Colorectal cancer (CRC), the second most fatal cancer and the 3rd most common cancer is expected to cause 0.9 million deaths globally in 2025. Carcinoembryonic antigen (CEA) is currently used in the follow-up of patients with colorectal cancer, and in this study, we are trying to find a better marker than CEA in following up on patients' health and knowing the effectiveness of the treatment used and as a diagnostic marker for colorectal cancer. To determine the significance of Cancer antigen 72-4 (CA72-4) as a prognosis predictor in patients with colorectal cancer, compare its prognostic validity to the CEA biomarker. this case-control study includes (150) participants, 100 patients (59 males and 41 females), and 50 healthy controls

The current study presents an experimental investigation of heat transfer and flow characteristic for subcooled flow boiling of deionized water in the microchannel heat sink. The test section consisted of a single microchannel having 300μm wide nominal dimensions and 300μm height (hydraulic diameter of 300μm). The test section formed of oxygen-free copper with 72mm length and 12mm width. Experimental operation conditions spanned the heat flux (78-800) kW/m², mass flux (1700 and 2100) kg/m².s at 31˚C subcooled inlet temperature. The boiling heat transfer coefficient is measured and compared with existing correlations. Also, the experimental pressure drop is measured and compared with microscale p

In this paper the experimentally obtained conditions for the fusion splicing with photonic crystal fibers (PCF) having large mode areas were reported. The physical mechanism of the splice loss and the microhole collapse property of photonic crystal fiber (PCF) were studied. By controlling the arc-power and the arc-time of a conventional electric arc fusion splicer (FSM-60S), the minimum loss of splicing for fusion two conventional single mode fibers (SMF-28) was (0.00dB), which has similar mode field diameter. For splicing PCF (LMA-10) with a conventional single mode fiber (SMF-28), the loss was increased due to the mode field mismatch.

     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

Mass transfer correlations for iron rotating cylinder electrode in chloride/sulphate solution, under isothermal and
controlled heat transfer conditions, were derived. Limiting current density values for the oxygen reduction reaction from
potentiostatic experiments at different bulk temperatures and various turbulent flow rates, under isothermal and heat
transfer conditions, were used for such derivation. The corelations were analogous to that obtained by Eisenberg et all
and other workers.

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai