Distributed Biogeography Based Optimization for Mobile Robots

I present hardware testing of an evolutionary algorithm (EA) known as distributed biogeography based optimization (DBBO). DBBO is an extended version of biogeography based optimization (BBO). Typically, EAs require a central computer to control the evaluation of candidate solutions to some optimization problem, and to control the sharing of information between those candidate solutions. DBBO, however, does not require a centralized unit to control individuals. Individuals independently run the EA and find a solution to a given optimization problem. Both BBO and DBBO are based on the theory of biogeography, which describes how organisms are distributed geographically in nature. I have compared the performance of BBO and DBBO by using fourteen benchmark functions that are commonly used to evaluate the performance of optimization algorithms. I perform both hardware and simulation experiments. Wall-following robots are used as hardware to implement the DBBO algorithm. Robots use two different controllers to maintain a constant distance from the wall: one is a proportional integral derivative (PID) controller and the other is a fuzzy controller. DBBO optimizes the performance of the robots with respect to the control parameters. During simulation experiments I used different EA mutation rates different staring points for the robots and different wheel bases. I have also done T-tests to analyze the statistical significance of performance differences and robustness tests to analyze the performance of the algorithms in the face of environmental changes. The results show that centralized BBO gives better optimization results than distributed BBO. DBBO gives less optimal solutions but it removes the necessity of centralized control. The results also show that the fuzzy controller performs better than the PID controlle

Status of ψ\psi (3686), ψ\psi (4040), ψ\psi (4160), Y (4260), ψ\psi (4415) and X (4630) charmonia like states

We examine the status of charmonia like states by looking into the behaviour of the energy level differences and regularity in the behaviour of the leptonic decay widths of the excited charmonia states. The spectroscopic states are studied using a phenomenological Martin-like confinement potential and their radial wave functions are employed to compute the di-leptonic decay widths. Their deviations from the expected behaviour provide a clue to consider them as admixtures of the nearby S and D states. The present analysis strongly favour \\backslash$psi \$ (3686) as admixture of $c \bar{c}$ (2S) and $c \bar{c}$g (4.1 GeV) hybrid, \\backslash$psi \$ (4040) and \$$\backslash$psi \$ (4160) as admixture states of charmonia (3S, 3D) states with mixing angle \$$\backslash$theta \$ = 11$^\circ$and 45$^\circ$respectively. We identify Y (4260) as a pure$c \bar{c}$(4S) state whose leptonic decay is predicted as 0.65 keV. While X(4630) is closer to the$c \bar{c}$(6S) state. The status of \$$\backslash$psi \$ (4415) is still not clear as it does not fit to be pure or admixture state

Elucidating the Effects of Interstitial Fluid Flow on Hepatocellular Carcinoma Invasion

Over the last two decades with advancements in research, detection, and treatment of all cancer types in the United States, resulting in an overall 23% decrease in cancer related deaths, liver cancer has gone against this trend possessing an increased death rate. Globally, hepatocellular carcinoma (HCC), the most common form of liver cancer, ranks as the second leading cause of cancer related deaths with approximately 788,000 deaths annually. In recent years much emphasis has been placed on understanding the process of HCC cell invasion; however, it has become apparent that the progression of this disease is not solely dependent on just the cancer cells or biological factors, but also their interaction with the tumor microenvironment. A significant number of studies have shown that changes in biomechanical forces within the tumor microenvironment can alter cancer progression. Previous research has demonstrated that interstitial fluid flow (IFF), one of the biomechanical forces that is altered during tumor growth, can promote cancer cell invasion. The findings in this work elucidate the effects of IFF in HCC cell invasion. Using our 3D in vitro flow invasion assay, we demonstrate that IFF increases cellular invasion through autologous gradient formation of chemokines (CXCR4/CXCL12) that promote migration, a mechanism known as autologous chemotaxis. We also demonstrated that MEK/ERK signaling affects IFF-induced invasion; however, this pathway was separate from CXCR4/CXCL12 signaling. Increased matrix metalloproteinase (MMP) expression is a hallmark for cancer progression and poor prognosis. Biomechanical forces have been observed to increase the secretion of these proteolytic enzymes, which promote extracellular matrix degradation and tumor cell invasion. We observed an increase in MMP-9 and MMP-2 activity in HCC cells exposed to IFF. In total these findings indicate multiple mechanisms are at play in HCC flow-induced invasion, further emphasizing the significance biomechanical forces play in disease progression. Finally, by modifying our 3D in vitro flow invasion assay, we examined IFF in a relevant cell-based disease model where HCC cells are embedded in a stiff matrix. The increase in matrix stiffness is a result of tumor growth, shown to disturb the mechanical forces and biochemical signaling that occurs in the microenvironment, effectively promoting disease progression. HCC also possesses a very unique disease profile and risk factors; nearly 80% of HCCs occur from patients who suffer from chronic fibrosis or cirrhosis, where inflammation and hepatic wound-healing response attributes to the hepatocarcinogenesis. Many studies have observed cellular behavior of hepatocytes and HCC cells in a stiff matrix; however, none have observed the effect of IFF and a stiff microenvironment in HCC cells. The findings in this chapter confirm a synergistic relationship between IFF and matrix stiffness on HCC cell invasion. Ultimately the findings in this study provide a better foundational and mechanistic understanding of IFF and its effects on HCC cell invasion adding to the mounting evidence of how biomechanical forces in the tumor microenvironment influence cancer progression.Ph.D., Biomedical Engineering -- Drexel University, 201

Distributed Learning with Biogeography-Based Optimization

We present hardware testing of an evolutionary algorithm known as biogeography-based optimization (BBO) and extend it to distributed learning. BBO is an evolutionary algorithm based on the theory of biogeography, which describes how nature geographically distributes organisms. We introduce a new BBO algorithm that does not use a centralized computer, and which we call distributed BBO. BBO and distributed BBO have been developed by mimicking nature to obtain an algorithm that optimizes solutions for different situations and problems. We use fourteen common benchmark functions to obtain results from BBO and distributed BBO, and we also use both algorithms to optimize robot control algorithms. We present not only simulation results, but also experimental results using BBO to optimize the control algorithms of mobile robots. The results show that centralized BBO generally gives better optimization results and would generally be a better choice than any of the newly proposed forms of distributed BBO. However, distributed BBO allows the user to find a less optimal solution to a problem while avoiding the need for centralized, coordinated control

A STUDY ON THE PRESCRIBING PATTERN OF ANTI-DIABETIC DRUGS IN A COMMUNITY CLINIC IN TELANGANA STATE

Objectives: There are many variations in prescribing patterns of Diabetes mellitus with hypertension which requires lifelong treatment as enormously increased the burden of chronic diseases and needs much care while choosing drugs. In a tertiary care Centre, prescribing pattern are powerful tools to ascertain the role of drugs in society. Hence, there is a need for appropriate, safe, effective and economical study to find out the patterns of drug therapy among diabetic hypertensive patients with other complications.Methods: Retrospective, randomized and non-interventional study design was conducted from September 2014 to November 2014 at a Community Clinic in Telangana State. The collected data are thoroughly analyzed and prescriptions were checked for appropriateness. For easy sorting all data obtained were entered into Microsoft Excel 2000 and cross-checked for accuracy. The data collected were analyzed to obtain averages, percentages and standard deviations. The data were grouped on the bases of age, gender, fasting blood glucose, blood pressure, co morbidities, various classes of drugs and analyzed for significance.Results: A total of 109 patients were included in this two months study. All the patients had Type 2 diabetes, while 18 patients also had Hypertension (on treatment). All the patients were on treatment for Type 2 Diabetes. The mean fasting Blood sugar was 119.27±40.34 mg/dl, while the mean post-prandial blood sugar was 212.78±67.35 mg/dl. The average number of OHAs per prescription was 1.99±0.54. About 19.26% of the patients were on monotherapy with Metformin, while all the other patients received a combination of oral hypoglycemic agents. Insulin was used in 2.75% of the patients. Among combinations, the most commonly used combination was glibenclamide and metformin 41.2%.Conclusion: Metformin is the drug of choice and glibenclamide is the most preferred combination with Metformin. Insulin was not preferred as monotherapy. Despite combination therapy, the post-prandial glucose levels were not in range–suggesting either poor patient compliance or inadequate dosing/inappropriate therapy. In addition to drugs, the services of a clinical pharmacist might be helpful in these patients.Â

Efficacy and safety of dual blockade of the renin-angiotensin system: meta-analysis of randomised trials

Objective To compare the long term efficacy and adverse events of dual blockade of the renin-angiotensin system with monotherapy. Design Systematic review and meta-analysis. Data sources PubMed, Embase, and the Cochrane central register of controlled trials, January 1990 to August 2012. Study selection Randomised controlled trials comparing dual blockers of the renin-angiotensin system with monotherapy, reporting data on either long term efficacy (≥1 year) or safety events (≥4 weeks), and with a sample size of at least 50. Analysis was stratified by trials with patients with heart failure versus patients without heart failure. Results 33 randomised controlled trials with 68 405 patients (mean age 61 years, 71% men) and mean duration of 52 weeks were included. Dual blockade of the renin-angiotensin system was not associated with any significant benefit for all cause mortality (relative risk 0.97, 95% confidence interval 0.89 to 1.06) and cardiovascular mortality (0.96, 0.88 to 1.05) compared with monotherapy. Compared with monotherapy, dual therapy was associated with an 18% reduction in admissions to hospital for heart failure (0.82, 0.74 to 0.92). However, compared with monotherapy, dual therapy was associated with a 55% increase in the risk of hyperkalaemia (P less than 0.001), a 66% increase in the risk of hypotension (P less than 0.001), a 41% increase in the risk of renal failure (P=0.01), and a 27% increase in the risk of withdrawal owing to adverse events (P less than 0.001). Efficacy and safety results were consistent in cohorts with and without heart failure when dual therapy was compared with monotherapy except for all cause mortality, which was higher in the cohort without heart failure (P=0.04 v P=0.15), and renal failure was significantly higher in the cohort with heart failure (P less than 0.001 v P=0.79). Conclusion Although dual blockade of the renin-angiotensin system may have seemingly beneficial effects on certain surrogate endpoints, it failed to reduce mortality and was associated with an excessive risk of adverse events such as hyperkalaemia, hypotension, and renal failure compared with monotherapy. The risk to benefit ratio argues against the use of dual therapy

Introducing Astrocytes on a Neuromorphic Processor: Synchronization, Local Plasticity and Edge of Chaos

While there is still a lot to learn about astrocytes and their neuromodulatory role in the spatial and temporal integration of neuronal activity, their introduction to neuromorphic hardware is timely, facilitating their computational exploration in basic science questions as well as their exploitation in real-world applications. Here, we present an astrocytic module that enables the development of a spiking Neuronal-Astrocytic Network (SNAN) into Intel's Loihi neuromorphic chip. The basis of the Loihi module is an end-to-end biophysically plausible compartmental model of an astrocyte that simulates the intracellular activity in response to the synaptic activity in space and time. To demonstrate the functional role of astrocytes in SNAN, we describe how an astrocyte may sense and induce activity-dependent neuronal synchronization, switch on and off spike-time-dependent plasticity (STDP) to introduce single-shot learning, and monitor the transition between ordered and chaotic activity at the synaptic space. Our module may serve as an extension for neuromorphic hardware, by either replicating or exploring the distinct computational roles that astrocytes have in forming biological intelligence.Comment: 9 pages, 7 figure