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Criteria of efficiency for conformal prediction

We study optimal conformity measures for various criteria of efficiency of classification in an idealised setting. This leads to an important class of criteria of efficiency that we call probabilistic; it turns out that the most standard criteria of efficiency used in literature on conformal prediction are not probabilistic unless the problem of classification is binary. We consider both unconditional and label-conditional conformal prediction.Comment: 31 page

Artificial Neural Network Modeling of Drying Kinetics and Color Changes of Ginkgo Biloba Seeds during Microwave Drying Process

Ginkgo biloba seeds were dried in microwave drier under different microwave powers (200, 280, 460, and 640 W) to determinate the drying kinetics and color changes during drying process. Drying curves of all samples showed a long constant rate period and falling rate period along with a short heating period. The effective moisture diffusivities were found to be 3.318 × 10−9 to 1.073 × 10−8 m2/s within the range of microwave output levels and activation energy was 4.111 W/g. The L⁎ and b⁎ values of seeds decreased with drying time. However, a⁎ value decreased firstly and then increased with the increase of drying time. Artificial neural network (ANN) modeling was employed to predict the moisture ratio and color parameters (L⁎, a⁎, and b⁎). The ANN model was trained for finite iteration calculation with Levenberg-Marquardt algorithm as the training function and tansig-purelin as the network transfer function. Results showed that the ANN methodology could precisely predict experimental data with high correlation coefficient (0.9056–0.9834) and low mean square error (0.0014–2.2044). In addition, the established ANN models can be used for online prediction of moisture content and color changes of ginkgo biloba seeds during microwave drying process

Pharmacologic Stem Cell Based Intervention as a New Approach to Osteoporosis Treatment in Rodents

Background: Osteoporosis is the most prevalent skeletal disorder, characterized by a low bone mineral density (BMD) and bone structural deterioration, leading to bone fragility fractures. Accelerated bone resorption by osteoclasts has been established as a principal mechanism in osteoporosis. However, recent experimental evidences suggest that inappropriate apoptosis of osteoblasts/osteocytes accounts for, at least in part, the imbalance in bone remodeling as occurs in osteoporosis. The aim of this study is to examine whether aspirin, which has been reported as an effective drug improving bone mineral density in human epidemiology studies, regulates the balance between bone resorption and bone formation at stem cell levels. Methods and Findings: We found that T cell-mediated bone marrow mesenchymal stem cell (BMMSC) impairment plays a crucial role in ovariectomized-induced osteoporosis. Ex vivo mechanistic studied revealed that T cell-mediated BMMSC impairment was mainly attributed to the apoptosis of BMMSCs via the Fas/Fas ligand pathway. To explore potential of using pharmacologic stem cell based intervention as an approach for osteoporosis treatment, we selected ovariectomy (OVX)-induced osteoporosis mouse model to examine feasibility and mechanism of aspirin-mediated therapy for osteoporosis. We found that aspirin can inhibit T cell activation and Fas ligand induced BMMSC apoptosis in vitro. Further, we revealed that aspirin increases osteogenesis of BMMSCs by aiming at telomerase activity and inhibits osteoclast activity in OVX mice, leading to ameliorating bone density. Conclusion: Our findings have revealed a novel osteoporosis mechanism in which activated T cells induce BMMSC apoptosis via Fas/Fas ligand pathway and suggested that pharmacologic stem cell based intervention by aspirin may be a new alternative in osteoporosis treatment including activated osteoblasts and inhibited osteoclasts. © 2008 Yamaza et al

FSD-C10: A more promising novel ROCK inhibitor than Fasudil for treatment of CNS autoimmunity.

Rho-Rho kinase (Rho-ROCK) triggers an intracellular signalling cascade that regulates cell survival, death, adhesion, migration, neurite outgrowth and retraction and influences the generation and development of several neurological disorders. Although Fasudil, a ROCK inhibitor, effectively suppressed encephalomyelitis (EAE), certain side effects may limit its clinical use. A novel and efficient ROCK inhibitor, FSD-C10, has been explored. In the present study, we present chemical synthesis and structure of FSD-C10, as well as the relationship between compound concentration and ROCK inhibition. We compared the inhibitory efficiency of ROCKI and ROCK II, the cell cytotoxicity, neurite outgrowth and dendritic formation, neurotrophic factors and vasodilation between Fasudil and FSD-C10. The results demonstrated that FSD-C10, like Fasudil, induced neurite outgrowth of neurons and dendritic formation of BV-2 microglia and enhanced the production of neurotrophic factor brain-derived neurotrophic factor (BDNF), glial cell line-derived neurotrophic factor (GDNF) and neurotrophin-3 (NT-3). However, the cell cytotoxicity and vasodilation of FSD-C10 were relatively small compared with Fasudil. Although Fasudil inhibited both ROCK I and ROCK II, FSD-C10 more selectively suppressed ROCK II, but not ROCK I, which may be related to vasodilation insensitivity and animal mortality. Thus, FSD-C10 may be a safer and more promising novel ROCK inhibitor than Fasudil for the treatment of several neurological disorders