Optimal Sampling-based Motion Planning in Gaussian Belief Space for Minimum Sensing Navigation

In this paper, we consider the motion planning problem in Gaussian belief space for minimum sensing navigation. Despite the extensive use of sampling-based algorithms and their rigorous analysis in the deterministic setting, there has been little formal analysis of the quality of their solutions returned by sampling algorithms in Gaussian belief space. This paper aims to address this lack of research by examining the asymptotic behavior of the cost of solutions obtained from Gaussian belief space based sampling algorithms as the number of samples increases. To that end, we propose a sampling based motion planning algorithm termed Information Geometric PRM* (IG-PRM*) for generating feasible paths that minimize a weighted sum of the Euclidean and an information-theoretic cost and show that the cost of the solution that is returned is guaranteed to approach the global optimum in the limit of large number of samples. Finally, we consider an obstacle-free scenario and compute the optimal solution using the "move and sense" strategy in literature. We then verify that the cost returned by our proposed algorithm converges to this optimal solution as the number of samples increases.Comment: 19 pages, 10 figure

Optimized Data Rate Allocation for Dynamic Sensor Fusion over Resource Constrained Communication Networks

This paper presents a new method to solve a dynamic sensor fusion problem. We consider a large number of remote sensors which measure a common Gauss-Markov process and encoders that transmit the measurements to a data fusion center through the resource restricted communication network. The proposed approach heuristically minimizes a weighted sum of communication costs subject to a constraint on the state estimation error at the fusion center. The communication costs are quantified as the expected bitrates from the sensors to the fusion center. We show that the problem as formulated is a difference-of-convex program and apply the convex-concave procedure (CCP) to obtain a heuristic solution. We consider a 1D heat transfer model and 2D target tracking by a drone swarm model for numerical studies. Through these simulations, we observe that our proposed approach has a tendency to assign zero data rate to unnecessary sensors indicating that our approach is sparsity promoting, and an effective sensor selection heuristic

Improving antibacterial efficiency of curcumin in magnetic polymeric nanocomposites

In recent years, resistance to chemical antibiotics, as well as their side effects, has caused a necessity to utilize natural substances and herbal components with antibacterial effects. Curcumin, the major substance of Curcuma longa’s rhizome, was used as an antibacterial agent since ancient times. This work aimed to formulate a novel nanocomposite for the delivery of curcumin to overcome orthodox drugs resistance against bacteria and improve its efficacy. To fabricate targeting nanocomposites, first, Fe3O4 nanoparticles were synthesized followed by coating the obtained nanoparticles using sodium alginate containing curcumin. A 2 by 3 factorial design was tailored to predict the optimum formulation of nanocomposites. Characterization of nanocomposites including particle size, polydispersity index (PDI), zeta potential, entrapment efficiency, and drug loading was performed. The optimum formulation was analyzed by differential scanning calorimetry (DSC), scanning electron microscopy (SEM), Fourier-transformed infrared spectroscopy (FT-IR), and in vitro release study at different pHs. Finally, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of samples against seven common bacteria were determined. Results showed that the optimized formulation contained 400 nm particles with the PDI and zeta potentials of 0.4 and − 58 mV, respectively. The optimized formulation with 70% entrapment efficiency reduced the MIC value 2 to 4 times in comparison with pure curcumin. Results also showed that polymer and drug concentrations can significantly affect entrapment efficiency. In conclusion, the current investigation demonstrated that this magnetic nanocomposite can be applied for the delivery of curcumin

Comparison of Honey versus Polylactide Anti-Adhesion Barrier on Peritoneal Adhesion and Healing of Colon Anastomosis in Rabbits

BACKGROUND: Postoperative adhesion is still a consequence of intra-abdominal surgeries, which results in bowel obstruction and abdominopelvic pain. Bowel anastomosis as a common abdominal surgery has the incidence of leakage in up to 30% of patients that increase morbidity and mortality. Due to similar pathways of adhesion formation and wound healing, it is important to find a way to reduce adhesions and anastomosis leakage. AIM: This study was designed to compare antiadhesive as well as anastomosis healing improvement effect of honey and polylactide anti-adhesive barrier film. METHODS: Forty-five rabbits divided into three groups of honey, adhesion barrier film, and control group in an animal study. Under a similar condition, rabbits underwent resection and anastomosis of cecum under general anaesthesia. In the first group, honey was used at the anastomosis site, in the second one polylactide adhesion barrier film utilised, and the third one was the control group. Adhesion, as well as anastomosis leakage, was assessed after 21 days. Data were analysed using the Statistical Package for Social Scientists (SPSS) for Windows version 25. RESULTS: Three groups of 15 rabbits were studied. The results showed that mean peritoneal adhesion score (PAS) was lower in the honey group (1.67) in comparison to the adhesion barrier film group (3.40) and the control group (6.33). CONCLUSION: Bio-absorbable polylactide barrier has an anti-adhesion effect but is not suitable for intestinal anastomosis in rabbits. Further studies needed to evaluate these effects on human beings

Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12·2 million (95% UI 11·0–13·6) incident cases of stroke, 101 million (93·2–111) prevalent cases of stroke, 143 million (133–153) DALYs due to stroke, and 6·55 million (6·00–7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8–12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1–6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0–73·0), prevalent strokes increased by 85·0% (83·0–88·0), deaths from stroke increased by 43·0% (31·0–55·0), and DALYs due to stroke increased by 32·0% (22·0–42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0–18·0), mortality decreased by 36·0% (31·0–42·0), prevalence decreased by 6·0% (5·0–7·0), and DALYs decreased by 36·0% (31·0–42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0–24·0) and incidence rates increased by 15·0% (12·0–18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5–3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5–3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57–8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97–3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01–1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7–90·8] DALYs or 55·5% [48·2–62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3–48·6] DALYs or 24·3% [15·7–33·2]), high fasting plasma glucose (28·9 million [19·8–41·5] DALYs or 20·2% [13·8–29·1]), ambient particulate matter pollution (28·7 million [23·4–33·4] DALYs or 20·1% [16·6–23·0]), and smoking (25·3 million [22·6–28·2] DALYs or 17·6% [16·4–19·0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.publishedVersio