Super-gauge Field in de Sitter Universe

The Gupta-Bleuler triplet for vector-spinor gauge field is presented in de Sitter ambient space formalism. The invariant space of field equation solutions is obtained with respect to an indecomposable representation of the de Sitter group. By using the general solution of the massless spin-$\frac{3}{2}$ field equation, the vector-spinor quantum field operator and its corresponding Fock space is constructed. The quantum field operator can be written in terms of the vector-spinor polarization states and a quantum conformally coupled massless scalar field, which is constructed on Bunch-Davies vacuum state. The two-point function is also presented, which is de Sitter covariant and analytic.Comment: 21 page

Electric jet assisted production of micro and nano-scale particles as drug delivery carriers

In this thesis, the capability of the electrohydrodynamic atomization (EHDA) process for preparing drug delivery carriers consisting of biodegradable polymeric particles with different sizes and shapes was explored. The first part of the thesis describes a detailed investigation of how the size, morphology and shape of the particles generated can be controlled through the operating parameters; specifically the flow rate, applied voltage and the properties of the solutions. Diameter and shape of the particles were greatly influenced by viscosity and applied voltage. The mean size of the particles changed from 340 nm to 4.4 μm as the viscosity increased from 2.5 mPa s to 11 mPa s. Also, using more concentrated polymer solution (30 wt%) and higher applied voltage (above 14 kV) were found to be ideal for promoting chain entanglement and shape transition from spherical to oblong to a more needle-like shape. Estradiol-loaded micro and nanoparticles were produced with mean sizes ranging from 100 nm to 4.5 μm with an encapsulation efficiency ranging between 65% to 75%. The in vitro drug release profiles of the particles started with an initial short burst phase and followed by a longer period characterised by a lower release rate. Two strategies were developed to tailor these profiles. First, ultrasound was explored as a non-invasive method to stimulate “on demand” drug release from carrier particles. Systematic investigations were carried out to determine the effect of various ultrasound exposure parameters on the release rate in particular output power, duty cycle and exposure time. These three exposure parameters were seen to have a significant enhancing effect upon the drug release rate (up to 14%). The second strategy explored was coating the surface of the particles with chitosan and gelatin. This enabled control and reduction of the prominence ‘burst release’ phase without affecting other parts of the release profile. Coating the particle surface with 1 wt% chitosan solution considerably reduces the initial release by 62%, 60% and 42% for PLGA 2 wt%, 5 wt% and 10 wt%, respectivly in the first 72 hours This work demonstrates a powerful method of generating micro and nano drug-loaded polymeric particles, with modified release behaviour and with control over the initial release

Formation of Nanostructured Al-Mg-Si Alloys and Evaluation Its Properties

In this study, nanostructured Al-Mg-Si (Al6061) alloy was prepared from elemental powders by mechanical alloying and heat treatment. 98.4% aluminum, 1% magnesium, 0.6% silicon powders were mixed and mechanically alloyed under argon atmosphere. The rotation speed of 500rpm and ball to powder ratio of 10:1 was employed. The mechanical alloyed powder was isothermally heat treated at 400 degrees Celsius for 2 h under argon atmosphere. The results showed that after 10h of milling, a solid solution of Al-Mg-Si with a grain size of ~ 40 nm was produced. The as milled and annealed powder was characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD). The microhardness values of alloy increase by increasing MA time. Mg2Si particles precipitate from solid solution during subsequent annealing. The as milled powder appeared to have good thermal stability against grain growth so that the grain size after annealing remained constant (~ 40 nm). When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3486

Antibiotic resistance and biofilm formation of Enterococcus faecalis in patient and environmental samples

Background: Enterococci are opportunistic pathogens and are a major factor in nosocomial infections. They may contain ebp operon, which upon expression makes them highly prone to biofilm formation on biotic and abiotic surfaces. Objectives: The aim of the current study was to detect the polymorphism of ebp genes in Enterococcus faecalis. Materials and Methods: Samples were isolated from patients (n = 58) and hospital environments (n = 32) of two hospitals in Tehran, Iran. All enterococcal species were identified by species-specific polymerase chain reaction (PCR); the antibiotic resistance pattern against nine antibiotics was determined. The ebp A, ebp B, ebp C and srt C genes were detected by PCR and the biofilm formation by the isolates was evaluated using the microtiter plate method. The genetic diversity of ebp genes was analyzed by restriction fragment length polymorphism (RFLP). Results: The results indicated that, 86 of patient and 29 of environmental isolates carried ebp genes. The ability of the isolates to strongly attach was 62 and 71 for patient and environmental samples, respectively. The RFLP of the ebp showed no genetic variations amongst the isolates. Conclusions: The results of the antibiotic resistance and other data suggest that there is a possible common clone of E. faecalis, which could rapidly disseminate in patients and the environment. © 2015, Ahvaz Jundishapur University of Medical Sciences

Exploiting Symmetry and Heuristic Demonstrations in Off-policy Reinforcement Learning for Robotic Manipulation

Reinforcement learning demonstrates significant potential in automatically building control policies in numerous domains, but shows low efficiency when applied to robot manipulation tasks due to the curse of dimensionality. To facilitate the learning of such tasks, prior knowledge or heuristics that incorporate inherent simplification can effectively improve the learning performance. This paper aims to define and incorporate the natural symmetry present in physical robotic environments. Then, sample-efficient policies are trained by exploiting the expert demonstrations in symmetrical environments through an amalgamation of reinforcement and behavior cloning, which gives the off-policy learning process a diverse yet compact initiation. Furthermore, it presents a rigorous framework for a recent concept and explores its scope for robot manipulation tasks. The proposed method is validated via two point-to-point reaching tasks of an industrial arm, with and without an obstacle, in a simulation experiment study. A PID controller, which tracks the linear joint-space trajectories with hard-coded temporal logic to produce interim midpoints, is used to generate demonstrations in the study. The results of the study present the effect of the number of demonstrations and quantify the magnitude of behavior cloning to exemplify the possible improvement of model-free reinforcement learning in common manipulation tasks. A comparison study between the proposed method and a traditional off-policy reinforcement learning algorithm indicates its advantage in learning performance and potential value for applications

Protective role of nutraceuticals against myocarditis

Myocarditis is an inflammatory disease of the myocardium that mostly affects young adults. The disease is commonly caused by viral infection, medications, autoimmune disorders, and inflammatory conditions. Nearly 50% of the cases of myocarditis are due to post-viral immune response in a setting of an identifiable or non-identifiable infection. The clinical manifestation is nonspecific ranging from asymptomatic courses to sudden death in infants and young patients. This review describes the properties of phytochemicals as plant-derived active ingredients which can be used in the prevention and treatment of myocarditis and its associated risk factors. Meanwhile, it has illustrated epidemiological analyses, mechanism of action, and the metabolism of phytochemicals in animal and human clinical trials. We also mentioned the precise mechanism of action by which phytochemicals elicit their anti-viral, anti-inflammatory, antioxidant, and immunomodulatory effects and how they regulate signal transduction pathways. Nevertheless, comprehensive clinical trials are required to study the properties of phytochemicals in vivo, in vitro, and in silico for a proper management of myocarditis. Our findings indicate that phytochemicals function as potent adjunctive therapeutic drugs in myocarditis and its related complications

Exploiting Intrinsic Stochasticity of Real-Time Simulation to Facilitate Robust Reinforcement Learning for Robot Manipulation

Simulation is essential to reinforcement learning (RL) before implementation in the real world, especially for safety-critical applications like robot manipulation. Conventionally, RL agents are sensitive to the discrepancies between the simulation and the real world, known as the sim-to-real gap. The application of domain randomization, a technique used to fill this gap, is limited to the imposition of heuristic-randomized models. We investigate the properties of intrinsic stochasticity of real-time simulation (RT-IS) of off-the-shelf simulation software and its potential to improve the robustness of RL methods and the performance of domain randomization. Firstly, we conduct analytical studies to measure the correlation of RT-IS with the occupation of the computer hardware and validate its comparability with the natural stochasticity of a physical robot. Then, we apply the RT-IS feature in the training of an RL agent. The simulation and physical experiment results verify the feasibility and applicability of RT-IS to robust RL agent design for robot manipulation tasks. The RT-IS-powered robust RL agent outperforms conventional RL agents on robots with modeling uncertainties. It requires fewer heuristic randomization and achieves better generalizability than the conventional domain-randomization-powered agents. Our findings provide a new perspective on the sim-to-real problem in practical applications like robot manipulation tasks

Scorpion fauna (Arachnida: Scorpiones) in Darmian county, Iran (2015-2016)

Background and purpose: Venomous bite and specific morphological features of scorpions are the most important reasons for paying attention to scorpions. Anxiety and stress caused by scorpions and their stings are amongst the important health issues in many countries especially in Iran. This study was conducted on scorpions’ fauna in Darmian County, South Khorasan province, Iran. Materials and methods: In this study, 21 districts in Darmian were sampled including plains, mountains, residential, non-residential, rural and urban areas. Sampling effort was conducted monthly in 2015-16. Scorpions were collected by actively searching in day and night using pitfall trap. The specimens were identified by appropriate identification keys. Results: Totally 685 specimens were collected. Five species including Mesobuthus eupeus, M. caucasicus Androctonus crassicauda, Orthochirus scrobiculosus, and Compsobuthus matthiesseni were identified from Butidae family. The most frequent species was M. eupeus (n= 373, 54.5%), while A. crassicauda (n= 22, 3.2%) was recognized as the least frequency species. Conclusion: Androctonus crassicauda (black scorpion) was found as the most dangerous species in Iran, so, alongside care programs for scorpionism in Darmian, prescription of anti-scorpion serum in cases stung by scorpion should be done by considering the coloring of scorpion and residential area of injured person. © 2016, Mazandaran University of Medical Sciences. All rights reserved