A Distributed Epigenetic Shape Formation and Regeneration Algorithm for a Swarm of Robots

Living cells exhibit both growth and regeneration of body tissues. Epigenetic Tracking (ET), models this growth and regenerative qualities of living cells and has been used to generate complex 2D and 3D shapes. In this paper, we present an ET based algorithm that aids a swarm of identically-programmed robots to form arbitrary shapes and regenerate them when cut. The algorithm works in a distributed manner using only local interactions and computations without any central control and aids the robots to form the shape in a triangular lattice structure. In case of damage or splitting of the shape, it helps each set of the remaining robots to regenerate and position themselves to build scaled down versions of the original shape. The paper presents the shapes formed and regenerated by the algorithm using the Kilombo simulator.Comment: 8 pages, 9 figures, GECCO-18 conferenc

Unravelling the potential of nitric acid as a surface modifier for improving the hemocompatibility of metallocene polyethylene for blood contacting devices

Design of blood compatible surfaces is obligatory to minimize platelet surface interactions and improve the thromboresistance of foreign surfaces when they are utilized as biomaterials particularly for blood contacting devices. Pure metallocene polyethylene (mPE) and nitric acid (HNO3) treated mPE antithrombogenicity and hydrophilicity were investigated. The contact angle of the mPE treated with HNO3 decreased. Surface of mPE and HNO3 treated mPE investigated with FTIR revealed no major changes in its functional groups. 3D Hirox digital microscopy, SEM and AFM images show increased porosity and surface roughness. Blood coagulation assays prothrombin time (PT) and activated partial thromboplastin time (APTT) were delayed significantly (P < 0:05) for HNO3 treated mPE. Hemolysis assay and platelet adhesion of the treated surface resulted in the lysis of red blood cells and platelet adherence, respectively indicating improved hemocompatibility of HNO3 treated mPE. To determine that HNO3 does not deteriorate elastic modulus of mPE, the elastic modulus of mPE and HNO3 treated mPE was compared and the result shows no significant difference. Hence, the overall observation suggests that the novel HNO3 treated mPE may hold great promises to be exploited for blood contacting devices like grafts, catheters, and etc

Development of Nanocrystalline Cellulose (NCC) from Microcrystalline Cellulose (MCC) via Dissolution using Ionic Liquid: 1-butyl-3-methylimidazolium hydrogen sulfate (BMIM HSO4)

Nanocrystalline Cellulose (NCC) was prepared by dissolution of Microcrystalline Cellulose (MCC) using Ionic Liquid: 1-butyl-3-methylimidazolium hydrogen sulfate (BMIM HSO4) at dissolution temperatures of 70 °C, 80 °C, and 90 °C, and dissolution time of 30 minutes and 1 hour respectively. Morphological properties of NCC and MCC were examined using Field Electron Scanning Electron Microscope (FESEM). Chemical characterization of NCC was performed for the analysis of crystallinity (Xc) using X-ray Diffraction (XRD) and to analyze the bonds that are present in NCC and MCC using Fourier Transform Infrared Spectroscopy (FTIR). FTIR was also used to analyze the chemical bonds in unused BMIM HSO4 and regenerated BMIM HSO4. Reduction of MCC particle size by BMIM HSO4 dissolution was clearly observed from FESEM images. The crystallinity of NCC obtained through dissolution of MCC in BMIM HSO4 showed a significant increase due to the degradation of amorphous region in cellulose. Both MCC and NCC have the same chemical bonds. Chemical bonds in regenerated BMIM HSO4 were unchanged, indicating that BMIM HSO4 can be recycled and reused

Charging Forward: Creating A Productive Framework For Promoting Electric Vehicle Adoption Among U.S. Cities Based on Development Stage

Electric vehicles are among the most promising innovations to date for their role in minimizing human-induced carbon emissions and combating climate change. Despite the clear need for this technology, the U.S. is struggling to promote its adoption, with electric vehicles accounting for a dismal 2% of the new automobile market—less than half of the global average. This disparity raises the logical question: “What can U.S. cities do to increase electric vehicle use?” To address this, I conducted a comparative analysis of the 2020 electric mobility action plans for two U.S. cities (San Jose, California and Denver, Colorado). These cities were selected because of their state, adoption rate, promotion efforts, and digitally-accessible action plans. To compare the action plans from both cities, I used a discourse and word cloud analysis and identified four areas of focus from both cities: (i) vehicle cost, (ii) charging infrastructure, (iii) fleet electrification, and (iv) public awareness. Due to significant variation between U.S. cities, I categorized cities into five levels of development: L1: Rural, L2: Town, L3: City, L4: Advanced City, and L5: Future City. Based on criteria such as population, adoption rate, charging infrastructure, and adoption goals, I used Denver as a reference point for Level 3 and San Jose for Level 4. From this analysis, I establish best practices for electric vehicle promotion efforts for cities at each of the five development stages. By creating this productive framework, I hope to facilitate and accelerate efforts for electric vehicle promotion among U.S. cities

A Swarm intelligence based approach to the mine detection problem

In this paper, we have applied a swarm intelligence based technique to a mine detection problem. Swarm intelligence techniques are used to model robotic agents to solve the problem. Studies made on the ant colonies, which is a typical member of the family of swarms, are applied in devising the techniques for the agents. Ant colony models bestow intelligence not only at the individual level, but more at the collective level (the interactions produced by the individual members in trying to solve a common problem). An analysis of the results obtained with a computer simulation of the mine detection is also presented

A Comparative Cross-sectional study on the Fasting and Postprandial Lipid levels as a Risk factor for Retinopathy in Patients with Type 2 Diabetes Mellitus

Background: The global prevalence of diabetes mellitus (DM) continues to rise, posing a significant public health challenge worldwide. Type 2 DM accounts for a substantial portion of this burden, characterized by chronic hyperglycaemia resulting from defects in insulin secretion, action, or both. Diabetic retinopathy, a microvascular complication of DM, is a leading cause of visual disability and blindness globally. Objective: To assess the relationship and importance between fasting dyslipidaemia vs postprandial dyslipidaemia as a risk factor for Diabetic retinopathy in these people. Methods: A study was conducted among diabetic patients in outpatient and inpatient units over 2 years. The sample size was determined based on the prevalence of diabetic retinopathy. Patients were recruited through purposive sampling. Demographic data were collected, fasting and 6-hour postprandial lipid levels were analysed. Ophthalmic evaluation was performed to assess diabetic retinopathy. Results: The study included 160 patients with a mean age of 56.66±8.16 years, with nearly equal gender distribution. Diabetic retinopathy was present in 18.8% of patients, with varying severity. There were significant associations between retinopathy and parameters such as random and postprandial blood glucose levels, HbA1c, and duration of DM. Additionally, There were significant differences in lipid profiles between patients with and without retinopathy, both in fasting and postprandial states. Conclusion: This study highlights the significant association between dyslipidaemia, particularly elevated triglycerides and LDL cholesterol, and the presence of retinopathy in patients with Type 2 DM. These findings show the importance of maintaining lower lipid levels for the prevention and management of diabetic retinopath