We report herein an innovative approach to prostate tumor therapy using tumor specific radioactive gold nanoparticles (198Au) functionalized with Mangiferin (MGF). Production and full characterization of MGF-198AuNPs are described. In vivo therapeutic efficacy of MGF-198AuNPs, through intratumoral delivery, in SCID mice bearing prostate tumor xenografts are described. Singular doses of the nano-radiopharmaceutical (MGF-198AuNPs) resulted in over 85% reduction of tumor volume as compared to untreated control groups. The excellent anti-tumor efficacy of MGF-198AuNPs are attributed to the retention of over 90% of the injected dose within tumors for long periods of time. The retention of MGF-198AuNPs is also rationalized in terms of the higher

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

Millions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Due to a party's violation of his obligations or responsibilities indicated in the contract, many engineering projects confront extensive contractual disputes, which in turn need arbitration or other forms of dispute resolution, which negatively impact the project's outcome. Each contract has its terms for dispute resolution. Therefore, this paper aims to study the provisions for dispute resolution according to Iraqi (SBDW) and the JCT (SBC/Q2016) and also to show the extent of the difference between the two contracts in the application of these provisions. The methodology includes a detailed study of the dispute settlement provisions for both contracts with a comparative analysis to identify the differences in the appli