Identification of Optimal Frequencies to Determine Alpha-Cypermethrin using Machine Learning Feature Selection Techniques

Machine learning feature space reduction techniques allow for vast feature spaces to be reduced with little loss or even significant improvements in the reliability of predictions of models. Microwave spectroscopy with feature spaces of over 8000 are not uncommon when considering magnitude and phase. Applying Machine learning techniques to this type of feature space allows for a quicker reduction and helps to identify the most suitable predictive features. The control of insect vectors that transmit diseases including malaria, visceral leishmaniasis and zika rely on the use of insecticide. These diseases affect millions, malaria alone accounted for 214 million new cases resulting in 438, 000 deaths in 2015. One method used in controlling the vectors is through indoor residual spraying, applying insecticide to the wall surface inside houses. Alpha-cypermethrin is one of the insecticides that is currently sprayed in several countries for vector control. Quality assurance and monitoring of the control activities is challenging relying on the use of laboratory-reared insects. This was improved with a chemical based Insecticide Quantification Kit, but these assays have been challenging to operationalise. An electromagnetic sensor is being developed to investigate the potential to detect alpha-cypermethrin. Preliminary experiments were carried out to differentiate tiles sprayed with Technical Grade alpha-cypermethrin, wettable powder containing 5% alpha-cypermethrin and wettable powder with over dose of alpha-cypermethrin using a horn antenna at a frequency range between 1 GHz to 6 GHz. The experimental results indicated the potential use of electromagnetic waves to determine alpha-cypermethrin in a non-destructive manner

Recent Advances in the Understanding of Molecular Mechanisms of Resistance in Noctuid Pests

This book brings together the papers published in the Special Issue "Recent advances in the understanding of molecular mechanisms of resistance in Noctuid pests" in the journal Insects in 2021. It contains 10 articles that are either original results or reviews. The focus is on insects of the noctuid family, as they are among the most devastating crop pests on the planet. Understanding the molecular mechanisms that allow these insects to become resistant to insecticides is essential for the implementation of sustainable control methods and resistance management strategies

Translational Biomarker Research for Militarily Relevant Populations in Neurocognitive Diseases

In recent decades more soldiers are being mobilized to conflict areas, such as the over 2 million service members, who have been deployed to Iraq and Afghanistan since October 2001, which includes but is not limited to Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF); or the 700,000 service veterans deployed to the Persian Gulf War in 1990-91 in the US. The UK mobilized over 46,000 military personnel to Iraq, 9,500 British troops to Afghanistan and 50,000 troops to the Gulf War. Soldiers are being exposed to traumatic events such as physical and psychological trauma, as well as chemical exposure and therefore service members are at risk of postdeployment health-related issues, associated commonly with post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) among OEF/OIF veterans, as well as Gulf War Illness (GWI) among the Persian Gulf War Veteran population. Although progress has been made in identifying underlying pathology for TBI and PTSD and acute as well as sub-acute biomarkers have been identified, with commercially available tests on the horizon, the work presented here addresses a critical but underinvestigated issue, the need for chronic biomarkers for these conditions, as they can go undetected for an extended period of time. Additionally, more evidence has surfaced that discusses how symptoms related to mild TBI (mTBI) can last for years after the insult, emphasizing the importance of investigatjng biomarkers at a late timepoint after injury as, owing to the mild nature of the injury, the condition was often undiagnosed at the time. PTSD itself still lacks an objective measure that can capture its complexity, whereas co-morbidity of PTSD with TBI further complicates the issue. The other mentioned militarily relevant condition, termed GWI, faces similar issues. Veterans deployed to the Persian Gulf War in 1991 suffer from a disease that has shown to exhibit persistent multisymptom complexity. No biomarker has been identified for this particular population thus making objective diagnosis difficult. Besides the identification of clinical biomarkers, much research has been done in preclinical models, yet there is still a need to verify and validate such animal models in order to demonstrate their utility. Once the validity of a preclinical model has been confirmed, investigation of pathogenic mechanisms in those models has the potential to reveal therapeutic targets of relevance to the human condition. Chapter 1 will discuss epidemiology, current clinical diagnosis and pathophysiology of TBI, PTSD and GWI as well as the status of biomarker research in each of these three areas. The thesis then focuses on the identification of plasma biomarkers in human patient populations, specifically in military populations suffering from TBI, PTSD or both at chronic time points post traumatic exposure (Chapters 2 & 3). In Chapter 4, we then explore whether or not such changes are present in our established animal model of TBI. In Chapter 5 we investigate peripheral biomarkers in plasma samples from Gulf War veterans and in two animal models of GWI. Given the complexity of TBI, PTSD and GWI clinical presentation and pathogenesis and their heterogeneity in human populations, it is anticipated that a valid biomarker for broad application will in fact require assessment of many markers to create a panel that can support diagnosis. The lipidomic and proteomic analyses I employed in this work are approaches with the required breadth and lack of bias to be successful in such an undertaking, and I hope that the work described in this thesis provides a foundation for future development of such biomarker panels

The Effect of Emotional Intelligence Training via Method Psychodrama on Marital Satisfaction of Patients with MS

MS is a progressive and chronic disease of the central nervous system with symptoms that can be debilitating. Appropriate interventions including Emotional Intelligence Training improve the quality of life MS patients. The aim of this study is to determine the effect of emotional intelligence training through Psycho-Drama methods on marital satisfaction of patients with MS. This study is a one-group, before-after, quasi-experimental study. A total of 22 patients were enrolled in this study. The samples were selected through non-random sampling based on the goal of study among visitors of MS Society, Kurdistan province, Iran. Data collection tool was questionnaires with two sections: 1) demographic information and 2) ENRICH-B marital satisfaction questionnaire including 47 items. Intervention was conducting 20 sessions of 2-hour training. Questionnaires were filled by patients before and after intervention. Methods for data analysis were descriptive statistics (tables of relative frequency distribution, the mean, and standard deviation) and inferential statistics of paired t test. Paired t test showed a significant difference in total scores of marital satisfaction before and after training sessions (P < 0.05). Finally, we concluded that, designing and applying emotional intelligence training programs via psychodrama method is effective on marital satisfaction in patients with multiple sclerosis. Keywords: Multiple sclerosis, emotional intelligence training, psychodrama, marital satisfactio