Non-Destructive Discrimination of arbitrary set of orthogonal quantum states by NMR using Quantum Phase Estimation

An algorithm based on quantum phase estimation, which discriminates quantum states nondestructively within a set of arbitrary orthogonal states, is described and experimentally verified by a NMR quantum information processor. The procedure is scalable and can be applied to any set of orthogonal states. Scalability is demonstrated through Matlab simulation

Singlet state creation and Universal quantum computation in NMR using Genetic Algorithm

Experimental implementation of a quantum algorithm requires unitary operator decomposition. Here we treat the unitary operator decomposition as an optimization problem and use Genetic Algorithm, a global optimization method inspired by nature's evolutionary process for operator decomposition. As an application, we apply this to NMR Quantum Information Processing and find a probabilistic way of doing universal quantum computation using global hard pulses. We also demonstrate efficient creation of singlet state (as a special case of Bell state) directly from thermal equilibrium using an optimum sequence of pulses

Various Component handling services for Software Defined Networking (SDN)

Software Defined Networking (SDN) provides us the platform for the easy management of various components, which was not possible in traditional networks. SDN is flexible and scalable because of the separation between control and data plane. OpenFlow protocol acts as the interface between both planes. The concept is that we can create control logic and implement it in network elements of the data plane through centralized control. The controller and the policy need to be updated regularly to meet the requirement of the network. In this paper we have discussed the need of security approaches that can detect any kind of fault or abnormal behavior with in the network and to manage the packet flow metrics. Also how can we distribute the global policy across each of the element in data plane so that the global policy becomes local to each networking elements

The Components that can Build Flexible

SDN (Software Defined Network) is a new networking approach towards current networking industry. S.D.N has attarcted the researchers attention, because there is wide scope of innovation and research. The main concept behind the SDN networks is the separation of controller from data plane. This natural feature makes SDN adaptive of being flexible and scalable. We are mentioning some of the important components those are needed to make current SDN networks even better and efficient that can be managed easily and updated whenever needed, without any interruption of services. Also we have discussed how we can manage the data plane, control plane and how we can identify where fault has occurred

A Hybrid Metaheuristics based technique for Mutation Based Disease Classification

Due to recent advancements in computational biology, DNA microarray technology has evolved as a useful tool in the detection of mutation among various complex diseases like cancer. The availability of thousands of microarray datasets makes this field an active area of research. Early cancer detection can reduce the mortality rate and the treatment cost. Cancer classification is a process to provide a detailed overview of the disease microenvironment for better diagnosis. However, the gene microarray datasets suffer from a curse of dimensionality problems also the classification models are prone to be overfitted due to small sample size and large feature space. To address these issues, the authors have proposed an Improved Binary Competitive Swarm Optimization Whale Optimization Algorithm (IBCSOWOA) for cancer classification, in which IBCSO has been employed to reduce the informative gene subset originated from using minimum redundancy maximum relevance (mRMR) as filter method. The IBCSOWOA technique has been tested on an artificial neural network (ANN) model and the whale optimization algorithm (WOA) is used for parameter tuning of the model. The performance of the proposed IBCSOWOA is tested on six different mutation-based microarray datasets and compared with existing disease prediction methods. The experimental results indicate the superiority of the proposed technique over the existing nature-inspired methods in terms of optimal feature subset, classification accuracy, and convergence rate. The proposed technique has illustrated above 98% accuracy in all six datasets with the highest accuracy of 99.45% in the Lung cancer dataset

Comparative study of hypospadias morphology with normal age-matched subjects

Background: Hypospadias is the most common congenital malformation of the penis, affecting about 4-6 males per 1000 births, and ranging in severity from a ventrally located urethral meatus that is slightly off-center to tip of penis to up to the perineal area. The current research is intended towards studying the morphology of hypospadias and undertakes a comparison with the age matched population. Methods: It was an observational, cross-sectional study conducted in the Department of General Surgery, Himalayan institute of medical sciences, Swami Ram Nagar, Dehradun, Uttarakhand, India over the period of 12 months. We included a total of 120 study subjects, consisting of 60 cases and 60 controls. All patients of hypospadias with no other genital pathology visiting the OPD for the 1st time were included. Patients were categorized as having distal (distal to corona), mid (proximal to corona & up to distal shaft), or proximal hypospadias (in the shaft). Mean maximum width, thickness and vertical length of the glans, stretched penile length, diameter and circumference of penile shaft were recorded. Results: Variables like stretched penile length, width and circumference of mid penile shaft and variables like urethral plate, urethral groove, breadth of dorsal hood, maximum width and thickness of glans were found to be insignificant when compared with controls. However, vertical length of glans among cases was significantly less when compared with controls. Conclusions: A significant association between vertical length of glans between controls and cases was found

CHANGES IN URINARY MONOAMINE METABOLITES WITH ANTIPSYCHOTIC TREATMENT IN SCHIZOPHRENIA

Objective: Monoamine neurotransmitters have been considered important mediators of schizophrenia pathology and antipsychotic drug action. Thisstudy examines the level of monoamine metabolites, homovanillic acid (HVA), 5-hydroxy indole acetic acid (5-HIAA), and vanillylmandelic acid (VMA),monoamine metabolites of major neurotransmitters dopamine, serotonin and norepinephrine, respectively in urine of patients with schizophrenia ascompared to normal controls and the change in monoamine metabolites with antipsychotic treatment.Methods: Thirty-four drug-free patients with schizophrenia diagnosed with Diagnostic and Statistical Manual of Mental Disorders Fourth Edition(DSM-IV) criteria and 15 normal controls were taken for the study. Patients were assessed for psychopathology using positive and negative syndromescale (PANSS) scale at baseline and 4 weeks after the treatment. Urinary monoamine metabolites (HVA, 5-HIAA, and VMA) were measured before andafter 4 weeks of treatment using high-performance liquid chromatography.Results: There was a trend toward higher levels of HVA and VMA in the patients as compared to controls. There was a trend toward reduction in 5-HIAAlevels with treatment in patients with schizophrenia. No correlation was found between the levels of monoamine metabolites and psychopathology.Significant positive correlation was found between 5-HIAA with VMA and HVA.Conclusion: The present study indicates that noninvasive measurement of monoamine metabolites in urine may be of value in differentiating patientswith schizophrenia from controls.Keywords: Monoamine, Homovanillic acid, 5-Hydroxy indole acetic acid, Vanillyl mandelic acid, Schizophrenia.Â

Applied Mathematics for Pharmaceutical Problems Using Robotics as Assistive Tools for Learning: A Comprehensive Review

Smart machine endures getting smarter as they are going to access more about the facts and pieces of evidence that make our work even more authentic than before. The term “robot” was created in 1920 by Czechoslovakian playwright Karel Capek and has been a principal point in science fiction ever since. Pharmacy automation involves machine-driven or mechanical processes of distributing, dispensing and managing medications. Pharmaceutical organizations take advantage of robotics to manoeuvre biological or chemical samples around to integrate novel chemical structure or to test the pharmaceutical value of remaining organic material. Pharmaceutical applications with aid of robotic systems are progressively accepted for enhanced throughput and proficiency to satisfy this growing demand, within a rapidly ageing population that directly requires sophisticated medical devices and newer drugs. According to Robot IQ, mathematics is one of the few main robotics attributes that cannot be learned along the way. A good background in many fields of mathematics and science is needed for robotics at the very least. Several studies have shown that robotics is an effective medium for teaching STEM (Science, Technology, Engineering, and Mathematics) skills to students. Thus, Novel methods are under development in machine learning, symbolic reasoning and signal processing which may be utilized in production and packaging concerned to the pharmaceuticals. The target is to review the Planning, Safety, Reliability, Accuracy, Quality, Flexibility, Redeployment, Efficiency and other vital applications of Robotics in Pharmacy