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SummaryBackground: Hypertension or high blood pressure is on the rise. Not only does it affect the elderly but is also increasingly spreading to younger sectors of the population. Treating this condition involves exhaustive monitoring of patients. The current mobile health services can be improved to perform this task more effectively. Objective: To develop a useful, user-friendly, robust and efficient app, to monitor hypertensive patients and adapted to the particular requirements of hypertension. Methods: This work presents BPcontrol, an Android and iOS app that allows hypertensive patients to communicate with their health-care centers, thus facilitating monitoring and diagnosis. Usability, robustness and efficiency factors for BPcontrol were evaluated for different devices and operating systems (Android, iOS and system-aware). Furthermore, its features were compared with other similar apps in the literature. Results: BPcontrol is robust and user-friendly. The respective start-up efficiency of the Android and iOS versions of BPcontrol were 2.4 and 8.8 times faster than a system-aware app. Similar values were obtained for the communication efficiency (7.25 and 11.75 times faster for the Android and iOS respectively). When comparing plotting performance, BPcontrol was on average 2.25 times faster in the Android case. Most of the apps in the literature have no communication with a server, thus making it impossible to compare their performance with BPcontrol. Conclusions: Its optimal design and the good behavior of its facilities make BPcontrol a very promising mobile app for monitoring hypertensive patients.

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PurposeWine has been produced for thousands of years and nowadays we have seen a spread in the wine culture. E-commerce sales of wine have increased considerably and online customer's satisfaction is influenced by quality and price. This paper presents a case study of the company “QuieroVinos, S.L.”, an online wine shop founded in 2015 that sells Spanish wines in two main marketplaces.Design/methodology/approachWith the final target of increasing the company profits it has been designed and developed an application to track the prices of competitors for a set of products. This information will be used to set the product prices in order to offer the products both competitively and profitably in each Marketplace. This application must check, by tacking into account information such as the product cost or the minimum product margin, if it is possible to decrease the price in order to reach the top cheapest position and as a consequence, increase the sales.FindingsThe application improved in a notorious way the company's results in terms of sales and shipping costs. It must be said that without the use of the presented application, performing the price comparison process within each one of the marketplaces would have taken a long time. Moreover, as prices change very frequently, the obtained information has a very limited time value, and the competitors prices should be analyzed daily in order to take accurate decisions regarding the company's price policy.Originality/valueAlthough the application has been designed for the wine sector and the two named marketplace, it could be exported to other sectors. For that, it should be implemented new modules to collect information regarding the competitor's price of the products selling on each corresponding marketplace.

Under many scenarios where resources may be scarce or a good Quality of Service is a requirement, appropriately sizing components and devices is one of the main challenges. New scenarios, such as IoT, mobile cloud computing, mobile edge computing or fog computing, have emerged recently. The ability to design, model and simulate those infrastructures is critical to dimension them correctly. Queuing theory models provide a good approach to understanding how a given architecture would behave for a given set of parameters, thus helping to detect possible bottlenecks and performance issues in advance. This work presents a fog-computing modelling framework based on queuing theory. The proposed framework was used to simulate a given scenario allowing the possibility of adjusting the system by means of user-defined parameters. The results show that the proposed model is a good tool for designing optimal fog architectures regarding QoS requirements. It can also be used to fine-tune the designs to detect possible bottlenecks or improve the performance parameters of the overall environment.

Background: Previous works have shown that risk factors for some kinds of cancer depend on people's lifestyle (e.g. rural or urban residence). This article looks into this, seeking relationships between cancer, age group, gender and population in the region of Lleida (Catalonia, Spain) using Multiple Correspondence Analysis (MCA). Methods: The dataset analysed was made up of 3,408 cancer episodes between 2012 and 2014, extracted from the Population-based Cancer Registry (PCR) for Lleida province. The cancers studied were colon and rectal (1,059 cases), lung (551 cases), urinary bladder (446 cases), prostate (609 cases) and breast (743 cases). The MCA technique was applied and used to search relationships among the main qualitative features. The basic statistics were the percentage explaining (variance), the inertia and the contribution of each qualitative variable. Results: General outcomes showed a low and moderate contribution of living in rural areas to colorectal and male prostate cancer. Males in urban areas were slightly and heavily affected by lung and urinary bladder cancer respectively. The analysis of each cancer provided additional information. Colorectal cancer greatly affected males aged <60, urban residents aged 70-79, and rural females aged ≥ 80. The impact of lung cancer was high among urban females <60, moderate among males aged 70-79 and high among rural females aged ≥ 80. The results for urinary bladder cancer results were similar to those for lung cancer. Prostate cancer affected both the <60 and ≥ 80 age groups significantly in rural areas. Breast cancer hit the 70-79 group significantly and, somewhat less so, rural females aged ≥ 80.Conclusions: MCA was a significant help for detecting the contributions of qualitative variables and the associations between them. MCA has proven to be an effective technique for analyzing the incidence of cancer. The outcomes obtained help to corroborate suspected trends, as well as detecting and stimulating new hypotheses about the risk factors associated with a specific area and cancer.