Background Cold atmospheric plasma (CAP) is widely used in the cancer therapy field. This type of plasma is very close to room temperature. This paper illustrates the effects of CAP on breast cancer tissues both in vivo and in vitro. Methods The mouse mammary adenocarcinoma cell line AN3 was used for the in vivo study, and the MCF7, AMJ13, AMN3, and HBL cell lines were used for the in vitro study. A floating electrode-dielectric barrier discharge (FE-DBD) system was used. The cold plasma produced by the device was tested against breast cancer cells. Results The induced cytotoxicity percentages were 61.7%, 68% and 58.07% for the MCF7, AMN3, and AMJ13 cell lines, respectively, whereas the normal breast tissue HBL cell line exhibited very little or no cytotoxicity. Reactive oxygen species (ROS) were measured, and we found that more ROS were generated under the impact of CAP in cancer cells, whereas the normal HBL cell line had the lowest ROS level. The in vivo study showed that CAP treatment could reduce the volume of treated tumors compared to those in untreated mice. Conclusions CAP has anticancer effects both in vitro and in vivo and this effect is mediated by the ROS and induce apoptosis in p53 independent pathway. the current method is promising for breast cancer therapy.
In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show MoreKinematics is the mechanics branch which dealswith the movement of the bodies without taking the force into account. In robots, the forward kinematics and inverse kinematics are important in determining the position and orientation of the end-effector to perform multi-tasks. This paper presented the inverse kinematics analysis for a 5 DOF robotic arm using the robotics toolbox of MATLAB and the Denavit-Hartenberg (D-H) parameters were used to represent the links and joints of the robotic arm. A geometric approach was used in the inverse kinematics solution to determine the joints angles of the robotic arm and the path of the robotic arm was divided into successive lines to accomplish the required tasks of the robotic arm.Therefore, this
... Show MoreIn this study water quality index (WQI) was calculated to classify the flowing water in the Tigris River in Baghdad city. GIS was used to develop colored water quality maps indicating the classification of the river for drinking water purposes. Water quality parameters including: Turbidity, pH, Alkalinity, Total hardness, Calcium, Magnesium, Iron, Chloride, Sulfate, Nitrite, Nitrate, Ammonia, Orthophosphate and Total dissolved solids were used for WQI determination. These parameters were recorded at the intakes of the WTPs in Baghdad for the period 2004 to 2011. The results from the annual average WQI analysis classified the Tigris River very poor to polluted at the north of Baghdad (Alkarkh WTP) while it was very poor to very polluted in t
... Show MoreA hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreTo obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which shows the reliability and applicability of the proposed approach.
Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of
... Show MoreFace recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.
Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting
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