts. By stacking on various 2D monolayers, the vdW solids behave dramatically different in light emission. Our studies demonstrate that h-BN monolayer is a great complement to organic perovskite for preserving its original optical properties. As a result, organic/h-BN vdW solid arrays are patterned for red light emitting. This work paves the way for designing unprecedented vdW solids with great potential for a wide spectrum of applications in optoelectronics

Aggregation-Induced Emission (AIE), Life and Health

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Metronomic chemotherapy prevents therapy-induced stromal activation and induction of tumor-initiating cells

Although traditional chemotherapy kills a fraction of tumor cells, it also activates the stroma and can promote the growth and survival of residual cancer cells to foster tumor recurrence and metastasis. Accordingly, overcoming the host response induced by chemotherapy could substantially improve therapeutic outcome and patient survival. In this study, resistance to treatment and metastasis has been attributed to expansion of stem-like tumor-initiating cells (TICs). Molecular analysis of the tumor stroma in neoadjuvant chemotherapy–treated human desmoplastic cancers and orthotopic tumor xenografts revealed that traditional maximum-tolerated dose chemotherapy, regardless of the agents used, induces persistent STAT-1 and NF-κB activity in carcinoma-associated fibroblasts. This induction results in the expression and secretion of ELR motif–positive (ELR(+)) chemokines, which signal through CXCR-2 on carcinoma cells to trigger their phenotypic conversion into TICs and promote their invasive behaviors, leading to paradoxical tumor aggression after therapy. In contrast, the same overall dose administered as a low-dose metronomic chemotherapy regimen largely prevented therapy-induced stromal ELR(+) chemokine paracrine signaling, thus enhancing treatment response and extending survival of mice carrying desmoplastic cancers. These experiments illustrate the importance of stroma in cancer therapy and how its impact on treatment resistance could be tempered by altering the dosing schedule of systemic chemotherapy

Can Corporate Governance Variables Enhance the Prediction Power of Accounting-Based Financial Distress Prediction Models?

Revised Draft May, 2003We integrated accounting, corporate governance, and macroeconomic variables to build up a binary logistic regression model for the prediction of financially distressed firms. Debt ratio and ROA are found to be the most explanatory accounting variables while the percentage of directors controlled by the largest shareholder (which measures negative entrenchment effect), management participation, and the percentage of shares pledged for loans by large shareholders are shown to have positive contribution to the probability of financial distress. For macroeconomic sensitivities, firms with higher sensitivities to the annualized growth rates of manufacturing production index and money supply (M2) are more vulnerable to financial distress. As to the issue of sampling technique, we find that oversampling of distressed firms is subject to the problem of choice-based sample bias pointed out by Zmijewski (1984). The classification accuracy is overstated consequently. We try to include as many healthy firms as possible in our sample instead of following the traditional 1: 1 or 1: 2 matching principle. The results show that the classification accuracy is mostly significantly improved in our integrated prediction model when the sample is closest to the actual population. For the trade-off between type I and type II errors in the predicted probability classification, we maximize the sum of classification accuracy for both groups of firms (the healthy and the distressed). It is found that an estimated probability of financial distress of 0.2000 represents the optimal cutoff point for predicting financial distress. Under such a cutoff scheme, our integrated model produces an in-sample classification accuracy of 80.7% for distressed firms and 93.2% for healthy firms. For out-sample prediction, 90% of the distressed firms and 85.4% healthy firms in 2001 are correctly identified using an integrated model built upon samples from 1998 to 2000

Chamaecyparis montane cloud forest in Taiwan: ecology and vegetation classification

Montane cloud forest is one of the most endangered ecosystems. However, there are few comprehensive studies on the distribution of subtropical montane cloud forest (SMCF). Chamaecyparis forest is one type of SMCF in Taiwan, distributed across the whole island. This study describes eleven types of this forest in Taiwan based on the Braun-Blanquet approach. Plots were selected from the National Vegetation Database of Taiwan. Two alliances were defined, both of which belong to the order Fagetalia hayatae. Topography and altitude explain the contrasting habitat requirements of these two alliances, whereas seasonality of moisture, soil properties and altitude explain differences in floristic composition at the association level. The alliance of Chamaecyparidion formosanae on slopes and ridges includes coniferous or mixed coniferous and evergreen broad-leaved forests; it is found at higher altitudes and is more influenced by the summer monsoon than the other alliance. Five associations are defined within this alliance. The alliance of Pasanio kawakamii - Machilion japonicae growing on slopes and in valleys contains evergreen broad-leaved forests or forests with a mixture of coniferous and evergreen broad-leaved species. Six associations can be determined under the alliance of Pasanio kawakamii-Machilion japonicae. Classification of each syntaxon was formalized using Cocktail Determination Key

Chamaecyparis montane cloud forest in Taiwan: ecology and vegetation classification

Montane cloud forest is one of the most endangered ecosystems. However, there are few comprehensive studies on the distribution of subtropical montane cloud forest (SMCF). Chamaecyparis forest is one type of SMCF in Taiwan, distributed across the whole island. This study describes eleven types of this forest in Taiwan based on the Braun-Blanquet approach. Plots were selected from the National Vegetation Database of Taiwan. Two alliances were defined, both of which belong to the order Fagetalia hayatae. Topography and altitude explain the contrasting habitat requirements of these two alliances, whereas seasonality of moisture, soil properties and altitude explain differences in floristic composition at the association level. The alliance of Chamaecyparidion formosanae on slopes and ridges includes coniferous or mixed coniferous and evergreen broad-leaved forests; it is found at higher altitudes and is more influenced by the summer monsoon than the other alliance. Five associations are defined within this alliance. The alliance of Pasanio kawakamii - Machilion japonicae growing on slopes and in valleys contains evergreen broad-leaved forests or forests with a mixture of coniferous and evergreen broad-leaved species. Six associations can be determined under the alliance of Pasanio kawakamii-Machilion japonicae. Classification of each syntaxon was formalized using Cocktail Determination Key

Achieving Ultrafast Hole Transfer at the Monolayer MoS₂ and CH₃NH₃PbI₃ Perovskite Interface by Defect Engineering

The performance of a photovoltaic device is strongly dependent on the light harvesting properties of the absorber layer as well as the charge separation at the donor/acceptor interfaces. Atomically thin two-dimensional transition metal dichalcogenides (2-D TMDCs) exhibit strong light–matter interaction, large optical conductivity, and high electron mobility; thus they can be highly promising materials for next-generation ultrathin solar cells and optoelectronics. However, the short optical absorption path inherent in such atomically thin layers limits practical applications. A heterostructure geometry comprising 2-D TMDCs (<i>e</i>.<i>g</i>., MoS₂) and a strongly absorbing material with long electron–hole diffusion lengths such as methylammonium lead halide perovskites (CH₃NH₃PbI₃) may overcome this constraint to some extent, provided the charge transfer at the heterostructure interface is not hampered by their band offsets. Herein, we demonstrate that the intrinsic band offset at the CH₃NH₃PbI₃/MoS₂ interface can be overcome by creating sulfur vacancies in MoS₂ using a mild plasma treatment; ultrafast hole transfer from CH₃NH₃PbI₃ to MoS₂ occurs within 320 fs with 83% efficiency following photoexcitation. Importantly, our work highlights the feasibility of applying defect-engineered 2-D TMDCs as charge-extraction layers in perovskite-based optoelectronic devices