1,004 research outputs found
Incidence rate of non-Hodgkin's lymphomas among males in Saudi Arabia: an observational descriptive epidemiological analysis of data from the Saudi cancer registry, 2001-2008
Background: This study describes epidemiological data of non-Hodgkin's lymphoma (NHL) diagnosed from 2001 to 2008 among Saudi men. Materials and methods: Retrospective data from all NHL cancer cases among Saudi men recorded in the Saudi Cancer Registry (SCR) between January 2001 and December 2008 were used. Descriptive statistics, analysis of variance, Poisson regression, and simple linear regression were also used. Results: In total, 2,555 new cases of NHL were recorded between January 2001 and December 2008. The region of Riyadh, Saudi Arabia had the highest overall age-standardized incidence rate (ASIR) at 7.8, followed by the Eastern region at 6.8, and Makkah at 6.1 per 100,000 men; however, Jazan, Hail, and Baha had the lowest average ASIRs at 2.5, 3.7, and 3.9 per 100,000 men, respectively. The incidence-rate ratio for the number of NHL cases was significantly higher in Riyadh (4.68, 95 confidence interval CI 4.11-5.32), followed by Makkah (4.47, 95% CI 3.94-5.07), and the Eastern region of Saudi Arabia (3.27, 95% CI 2.90-3.69) than that in the reference region of Jazan. Jouf had the highest changes in the ASIRs of NHL among Saudi men from 2001 and 2008 (5.0 per 100,000 men). Conclusion: A significant increase in the crude incidence rate and ASIR for NHL in Saudi Arabia between 2001 and 2008 was found. Riyadh, the Eastern region, and Makkah had the highest overall ASIR in Saudi Arabia. Jazan, Hail, and Baha had the lowest rates. Additionally, Riyadh, Makkah, and the Eastern region had the highest incidence-rate ratio for the number of NHL cases. Finally, Jouf had the highest changes in crude incidence rate and ASIR from 2001 to 2008. Further analytical studies are needed to determine the potential risk factors of NHL among Saudi men. © 2014 Alghamidi et al
Mechanical and Microstructure Characteristics of Concrete-Mixtures Designed for Durability of RC-Structures in Corrosive Environment
As exposures to chloride-salts are known as prime factors causing initiation and continuity of corrosion-process of steel reinforcement bars in reinforced concrete (RC) structures, it has always been a major concern for designers considering the requirements of structural-durability for targeted-service life of RC-structures in aggressively corrosive environments typically prevalent in coastal regions. Research works previously reported by the researchers have modeled corrosion-process in terms of corrosion-current density, and it was realized that concrete-mixtures design quality and characteristics, degree of exposures to corrosive-agents such as chloride salts, and protective-concrete cover-thickness are now known beyond doubt to be determinant factors as regards RC-structures durability. This research paper is focused on presenting highlights of an extensive experimental investigation carried out on a large number of concrete specimens that were designed, and placed in chloride-salt solution simulating exposure to corrosion-conditions. Results presented in this paper include close-looks at mechanical and micro-structure characteristics with regard to the influence of key design-parameters and exposure-conditions used for test-specimens with various combinations of cementitious materials constituents and proportioning using three replicate-combinations of water-cementitious ratios, fine to total aggregate ratio, and concrete-cover thickness, and with different concentrations of chloride-solution. Statistical analysis of results obtained from a three-year test-program is outlined in terms of one unifying corrosion-process progress indicator, namely, corrosion-current density Icorr, determined by both electrochemicalmethod and gravimetric weight-loss method. The paper presents a general overview of the test program and a summary of sample results on mechanical, strength, and microstructural characteristics obtained from test specimens
Stimulatory Effects of Lycium shawii on Human Melanocyte Proliferation, Migration, and Melanogenesis: In Vitro and In Silico Studies
There is no first-line treatment for vitiligo, a skin disease characterized by a lack of melanin produced by the melanocytes, resulting in an urgent demand for new therapeutic drugs capable of stimulating melanocyte functions, including melanogenesis. In this study, traditional medicinal plant extracts were tested for cultured human melanocyte proliferation, migration, and melanogenesis using MTT, scratch wound-healing assays, transmission electron microscopy, immunofluorescence staining, and Western blot technology. Of the methanolic extracts, Lycium shawii L. (L. shawii) extract increased melanocyte proliferation at low concentrations and modulated melanocyte migration. At the lowest tested concentration (i.e., 7.8 ÎĽg/mL), the L. shawii methanolic extract promoted melanosome formation, maturation, and enhanced melanin production, which was associated with the upregulation of microphthalmia-associated transcription factor (MITF), tyrosinase, tyrosinase-related protein (TRP)-1 and TRP-2 melanogenesis-related proteins, and melanogenesis-related proteins. After the chemical analysis and L. shawii extract-derived metabolite identification, the in silico studies revealed the molecular interactions between Metabolite 5, identified as apigenin (4,5,6-trihydroxyflavone), and the copper active site of tyrosinase, predicting enhanced tyrosinase activity and subsequent melanin formation. In conclusion, L. shawii methanolic extract stimulates melanocyte functions, including melanin production, and its derivative Metabolite 5 enhances tyrosinase activity, suggesting further investigation of the L. shawii extract-derived Metabolite 5 as a potential natural drug for vitiligo treatment
Blockchain Empowered Federated Learning Ecosystem for Securing Consumer IoT Features Analysis
Resource constraint Consumer Internet of Things (CIoT) is controlled through gateway devices (e.g., smartphones, computers, etc.) that are connected to Mobile Edge Computing (MEC) servers or cloud regulated by a third party. Recently Machine Learning (ML) has been widely used in automation, consumer behavior analysis, device quality upgradation, etc. Typical ML predicts by analyzing customers’ raw data in a centralized system which raises the security and privacy issues such as data leakage, privacy violation, single point of failure, etc. To overcome the problems, Federated Learning (FL) developed an initial solution to ensure services without sharing personal data. In FL, a centralized aggregator collaborates and makes an average for a global model used for the next round of training. However, the centralized aggregator raised the same issues, such as a single point of control leaking the updated model and interrupting the entire process. Additionally, research claims data can be retrieved from model parameters. Beyond that, since the Gateway (GW) device has full access to the raw data, it can also threaten the entire ecosystem. This research contributes a blockchain-controlled, edge intelligence federated learning framework for a distributed learning platform for CIoT. The federated learning platform allows collaborative learning with users’ shared data, and the blockchain network replaces the centralized aggregator and ensures secure participation of gateway devices in the ecosystem. Furthermore, blockchain is trustless, immutable, and anonymous, encouraging CIoT end users to participate. We evaluated the framework and federated learning outcomes using the well-known Stanford Cars dataset. Experimental results prove the effectiveness of the proposed framework
Smoking cessation during COVID-19: the top to-do list
As evidence continues to emerge, our understanding of the relationship between smoking and COVID-19 prognosis is steadily growing. An early outlook from World Health Organisation (WHO) indicates that smokers are more vulnerable to severe COVID-19 disease and are also more likely to be infected, as frequent motions from hand to mouth and sharing of tobacco products such as waterpipes increased the possibility of being infected. In this commentary, we discuss some of the latest evidence on smoking and COVID-19 and emphasise the need to promote the personal and public advantages of smoking cessation during the COVID-19 pandemic
The Need for Emergency Management Models
Emergency agencies can use emergency management models to enable them to better prepare for and respond to emergencies. This qualitative study aims to undertake a critical examination of emergency management models by thematic analysis to determine their significance to emergency management. A review and analysis of the existing literature were used in the study. The models were studied to explore their role in emergency management and to identify any significant constraints or challenges which could limit the ability of the emergency management model to carry out appropriate actions. The study found that such models are indispensable because they simplify and improve emergency management. Additionally, they may support planners, managers, and practitioners in reaching proper decisions, making them a valuable and necessary decision-making support tool. The study also showed that each model has an advantage that distinguishes it from the other models. Consequently, a comprehensive emergency management model should be designed to suit all cases and circumstances. The findings also confirmed the doubts raised about the limitations and concerns associated with the models. Concerns included future events’ unpredictability, the models’ prescriptive nature, the event’s cultural context, and the impact on businesses. The findings also indicated that certain planners, managers, and practitioners had a limited understanding of the use of models in emergency management. As such, they appear to have overlooked the use of models while dealing with emergencies. Hence, the study recommends that the models should be employed in all emergency management activities. The study also recommends that the findings are utilized as a basis for further research into the potential use of emergency management models
Key toolkits of non-pharmacological management in COPD: during and beyond COVID-19
Individuals with COPD are at higher risk of severe disease and mortality if they contract COVID-19. Shielding and social distancing have negatively impacted the delivery of routine care for COPD patients, which should be maintained to avoid further deterioration. We aimed to review the literature about the key toolkits of non-pharmacological treatments of COPD patients before and during the COVID-19 pandemic. In particular, we focused on smoking cessation, pulmonary rehabilitation, and telehealth delivery approaches during the COVID-19 crisis. Smoking cessation services are important to mitigate the spread of the virus, especially in people with chronic lung disease; the pandemic, in one way or another, has helped to enhance people's motivation to quit smoking. Also, tele-rehabilitation is considered as effective as conventional pulmonary rehabilitation in controlling symptoms of disease, promoting physical activity, and enhancing self-management of COPD. Telerehabilitation offers flexibility and it could be the dominant mode for providing a pulmonary rehabilitation programme. Finally, the use of telehealth (TH) modes has trended during the pandemic. Consensus about the effectiveness of TH in reducing exacerbation events is still inconclusive. In the context of COPD, further clinical research must concentrate on understanding attitudes, behaviours, and motivations towards smoking cessation. Further recommendations include gauging the feasibility of a long-term tele-rehabilitation programme in large COPD populations, designing more COPD-related mobile apps, and evaluating the feasibility of tele-rehabilitation in clinical practice
GEANT4 Simulation for Radioactive Particle Tracking (RPT) Technique
In the past two decades, the radioactive particle tracking (RPT) measurement technique has been proven to visualize flow fields of most multiphase flow systems of industrial interest. The accuracy of RPT, and hence the data obtained, depend largely on the calibration process, which stands here as a basis for two subsequent processes: tracking and reconstruction. However, limitations in the RPT calibration process can be found in different experimental constrains and in assumptions made in the classical Monte Carlo approach used to simulate number of counts received by the detectors. Therefore, in this work, we applied a GEANT4-based Monte Carlo code to simulate the RPT calibration process for an investigated multiphase flow system (i.e., gas–liquid bubble column). The GEANT4 code was performed to simulate the number of counts received by 28 scintillation detectors for 931 known tracer positions while capturing all the types of photon interaction and overcoming solids\u27 angle limitations in classical approaches. The results of the simulation were validated against experimental data obtained using an automated RPT calibration device. The results showed a good agreement between the simulated and experimental counts, where the maximum absolute average relative deviation detected was about 5%. The GEANT4 model typically predicted the number of counts received by all the detectors; however, it over-estimated the counts when the number of primary events applied in the model was not the optimal
Active Expert Learning for the Digital Humanities
Current platforms for paper sharing among scholars, such as Research Gate, could support Active Expert Learning, whereby the paper being uploaded is processed using human language technology techniques, and feedback is asked of the scholar doing the upload using active learning techniques to minimize the amount of feedback requested. We show that this approach could outperform traditional active learning as well as randomly asking for feedback
- …