QCD sum rules for the production of the X(3872) as a mixed molecule-charmonium state in B meson decay

We use QCD sum rules to calculate the branching ratio for the production of the meson X(3872) in the decay B -> X(3872)K, assumed to be a mixture between charmonium and exotic molecular vertical bar c (q) over bar vertical bar vertical bar q (c) over bar vertical bar states with J(PC) = 1(++). We find that in a small range for the values of the mixing angle, 5 degrees <= theta <= 13 degrees, we get the branching ratio B(B -> XK) = (1.00 +/- 0.68) x 10(-5), which is in agreement with the experimental upper limit. This result is compatible with the analysis of the mass and decay width of the mode J/psi(n pi) and the radiative decay mode J/psi gamma performed in the same approach. (C) 2011 Elsevier B.V. All rights reserved.

QCD sum rules study of the J(PC)=1(- -) charmonium Y mesons

We use QCD sum rules to test the nature of the recently observed mesons Y(4260), Y(4350) and Y(4660), assumed to be exotic four-quark (c (c) over barq (q) over bar) or (c (c) over bars (s) over bar) states with J(PC)= 1(--). We work at leading order in alpha(s), consider the contributions of higher dimension condensates and keep terms which are linear in the strange quark mass m(s). We find for the (c (c) over bars (s) over bar) state a mass in m(Y) = (4.65 +/- 0.10) GeV which is compatible with the experimental candidate Y (4660), while for the (c (c) over barq (q) over bar) state we find a mass in m(Y) = (4.49 +/- 0.11) GeV, which is still consistent with the mass of the experimental candidate Y(4350). With the tetraquark structure we are working we cannot explain the Y(4260) as a tetraquark state. We also consider molecular D(s0)(D) over bar (s)* and D(0)(D) over bar* states. For the D(s0)(D) over bar (s)* molecular state we get m(Ds0 (D) over bars*) = (4.42 +/- 0.10) GeV which is consistent, considering the errors, with the mass of the meson Y(4350) and for the D(0)(D) over bar* molecular state we get m(D0 (D) over bar*) = (4.27 +/- 0.10) GeV in excellent agreement with the mass of the meson Y(4260). (C) 2008 Elsevier B.V. All rights reserved.

QCD sum rules study of the meson Z(+)(4430)

We use QCD sum rules to study the recently observed meson Z(+)(4430), considered as a D*D-1 molecule with J(P) = 0(-). We consider the contributions of condensates up to dimension eight and work at leading order in alpha(s). We get m(Z) = (4.40 +/- 0.10) GeV in a very good agreement with the experimental value. We also make predictions for the analogous mesons Z(s) and Z(bb) considered as D-s*D-1 and B*B-1 molecules, respectively. For Z(s) we predict mZ(s) = (4.70 +/- 0.06) GeV, which is above the D-s* D-1 threshold, indicating that it is probably a very broad state and, therefore, difficult to observe experimentally. For Z(bb) we predict m(Zbb) = (10.74 +/- 0.12) GeV, in agreement with quark model predictions. (c) 2008 Elsevier B.V. All rights reserved.

rho D*D* vertex from QCD sum rules

We calculate the form factors and the coupling constant in the rho D*D* vertex in the framework of QCD sum rules. We evaluate the three point correlation functions of the vertex considering both rho and D* mesons off-shell. The form factors obtained are very different but give the same coupling constant: g rho D*D* = 6.60 +/- 0.31. This number is 50% larger than what we would expect from SU(4) estimates. (c) 2007 Elsevier B.V. All rights reserved.

"I like being under those rules here": Students Using the College Library

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

A web based decision support system for status assessment in advanced parkinson

The purpose of this work is to develop a web based decision support system, based onfuzzy logic, to assess the motor state of Parkinson patients on their performance in onscreenmotor tests in a test battery on a hand computer. A set of well defined rules, basedon an expert’s knowledge, were made to diagnose the current state of the patient. At theend of a period, an overall score is calculated which represents the overall state of thepatient during the period. Acceptability of the rules is based on the absolute differencebetween patient’s own assessment of his condition and the diagnosed state. Anyinconsistency can be tracked by highlighted as an alert in the system. Graphicalpresentation of data aims at enhanced analysis of patient’s state and performancemonitoring by the clinic staff. In general, the system is beneficial for the clinic staff,patients, project managers and researchers.

A fuzzy logic controller for intestinal levodopa infusion in Parkinson’s disease

The aim of this work is to evaluate the fuzzy system for different types of patients for levodopa infusion in Parkinson Disease based on simulation experiments using the pharmacokinetic-pharmacodynamic model. Fuzzy system is to control patient’s condition by adjusting the value of flow rate, and it must be effective on three types of patients, there are three different types of patients, including sensitive, typical and tolerant patient; the sensitive patients are very sensitive to drug dosage, but the tolerant patients are resistant to drug dose, so it is important for controller to deal with dose increment and decrement to adapt different types of patients, such as sensitive and tolerant patients. Using the fuzzy system, three different types of patients can get useful control for simulating medication treatment, and controller will get good effect for patients, when the initial flow rate of infusion is in the small range of the approximate optimal value for the current patient’ type.

ANFIS BASED MODELS FOR ACCESSING QUALITY OF WIKIPEDIA ARTICLES

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.

DC Motor Speed Control via Fuzzy / Pole Placement / PI Controller

This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.

A fuzzy rule-based decision support system for Duodopa treatment in Parkinson

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.