The Value of Academic Directors to Stakeholders: Evidence on Corporate Social Responsibility Reporting

This study explores the regulatory setting in Taiwan and examines the association between academic directors and corporate social responsibility (CSR) reporting. We find that firms with academic directors on the board are more likely to issue a stand-alone CSR report and obtain third-party assurance on their CSR reports. We also find a positive association between CSR reporting and academic directors with industry expertise. Further cross-sectional analyses indicate that the positive relation between academic directors (and their industry expertise) and CSR reporting is stronger in firms with higher growth, greater institutional ownership, and lower control-ownership divergence. Our findings that the presence of academic directors can promote better sustainability reporting suggest that academic directors contribute not only to shareholder value but also to wider stakeholder interests

Dichlorido{N′-[(pyridin-2-yl)methyl­idene-κN]acetohydrazide-κ2 N′,O}copper(II)

In the title compound, [CuCl2(C8H9N3O)], the CuII atom has a distorted square-pyramidal CuCl2N2O coordination geometry. The tridentate acetohydrazide ligand occupies three basal positions, the fourth basal position being defined by a chloride anion at a distance of 2.2116 (6) Å. The second chloride anion is in the apical position and forms a longer Cu—Cl distance of 2.4655 (7) Å. Inter­molecular N—H⋯Cl hydrogen bonds are present in the crystal, leading to the formation of chains along [10]

Combination of G72 Genetic Variation and G72 Protein Level to Detect Schizophrenia: Machine Learning Approaches

The D-amino acid oxidase activator (DAOA, also known as G72) gene is a strong schizophrenia susceptibility gene. Higher G72 protein levels have been implicated in patients with schizophrenia. The current study aimed to differentiate patients with schizophrenia from healthy individuals using G72 single nucleotide polymorphisms (SNPs) and G72 protein levels by leveraging computational artificial intelligence and machine learning tools. A total of 149 subjects with 89 patients with schizophrenia and 60 healthy controls were recruited. Two G72 genotypes (including rs1421292 and rs2391191) and G72 protein levels were measured with the peripheral blood. We utilized three machine learning algorithms (including logistic regression, naive Bayes, and C4.5 decision tree) to build the optimal predictive model for distinguishing schizophrenia patients from healthy controls. The naive Bayes model using two factors, including G72 rs1421292 and G72 protein, appeared to be the best model for disease susceptibility (sensitivity = 0.7969, specificity = 0.9372, area under the receiver operating characteristic curve (AUC) = 0.9356). However, a model integrating G72 rs1421292 only slightly increased the discriminative power than a model with G72 protein alone (sensitivity = 0.7941, specificity = 0.9503, AUC = 0.9324). Among the three models with G72 protein alone, the naive Bayes with G72 protein alone had the best specificity (0.9503), while logistic regression with G72 protein alone was the most sensitive (0.8765). The findings remained similar after adjusting for age and gender. This study suggests that G72 protein alone, without incorporating the two G72 SNPs, may have been suitable enough to identify schizophrenia patients. We also recommend applying both naive Bayes and logistic regression models for the best specificity and sensitivity, respectively. Larger-scale studies are warranted to confirm the findings

Comparative Study of Some Population-based Optimization Algorithms on Inverse Scattering of a Two-Dimensional Perfectly Conducting Cylinder in Slab Medium

[[abstract]]The application of four techniques for the shape reconstruction of a 2-D metallic cylinder buried in dielectric slab medium by measured the cattered fields outside is studied in the paper. The finite-difference time-domain (FDTD) technique is employed for electromagnetic analyses for both the forward and inverse scattering problems, while the shape reconstruction problem is transformed into optimization one during the course of inverse scattering. Then, four techniques including asynchronous particle swarm optimization (APSO), PSO, dynamic differential evolution (DDE) and self-adaptive DDE (SADDE) are applied to reconstruct the location and shape of the 2-Dmetallic cylinder for comparative purposes. The statistical performances of these algorithms are compared. The results show that SADDE outperforms PSO, APSO and DDE in terms of the ability of exploring the optima. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

RINGdb: An integrated database for G protein-coupled receptors and regulators of G protein signaling

BACKGROUND: Many marketed therapeutic agents have been developed to modulate the function of G protein-coupled receptors (GPCRs). The regulators of G-protein signaling (RGS proteins) are also being examined as potential drug targets. To facilitate clinical and pharmacological research, we have developed a novel integrated biological database called RINGdb to provide comprehensive and organized RGS protein and GPCR information. RESULTS: RINGdb contains information on mutations, tissue distributions, protein-protein interactions, diseases/disorders and other features, which has been automatically collected from the Internet and manually extracted from the literature. In addition, RINGdb offers various user-friendly query functions to answer different questions about RGS proteins and GPCRs such as their possible contribution to disease processes, the putative direct or indirect relationship between RGS proteins and GPCRs. RINGdb also integrates organized database cross-references to allow users direct access to detailed information. The database is now available at . CONCLUSION: RINGdb is the only integrated database on the Internet to provide comprehensive RGS protein and GPCR information. This knowledgebase will be useful for clinical research, drug discovery and GPCR signaling pathway research

Efficacy of green onion root extract in cosmetics and skin care products

In this study, leftover roots of Sansing green onions grown without toxic chemicals in Sansing Township, Ilan County, Taiwan were used as a raw material of skincare products. The raw material was extracted from the green onion roots by ultrasound in a low-temperature, safe and pollution-free environment. We hope to develop cleansers and other facial care products made of this natural, environmentally friendly, safe and affordable raw material so that people with sensitive skin can also use these products. We also hope that this study can contribute to circular economy and achieve the goal of green innovation by recycling the leftover roots. In terms of anti-oxidation, the DPPH free radical scavenging ability of 2.5 mg/mL green onion root extract was equivalent to 98% of that of 1 mg/mL BHT; the Fe2+ chelating ability was equivalent to 87.0% of that of 0.02 mg/mL EDTA; the superoxide anions scavenging ability of 2.5 mg/mL green onion root extract was equivalent to 84.2% of that of 1 mg/mL BHT and 80.4% of that of 0.05 mg/mL vitamin C. With respect to melanin synthesis inhibition, the green onion root extract's ability to inhibit dopachrome, the intermediate product of melanin, was positively correlated to its concentration, i.e., the higher the concentration of the green onion root extract, the better the inhibition ability. The IC50 of green onion root extract was 1.83 mg/mL, while, for comparison, the IC50 of vitamin C was 0.62 mg/mL. Furthermore, according to the cell survival assay, no obvious cytotoxic effect was found with the increase in the concentration of the green onion root extract. The whitening effect improved after 30 days of test. The improvement rate was 5.6% for 2.5 mg/mL green onion root extract, 3.1% for 1.25 mg/mL extract, and 1.7% for 0.625 mg/mL extract. The moisture retention also improved after 30 days of test. The moisture retention improvement rate was 22.7% for 2.5 mg/mL green onion root extract, 21.6% for 1.25 mg/mL extract, and 15.4% for 0.625 mg/mL extract. Based on the experiments, the green onion root extract obtained from ultrasound not only did not cause skin allergy and irritation but also showed anti-aging, melanin synthesis inhibition, whitening and moisture retention effects. The results showed that the green onion root extract can improve the moisture retention and whitening effect of the mask

Intraprostatic injection of botulinum toxin type- A relieves bladder outlet obstruction in human and induces prostate apoptosis in dogs

BACKGROUND: With the increasing interest with botulinum toxin – A (BTX-A) application in the lower urinary tract, we investigated the BTX-A effects on the canine prostate and also in men with bladder outlet obstruction (BOO) due to benign prostatic hyperplasia (BPH). METHODS: Transperineal injection into the prostate using transrectal ultrasound (TRUS) was performed throughout the study. Saline with or without 100 U of BTX-A was injected into mongrel dogs prostate. One or 3 months later, the prostate was harvested for morphologic and apoptotic study. In addition, eight BPH patients refractory to α-blockers were treated with ultrasound guided intraprostatic injection of 200 U of BTX-A. RESULTS: In the BTX-A treated dogs, atrophy and diffuse apoptosis was observed with H&E stain and TUNEL stain at 1 and 3 months. Clinically, the mean prostate volume, symptom score, and quality of life index were significantly reduced by 18.8%, 73.1%, and 61.5% respectively. Maximal flow rate significantly increased by 72.0%. CONCLUSION: Intraprostatic BTX-A injection induces prostate apotosis in dogs and relieves BOO in humans. It is therefore a promising alternative treatment for refractory BOO due to BPH

Antinociceptive Activities and the Mechanisms of Anti-Inflammation of Asiatic Acid in Mice

Asiatic acid (AA), a pentacyclic triterpene compound in the medicinal plant Centella asiatica, was evaluated for antinociceptive and anti-inflammatory effects. Treatment of male ICR mice with AA significantly inhibited the numbers of acetic acid-induced writhing responses and the formalin-induced pain in the late phase. In the anti-inflammatory test, AA decreased the paw edema at the 4th and 5th h after λ-carrageenan (Carr) administration and increased the activities of catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) in the liver tissue. AA decreased the nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β) levels on serum level at the 5th h after Carr injection. Western blotting revealed that AA decreased Carr-induced inducible nitric oxide synthase (iNOS), cyclooxygenase (COX-2), and nuclear factor-κB (NF-κB) expressions at the 5th h in the edema paw. An intraperitoneal (i.p.) injection treatment with AA also diminished neutrophil infiltration into sites of inflammation as did indomethacin (Indo). The anti-inflammatory mechanisms of AA might be related to the decrease in the level of MDA, iNOS, COX-2, and NF-κB in the edema paw via increasing the activities of CAT, SOD, and GPx in the liver

Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Mixture-of-Experts (MoE) models have gained popularity in achieving state-of-the-art performance in a wide range of tasks in computer vision and natural language processing. They effectively expand the model capacity while incurring a minimal increase in computation cost during training. However, deploying such models for inference is difficult due to their large size and complex communication pattern. In this work, we provide a characterization of two MoE workloads, namely Language Modeling (LM) and Machine Translation (MT) and identify their sources of inefficiencies at deployment. We propose three optimization techniques to mitigate sources of inefficiencies, namely (1) Dynamic gating, (2) Expert Buffering, and (3) Expert load balancing. We show that dynamic gating improves maximum throughput by 6.21-11.23$\times$ for LM, 5.75-10.98$\times$ for MT Encoder and 2.58-5.71$\times$ for MT Decoder. It also reduces memory usage by up to 1.36$\times$ for LM and up to 1.1$\times$ for MT. We further propose Expert Buffering, a new caching mechanism that only keeps hot, active experts in GPU memory while buffering the rest in CPU memory. This reduces static memory allocation by up to 1.47$\times$. We finally propose a load balancing methodology that provides additional scalability to the workload