Response Detection of Castrate-Resistant Prostate Cancer to Clinically Utilised and Novel Treatments by Monitoring Phospholipid Metabolism

The authors gratefully acknowledge funding from Grampian NHS Endowment. The use of Professor Zanda’s and Jaspar’s NMR equipment and Russell Gray’s assistance are also gratefully acknowledged.Peer reviewedPublisher PD

ENHANCING EMAIL SPAM DETECTION THROUGH ENSEMBLE MACHINE LEARNING: A COMPREHENSIVE EVALUATION OF MODEL INTEGRATION AND PERFORMANCE

Email spam detection and filtering are crucial security measures in all organizations. It is applied to filter unsolicited messages; most of the time, they comprise a large portion of harmful messages. Machine learning algorithms, specifically classification algorithms, are used to filter and detect if the email is spam or not spam. These algorithms entail training models on labelled data to predict whether an email is spam or not based on its features. In particular, traditional classification machine learning algorithms have been applied for decades but proved ineffective against fast-evolving spam emails. In this research, ensemble techniques by using the meta-learning approach are introduced to reduce the problem of misclassification of spam email and increase the performance of the combined model. This approach is based on combining different classification models to enhance the performance of detecting the spam emails by aggregating different algorithms to reduce false positives and false negative rates, and increase the accuracy of the combined model. The paper proposed ensemble techniques where various machine-learning algorithms are combined to improve the accuracy and strength of spam detection systems. Using different algorithms, it tries to create an appropriate systematic behaviour to increase the detection rates and reduce the number of misclassification cases. In this research, four machine learning algorithms were selected to build the meta-learning model; these algorithms have been chosen based on their proven effectiveness in spam detection systems, such as Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbours (KNN). The selected algorithms were applied individually on different datasets. Subsequently, an ensemble model was created using the stacking method to collect all the predictions of the models then aggregate and use them as input features for the final classifier that is based on the Logistic Regression algorithm. This study demonstrates the effectiveness of an ensemble approach for email spam detection by aggregating multiple weak machine learning algorithms to produce a strong machine learning model. The purpose of this research is to enhance the accuracy and robustness of the predictive model to detect spam emails. As a result, the proposed approach produced a better performance with 95.8% accuracy

Economical and Reliable Expansion Alternative of Composite Power System under Restructuring

The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46-bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions

Employee Innovation in the Hospitality Industry: the Mediating Role of Psychological Safety

In the current turbulent and highly competitive environment, innovation can be considered a strategic weapon that enables hotels to survive, compete, and succeed. Innovation has been advocated to enhance hotels’ products, services, productions, processes, and overall performance. Innovation activities can take place as a result of employees’ behaviour, hence there is a call for greater attention to employees, in order to enhance hotel performance. Since innovation activities may involve uncertainty and risk, it is crucial to understand what makes employees feel safe, also referred to in literature as psychological safety, and encouraged to engage in the innovative behaviour. This conceptual paper presents an exploration of the factors that could encourage employee innovation in the hospitality industry. This relationship is supposedly mediated by psychological safety of the employees. The model propose seven essential elements that can promote innovative behaviour in the hospitality industry. Support and motivation from the management, high-quality relationships amongst members at work, autonomy, role expectation, and proactive personality, as an interpersonal trait, are all proposed to be positively associated with psychological safety and employee innovation, whereas openness to experiences and challenges at work are suggested to be positively associated only with employee innovation. Thus, understanding what promotes innovative behaviour will help hoteliers to cultivate and encourage the innovative behaviour amongst hotels’ employees, which can, in turn, enhance hotels’ services quality and performance

The validity and reliability of the exposure index as a metric for estimating the radiation dose to the patient

Introduction With the introduction of digital radiography, the feedback between image quality and over-exposure has been partly lost which in some cases has led to a steady increase in dose. Over the years the introduction of exposure index (EI) has been used to resolve this phenomenon referred to as ‘dose creep’. Even though EI is often vendor specific it is always a related of the radiation exposure to the detector. Due to the nature of this relationship EI can also be used as a patient dose indicator, however this is not widely investigated in literature. Methods A total of 420 dose-area-product (DAP) and EI measurements were taken whilst varying kVp, mAs and body habitus on two different anthropomorphic phantoms (pelvis and chest). Using linear regression, the correlation between EI and DAP were examined. Additionally, two separate region of interest (ROI) placements/per phantom where examined in order to research any effect on EI. Results When dividing the data into subsets, a strong correlation between EI and DAP was shown with all R-squared values > 0.987. Comparison between the ROI placements showed a significant difference between EIs for both placements. Conclusion This research shows a clear relationship between EI and radiation dose which is dependent on a wide variety of factors such as ROI placement, body habitus. In addition, pathology and manufacturer specific EI’s are likely to be of influence as well. Implications for practice The combination of DAP and EI might be used as a patient dose indicator. However, the influencing factors as mentioned in the conclusion should be considered and examined before implementation

Effects of body part thickness on low‐contrast detail detection and radiation dose during adult chest radiography

Introduction Differences in patient size often provide challenges for radiographers, particularly when choosing the optimum acquisition parameters to obtain radiographs with acceptable image quality (IQ) for diagnosis. This study aimed to assess the effect of body part thickness on IQ in terms of low‐contrast detail (LCD) detection and radiation dose when undertaking adult chest radiography (CXR). Methods This investigation made use of a contrast detail (CD) phantom. Polymethyl methacrylate (PMMA) was utilised to approximate varied body part thicknesses (9, 11, 15 and 17 cm) simulating underweight, standard, overweight and obese patients, respectively. Different tube potentials were tested against a fixed 180 cm source to image distance (SID) and automatic exposure control (AEC). IQ was analysed using bespoke software thus providing an image quality figure inverse (IQFinv) value which represents LCD detectability. Dose area product (DAP) was utilised to represent the radiation dose. Results IQFinv values decreased statistically (P = 0.0001) with increasing phantom size across all tube potentials studied. The highest IQFinv values were obtained at 80 kVp for all phantom thicknesses (2.29, 2.02, 1.8 and 1.65, respectively). Radiation dose increased statistically (P = 0.0001) again with increasing phantom thicknesses. Conclusion Our findings demonstrate that lower tube potentials provide the highest IQFinv scores for various body part thicknesses. This is not consistent with professional practice because radiographers frequently raise the tube potential with increased part thickness. Higher tube potentials did result in radiation dose reductions. Establishing a balance between dose and IQ, which must be acceptable for diagnosis, can prevent the patient from receiving unnecessary additional radiation dose

Defining criteria for disease activity states in systemic juvenile idiopathic arthritis based on the systemic Juvenile Arthritis Disease Activity Score

Objective To develop and validate cutoff values in the systemic Juvenile Arthritis Disease Activity Score 10 (sJADAS10) that distinguish the states of inactive disease (ID), minimal disease activity (MiDA), moderate disease activity (MoDA), and high disease activity (HDA) in children with systemic juvenile idiopathic arthritis (sJIA), based on subjective disease state assessment by the treating pediatric rheumatologist. Methods The cutoffs definition cohort was composed of 400 patients enrolled at 30 pediatric rheumatology centers in 11 countries. Using the subjective physician rating as an external criterion, 6 methods were applied to identify the cutoffs: mapping, calculation of percentiles of cumulative score distribution, Youden index, 90% specificity, maximum agreement, and ROC curve analysis. Sixty percent of the patients were assigned to the definition cohort and 40% to the validation cohort. Cutoff validation was conducted by assessing discriminative ability. Results The sJADAS10 cutoffs that separated ID from MiDA, MiDA from MoDA, and MoDA from HDA were ≤ 2.9, ≤ 10, and > 20.6. The cutoffs discriminated strongly among different levels of pain, between patients with or without morning stiffness, and between patients whose parents judged their disease status as remission or persistent activity/flare or were satisfied or not satisfied with current illness outcome. Conclusion The sJADAS cutoffs revealed good metrologic properties in both definition and validation cohorts, and are therefore suitable for use in clinical trials and routine practice

The steel–concrete interface

Although the steel–concrete interface (SCI) is widely recognized to influence the durability of reinforced concrete, a systematic overview and detailed documentation of the various aspects of the SCI are lacking. In this paper, we compiled a comprehensive list of possible local characteristics at the SCI and reviewed available information regarding their properties as well as their occurrence in engineering structures and in the laboratory. Given the complexity of the SCI, we suggested a systematic approach to describe it in terms of local characteristics and their physical and chemical properties. It was found that the SCI exhibits significant spatial inhomogeneity along and around as well as perpendicular to the reinforcing steel. The SCI can differ strongly between different engineering structures and also between different members within a structure; particular differences are expected between structures built before and after the 1970/1980s. A single SCI representing all on-site conditions does not exist. Additionally, SCIs in common laboratory-made specimens exhibit significant differences compared to engineering structures. Thus, results from laboratory studies and from practical experience should be applied to engineering structures with caution. Finally, recommendations for further research are made

Transitioning from recruit to officer : An investigation of how stress appraisal, and coping influence engagement

This study investigated stress, coping, and work engagement among Portuguese police officers while undergoing academy training and then 1 year later, when on duty. It was hypothesized that stress appraisal and coping preferences predicted engagement. Additionally, in order to test a full cross‐lagged prediction model, it was hypothesized that stress, coping, and engagement in recruits predicted these variables later when working as police officers. Structural equation modeling was used to test the research hypotheses. Results suggest that coping and stress appraisals do not seem to be strong predictors of work engagement among recruits and police officers on duty. With the exception of self‐blame, that seems to be a strong predictor of work engagement among police officers on duty. These results highlight the need to investigate other potential variables such as working conditions that may better explain work engagement. Considering the positive influence of engagement on health, wellbeing, and performance of police recruits and officers future applied and theoretical implications are discussed.Fundação para a Ciência e a Tecnologia - FCT; FEDERinfo:eu-repo/semantics/acceptedVersio