Differences in the Psychological Profiles of Elite and Non-elite Athletes

One of the main goals of sport psychology is to identify those psychological factors that are relevant for sport performance as well as possibilities of their development. The aim of the study was to determine whether the set of specific psychological characteristics [generalized self-efficacy, time perspective, emotional intelligence (EI), general achievement motivation, and personality dimensions] makes the distinction between athletes based on their (non)-participation in the senior national team, that is, their belonging to the subsample of elite or non-elite athletes depending on this criterion. According to the group centroids it can be said that elite athletes are characterized by a positive high score in self-efficacy, emotionality, present fatalistic time perspective, past positive time perspective, and openness to experience. They are also characterized by low past negative time perspective, emotional competence, and future time perspective. Non-elite athletes have the opposite traits. The results have been discussed in the context of their application in the process of talent selection and development in sport as well as the development of life skills in athletes

Ongoing strategies to improve the management of upper respiratory tract infections and reduce inappropriate antibiotic use particularly among lower and middle-income countries: findings and implications for the future

Introduction: Antibiotics are indispensable to maintaining human health; however, their overuse has resulted in resistant organisms, increasing morbidity, mortality and costs. Increasing antimicrobial resistance (AMR) is a major public health threat, resulting in multiple campaigns across countries to improve appropriate antimicrobial use. This includes addressing the overuse of antimicrobials for self-limiting infections, such as upper respiratory tract infections (URTIs), particularly in lower- and middle-income countries (LMICs) where there is the greatest inappropriate use and where antibiotic utilization has increased the most in recent years. Consequently, there is a need to document current practices and successful initiatives in LMICs to improve future antimicrobial use. Methodology: Documentation of current epidemiology and management of URTIs, particularly in LMICs, as well as campaigns to improve future antimicrobial use and their influence where known. Results: Much concern remains regarding the prescribing and dispensing of antibiotics for URTIs among LMICs. This includes considerable self-purchasing, up to 100% of pharmacies in some LMICs. However, multiple activities are now ongoing to improve future use. These incorporate educational initiatives among all key stakeholder groups, as well as legislation and other activities to reduce self-purchasing as part of National Action Plans (NAPs). Further activities are still needed however. These include increased physician and pharmacist education, starting in medical and pharmacy schools; greater monitoring of prescribing and dispensing practices, including the development of pertinent quality indicators; and targeted patient information and health education campaigns. It is recognized that such activities are more challenging in LMICs given more limited resources and a lack of healthcare professionals. Conclusion: Initiatives will grow across LMICs to reduce inappropriate prescribing and dispensing of antimicrobials for URTIs as part of NAPs and other activities, and these will be monitored

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate

Real-time context-aware network security policy enforcement system (RC-NSPES)

The major technical objectives of the RC-NSPES are to provide a framework for the concurrent operation of reactive and pro-active security functions to deliver efficient and optimised intrusion detection schemes as well as enhanced and highly correlated rule sets for more effective alerts management and root-cause analysis. The design and implementation of the RC-NSPES solution includes a number of innovative features in terms of real-time programmable embedded hardware (FPGA) deployment as well as in the integrated management station. These have been devised so as to deliver enhanced detection of attacks and contextualised alerts against threats that can arise from both the network layer and the application layer protocols. The resulting architecture represents an efficient and effective framework for the future deployment of network security systems