A Data Hiding Method Based on Partition Variable Block Size with Exclusive-or Operation on Binary Image

In this paper, we propose a high capacity data hiding method applying in binary images. Since a binary image has only two colors, black or white, it is hard to hide data imperceptible. The capacities and imperception are always in a trade-off problem. Before embedding we shuffle the secret data by a pseudo-random number generator to keep more secure. We divide the host image into several non-overlapping (2n+1) by (2n+1) sub-blocks in an M by N host image as many as possible, where n can equal 1, 2, 3 , …, or min(M,N). Then we partition each sub-block into four overlapping (n+1) by (n+1) sub-blocks. We skip the all blacks or all whites in each (2n+1) by (2n+1) sub-blocks. We consider all four (n+1) by (n+1) sub-blocks to check the XOR between the non overlapping parts and center pixel of the (2n+1) by (2n+1) sub-block, it embed n 2 bits in each (n+1) by (n+1) sub-block, totally are 4*n 2 . The entire host image can be embedded 4×n 2×M/(2n+1)×N/(2n+1) bits. The extraction way is simply to test the XOR between center pixel with their non-overlapping part of each sub-block. All embedding bits are collected and shuffled back to the original order. The adaptive means the partitioning sub-block may affect the capacities and imperception that we want to select. The experimental results show that the method provides the large embedding capacity and keeps imperceptible and reveal the host image lossless

An Optimal Sizing Design Approach of Hybrid Energy Sources for Various Electric Vehicles

In this paper, we present a discussion about green energy sources that have been widely utilized in electric vehicles (EVs). To achieve different requirements of various EVs, the correct sizing of energy sources is crucial so that the cost and output performance will be optimized. In this research, three energy sources, supercapacitors (SCs), lithium titanate oxide (LTO) batteries, and Nickel Manganese Cobalt (NCM) (or Li3) batteries, were considered for hybridization. An effective global search algorithm (GSA) was designed for optimal sizing of hybrid electric energy systems (HEESs). The GSA procedures were: (1) vehicle specification and performance requirements of energy sources, (2) determination of cost function and constraints, (3) GSA optimization with for-loops, (4) optimal results. Five examples of EVs, the electric sedan, long-distance electric bus, short-distance electric bus, electric forklift, and electric sports car, were analyzed for optimal hybrid energy combination under different criteria and specifications. The GSA effectively optimized the designs of energy sizing. The performance indices and vehicle requirements studied were the specific price, specific energy at a constant volume, specific energy at a constant mass, and specific power at a constant mass for three energy sources, SCs, LTO batteries, and Li batteries. The vehicle requirements including the maximum output power, vehicle acceleration, climbability, and maximum speed have been formulated as the design constraints. A numerical analysis of five types of EVs was analyzed for optimal sizing of the HEES and the optimal position of the DC/DC converter with the lowest cost function. The integrated system and control designs of the HESS using the GSA, more applications for green energy sources, and different types of EVs will be studied in the future

An Optimal Sizing Design Approach of Hybrid Energy Sources for Various Electric Vehicles

In this paper, we present a discussion about green energy sources that have been widely utilized in electric vehicles (EVs). To achieve different requirements of various EVs, the correct sizing of energy sources is crucial so that the cost and output performance will be optimized. In this research, three energy sources, supercapacitors (SCs), lithium titanate oxide (LTO) batteries, and Nickel Manganese Cobalt (NCM) (or Li3) batteries, were considered for hybridization. An effective global search algorithm (GSA) was designed for optimal sizing of hybrid electric energy systems (HEESs). The GSA procedures were: (1) vehicle specification and performance requirements of energy sources, (2) determination of cost function and constraints, (3) GSA optimization with for-loops, (4) optimal results. Five examples of EVs, the electric sedan, long-distance electric bus, short-distance electric bus, electric forklift, and electric sports car, were analyzed for optimal hybrid energy combination under different criteria and specifications. The GSA effectively optimized the designs of energy sizing. The performance indices and vehicle requirements studied were the specific price, specific energy at a constant volume, specific energy at a constant mass, and specific power at a constant mass for three energy sources, SCs, LTO batteries, and Li batteries. The vehicle requirements including the maximum output power, vehicle acceleration, climbability, and maximum speed have been formulated as the design constraints. A numerical analysis of five types of EVs was analyzed for optimal sizing of the HEES and the optimal position of the DC/DC converter with the lowest cost function. The integrated system and control designs of the HESS using the GSA, more applications for green energy sources, and different types of EVs will be studied in the future

Cancer-Derived VEGF-C Increases Chemokine Production in Lymphatic Endothelial Cells to Promote CXCR2-Dependent Cancer Invasion and MDSC Recruitment

Breast cancer-derived vascular endothelial growth factor-C (VEGF-C) has been shown to enhance lymphangiogenesis in lymph nodes to accelerate cancer metastasis. However, the remodeling of lymph node microenvironments by VEGF-C remains elusive. By in vivo selection, we established a subline (named as “LC”) with strong lymphatic tropism and high VEGF-C expression from the human MDA-MB-231 breast cancer cell line. Co-culture with LC cells or treatment with LC-conditioned medium upregulated the expression of CXC chemokines in lymphatic endothelial cells (LECs), which could be inhibited by pre-incubation with VEGF-C-neutralizing antibodies and VEGFR3 inhibitors. The chemokines produced by LECs enhanced recruitment of myeloid-derived suppressor cells (MDSCs) to tumor-draining and distant lymph nodes in tumor-bearing mice. Treatment with a CXCR2 inhibitor after tumor cell inoculation dramatically decreased the number of MDSCs in lymph nodes, suggesting the importance of the chemokine/CXCR2 signaling axis in MDSC recruitment. In addition, LEC-released chemokines also stimulated the expression of serum amyloid A1 (SAA1) in cancer cells, enhancing their lymphatic invasion by increasing VE-cadherin phosphorylation, junction disruption, and vascular permeability of LECs. Clinical sample validation confirmed that SAA1 expression was associated with increased lymph node metastasis. Collectively, we reveal a novel mechanism by which cancer cell-derived VEGF-C remodels lymphovascular microenvironments by regulating chemokine production in LECs to promote cancer invasion and MDSC recruitment. Our results also suggest that inhibition of CXCR2 is effective in treating lymphatic metastasis

Effects of board game play on nursing students’ medication knowledge: A randomized controlled trial.

[[abstract]]Aim: This study aimed to examine the effectiveness of an educational board game in improving nursing students' medication knowledge. Background: Maintaining patient safety is a core practice for nurses. Medication management is a central principle of patient safety. Nurses acquire pharmacology knowledge and medication safety skills in the classroom training. Thus, solidifying and strengthening nursing students' medication knowledge are crucial tasks for nursing faculty members. In recent years, board games, which offer both entertainment and competitive play, have been employed to educate students in a variety of disciplines and settings. Through board game play, students can learn in an enjoyable and fun atmosphere. Design: A randomized controlled trial design. Methods: A convenience sample of 69 nursing students was obtained from a university in Taiwan. Participants were randomly assigned either to an experimental (board game) group (n = 35) or a comparison group (n = 34) using block randomization. The experimental group engaged in board game play to learn about medications, whereas the comparison group attended a one-hour didactic lecture. Using questionnaires, data were collected before the intervention, immediately post intervention and one month post intervention. Results: Following the intervention, regardless of the learning method, both groups showed significant improvements in their immediate recall of medication information. However, when retested after one month, the experimental group obtained significantly higher scores than the comparison group. Moreover, students in the experimental group reported more satisfaction with the learning method than those in the comparison group. Conclusions: The study results suggest that learning through board games could enhance nursing students' retention of knowledge. Students reported favorable reactions to using a board game learning method for increasing knowledge of medication. With respect to this finding, faculty members may consider employing board games as teaching tools in nursing and other health science courses. Moreover, the findings of this study can also provide additional information for nursing managers in hospital wards or long-term care facilities where nurses are trained to familiarize themselves with frequently administered medications. Tweetable abstract: Board game play can enhance nursing students' retention of knowledge; students reported positive reactions to game-based learning for medication training