This study shows the effects of copper material electrode, applied voltage, and different pressure values on electrical discharge plasma. The purpose of the work is the application of the spectral analysis method to obtain accurate results of nitrogen plasma parameters. By using the optical emission spectroscopy (OES), many N2 molecular spectra peaks appeared in the range from 300 to 480 nm. Also, some additional peaks were recorded, corresponding to atomic and ionic lines for nitrogen, target material, and hydrogen, in all samples. The electron density (ne) was calculated from the measurement of Stark broadening effect, which was found to decrease with increasing pressure from 0.1 mba
... Show MoreThe present study aimed to the isolation and identification of Penicillium chrysogenum from subclinical bovine mastitis as well as the evaluation of their potential to produce the main virulence factors by assessing proteinase production, urease production, growth rate at 37 ̊C, and hemolytic activity on Blood agar. One hundred milk samples were assembled from the White Gold village and surrounded outlying farms of Abu-Ghraib, Baghdad province, during the period from November 2018 to March 2019. Each milk sample was tested for California Mastitis (CMT). The results indicated that 85% of the samples gave positive (+ve) results for CMT. Sixty six mycotic isolates were detected, including 31 isolates of Peni
... Show MoreA review of the literature on intellectual capital development was conducted using systemic criteria for the inclusion of relevant studies. The concepts behind the ideas explored in the present study were discussed in respect to the subject matter. Examining the past state of the art in the intellectual capital sector for achieving high levels of innovation performance provided a multidimensional picture of intellectual capital, innovation performance, and dynamic capabilities. The present review was designed to illustrate the correlation between intellectual capital and innovation performance, as well as the role of dynamic capabilities in moderating the relationship between these constructs. Accordingly, we presented an extensive
... Show MoreThe Internet of Things (IoT) has great importance in the medical industry. The creation of intelligent sensors, intelligent machines, and superior algorithms for lightweight communication made it feasible to connect medical equipment in order to monitor biomedical signals and also to detect illnesses in patients without human intervention. This new IoT and medical equipment connection is called IoMT. This IoMT model is most adapted to this pandemic since every human being has to be interconnected and monitored via a larger communication network. Hence, this article provides an overview of remote healthcare systems, monitoring ingestible sensors, mobile health, smart hospitals, and improved chronic disease management focused on t
... Show MoreIn this study, dark and various light qualities (white, red, green, and blue) were applied to evaluate their effects on growth characteristics, chemical content, and callus characteristics of Rosa damascene Mill. and Rosa hybirda L.
Explant (single-node and shoot tips) cultured on MS media supplemented with sucrose, agar, and plant growth regulators ( Kin 0.5 mg/l and IBA 1 mg/l for whole plant formation experiment or 1 mg/l kin with 0.5 mg/l IBA for callus experiment), incubated in a growth chamber.
The results of the whole plant formation experiment showed variation in growth characteristics in two types of Rosa, Green and white light caused the height ratio of shoot growth compared wi
... Show MoreSupport vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa
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