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Objective. We aimed to assess the quality of life (QoL) and its predictors in colorectal cancer (CRC) patients at King Abdulaziz Medical City, Jeddah. Methods. A total of 118 CRC patients at King Abdulaziz Medical City, a tertiary hospital in Jeddah, participated in this study. The participants were provided with the online questionnaire via WhatsApp by trained researchers and data collectors in February 2021. All participants were required to answer the three-section questionnaire comprising of (a) demographic data and a validated Arabic version of the European Organization for Research and Treatment of Cancer (EORTC) quality of life questionnaires, (b) a general version (QLQ-30), and (c) a CRC-specific version (QLQ-CR29). Results. Statistical analysis revealed that the most common comorbidity among the participants was diabetes mellitus (42.4%). In addition, the mean global health status was 63.91 ± 24.75. For the global health tool QLQ-C30, results exhibited that physical functioning [62.94 (30.04)] and social functioning [63.56 (31.95)] scored below the threshold, while the cognitive functioning scale scored the highest [74.86 (25.11)]. In addition, on the QLQ-C30 scales, fatigue and insomnia were distressing, with fatigue scoring the highest. For the disease-specific tool QLQ-CR29, it was found that for the symptom scale, urinary frequency and embarrassment scored the highest. Conclusion. The participants reported high global quality of life on both the EORTC QLQ-30 and QLQ-CR29 scales. This study identifies the factors and predictors that affect the quality of life of CRC patients in Saudi Arabia. Recognizing these factors and predictors may empower those patients to maintain positive perception towards the impact of colorectal cancer and improve their survival.

Exploratory data analysis (EDA) a vital role in the interpretation of the contents behind the data and offers descriptive and inferential analysis for data. The data mining technique helps to identify the topics contained in the text corpus. In the present study, we manipulated the Yelp dataset and have applied visual analysis to determine the significant features and key characteristics of the data. We also analyzed temporal and spatial data for a restaurant as a case study. Moreover, we applied the Term Frequency method (Bag-of-Words) on reviews given by the users to get frequent words and phrases in each review class, whether positive, negative, or neutral. Finally, we were able to identify some relationships between the restaurant and the results of the rating system, as well as extract the most important topics that we expect to have the highest impact on the customer's experience.

Thermal infrared cameras provide unique information on surface temperature that can benefit a range of environmental, industrial and agricultural applications. However, the use of uncooled thermal cameras for field and unmanned aerial vehicle (UAV) based data collection is often hampered by vignette effects, sensor drift, ambient temperature influences and measurement bias. Here, we develop and apply an ambient temperature-dependent radiometric calibration function that is evaluated against three thermal infrared sensors (Apogee SI-11(Apogee Electronics, Santa Monica, CA, USA), FLIR A655sc (FLIR Systems, Wilsonville, OR, USA), TeAx 640 (TeAx Technology, Wilnsdorf, Germany)). Upon calibration, all systems demonstrated significant improvement in measured surface temperatures when compared against a temperature modulated black body target. The laboratory calibration process used a series of calibrated resistance temperature detectors to measure the temperature of a black body at different ambient temperatures to derive calibration equations for the thermal data acquired by the three sensors. As a point-collecting device, the Apogee sensor was corrected for sensor bias and ambient temperature influences. For the 2D thermal cameras, each pixel was calibrated independently, with results showing that measurement bias and vignette effects were greatly reduced for the FLIR A655sc (from a root mean squared error (RMSE) of 6.219 to 0.815 degrees Celsius (℃)) and TeAx 640 (from an RMSE of 3.438 to 1.013 ℃) cameras. This relatively straightforward approach for the radiometric calibration of infrared thermal sensors can enable more accurate surface temperature retrievals to support field and UAV-based data collection efforts.

Background: Nutritional anemia or anemia due to dietary causes is the most common form, yet the easiest to manage compared to other forms of anemia. Some of the most common nutritional deficiencies are iron, cobalamin, folate, and also other elements like copper. Anemia due to diet is mostly asymptomatic in the initial phase until the stores are depleted, which can take a few months to several years, depending upon the cause. Methodology: We conducted this review using a comprehensive search of MEDLINE, PubMed, and EMBASE from January 1987 to March 2017. The following search terms were used: nutritional anemia, dietary anemia, iron deficiency anemia, cobalamin deficiency, folic acid deficiency anemia, dietary anemia treatment Aim of the work: In this study we aimed to understand about the different types of anemia caused as a result of dietary deficiency. We will also briefly study about their presentation, pathophysiology, and treatment. Conclusion: Various causes, presentations, and complications are associated with different types of nutritional anemia, but they still are the easiest to treat and manage. Most cases are due to an underlying occult disorder rather than simple dietary insufficiency, making diagnosis more difficult in some cases, and requiring thorough history and investigations integration to reach an accurate diagnosis and treat the underlying cause.