Oswald Biological Sciences Second Place: RNA Degradation is Elevated with Age-, but not Disuse-Associated Skeletal Muscle Atrophy

Aging and inactivity are both associated with decreased muscle size and protein content. The possible role of RNA degradation in the loss of protein has not yet been investigated. Therefore, we hypothesized that RNA degradation was elevated with muscle atrophy in aging and disuse. Brown Norway/Fisher344 male rats at 6 and 32 months were hindlimb suspended (HS) for 14 days to induce muscle atrophy or remained weight bearing (WB). Cytosolic extracts from gastrocnemius muscles were prepared for Western analysis of DCP-2 protein (marker of p-bodies) and RNA degradation assay. In vitro total RNA decay assay was performed using 30ug of total RNA (from tibialis anterior) incubated with 20ug of S15 extracts from gastrocnemius. RNA integrity was determined using the Agilent Technologies algorithm to calculate the RNA Integrity Number (RIN); decay rate and half-life were calculated for each sample. Results indicated an increase in DCP-2 protein at 32 months of age in both HS and WB groups. In addition, an almost 2-fold increase in decay rate and 48% decrease in half-life of total RNA was observed in muscle from 32 month old rats. However, no significant difference in decay rate and half-life was observed with disuse at either 6 or 32 months. We conclude that muscle atrophy associated with aging, but not disuse, may be due to a decrease in total RNA because of increased RNA degradation

System level airborne avionics prognostics for maintenance, repair and overhaul

The aim of this study is to propose an alternative approach in prognostics for airborne avionics system in order to enhance maintenance process and aircraft availability. The objectives are to analyse the dependency of avionic systems for fault propagation behaviour degradation, research and develop methods to predict the remaining useful life of avionics Line Replaceable Units (LRU), research and develop methods to evaluate and predict the degradation performances of avionic systems, and lastly to develop software simulation systems to evaluate methods developed. One of the many stakeholders in the aircraft lifecycle includes the Maintenance, Repair and Overhaul (MRO) industry. The predictable logistics process to some degree as an outcome of IVHM gives benefit to the MRO industry. In this thesis, a new integrated numerical methodology called ‘System Level Airborne Avionic Prognostics’ or SLAAP is developed; looking at a top level solution in prognostics. Overall, this research consists of two main elements. One is to thoroughly understand and analyse data that could be utilised. Secondly, is to apply the developed methodology using the enhanced prognostic methodology. Readily available fault tree data is used to analyse the dependencies of each component within the LRUs, and performance were simulated using the linear Markov Model to estimate the time to failure. A hybrid approach prognostics model is then integrated with the prognostics measures that include environmental factors that contribute to the failure of a system, such as temperature. This research attempts to use data that is closest to the data available in the maintenance repair and overhaul industry. Based on a case study on Enhanced Ground Proximity Warning System (EGPWS), the prognostics methodology developed showed a sufficiently close approximation to the Mean Time Before Failure (MTBF) data supplied by the Original Equipment Manufacturer (OEM). This validation gives confidence that the proposed methodology will achieve its objectives and it should be further developed for use in the systems design process

System level airborne avionics prognostics for maintenance, repair and overhaul

The aim of this study is to propose an alternative approach in prognostics for airborne avionics system in order to enhance maintenance process and aircraft availability. The objectives are to analyse the dependency of avionic systems for fault propagation behaviour degradation, research and develop methods to predict the remaining useful life of avionics Line Replaceable Units (LRU), research and develop methods to evaluate and predict the degradation performances of avionic systems, and lastly to develop software simulation systems to evaluate methods developed. One of the many stakeholders in the aircraft lifecycle includes the Maintenance, Repair and Overhaul (MRO) industry. The predictable logistics process to some degree as an outcome of IVHM gives benefit to the MRO industry. In this thesis, a new integrated numerical methodology called ‘System Level Airborne Avionic Prognostics’ or SLAAP is developed; looking at a top level solution in prognostics. Overall, this research consists of two main elements. One is to thoroughly understand and analyse data that could be utilised. Secondly, is to apply the developed methodology using the enhanced prognostic methodology. Readily available fault tree data is used to analyse the dependencies of each component within the LRUs, and performance were simulated using the linear Markov Model to estimate the time to failure. A hybrid approach prognostics model is then integrated with the prognostics measures that include environmental factors that contribute to the failure of a system, such as temperature. This research attempts to use data that is closest to the data available in the maintenance repair and overhaul industry. Based on a case study on Enhanced Ground Proximity Warning System (EGPWS), the prognostics methodology developed showed a sufficiently close approximation to the Mean Time Before Failure (MTBF) data supplied by the Original Equipment Manufacturer (OEM). This validation gives confidence that the proposed methodology will achieve its objectives and it should be further developed for use in the systems design process

Role of Mass Media as Changing Agent in Behavioral Change amid Coronavirus Crisis: A Study on Bangladesh Perspective

The Covid-19 pandemic has caused the biggest humanitarian crisis of the 21st century In an overpopulated country like Bangladesh it is even tougher to fight the situation The government and different stakeholders are relentlessly encouraging people to maintain the necessary health care measures where the mass media is playing the supporting role The research examines how mass media has been influencing in the behavioral change during this pandemic and played the role of changing agent The research is designed on mixed method including content analysis and survey This study analyses 191 health awareness-based news from three different print newspapers and two television channels prime hour bulletins within the timeline of 1st March to 31st March Also a survey questionnaire was set with close-ended questions to accumulate people s feedback Using the The Behaviorism Theory this study explains how all behaviors are acquired through conditioning Throughout this theoretical lens this research finds out how media worked as an external stimulus in changing people s behavior patter

Role of Pakistan poverty alleviation fund's micro credit in poverty alleviation: a case of Pakistan

Poverty alleviation has been one of the major agenda of all civilized societies throughout the history. Different strategies have been adopted in Pakistan for the purpose, which include special programs and short-term measures targeted towards improving the earning capacity of masses and provision of social safety nets for the really poor. With a view to enhance the access of the low-income communities to socio-economic services, the Government of Pakistan has set up an independent and professionally managed unit, the Pakistan Poverty Alleviation Fund (PPAF). The Fund is working through a network of partner organizations having strong community outreach programs. PPAF continuously monitors and analyzes effectiveness of its programs. This paper attempts to quantify the impact of PPAF micro credit on poverty alleviation.. Data collected in Gallup (2005) has been utilized for the purpose. Counter-factual ‘Combined approach’ has been employed in the analysis. The Paper concludes that Micro credit has reduced poverty by 3.05 percentage points in the period under stud

MOOCs without borders. Investigating the dynamics of a contextualised approach to scalable online learning, inclusion of displaced populations and conditions of poverty.

MOOCs, Massive Open Online Courses. This form of scalable education has gained a reputation for providing anytime, anywhere access to knowledge across the globe. Through the ubiquitous presence of the internet as the mechanism by which to deliver courses, MOOCs are primed to break down barriers of access to education between nations and population segments. However, is the ecosystem of MOOCs really developed for anyone, anywhere? With wars, national conflicts and natural disasters setting a record for the largest number of refugees and displaced populations ever recorded along with millions of people around the globe who continue to live in conditions of poverty, are indeed “MOOCs without borders” and can they provide much needed educational opportunities to transform the lives of these less privileged populations? This research investigates the plight for these populations by reflecting on the concept it has termed as “MOOCs without borders”. It examines the contexts of such populations and their nations which are heavily tasked to minimise gaps in the attainment of knowledge, through providing inclusive, adaptable and therefore contextualised education at scale. Reflecting on this, this thesis investigates the dynamics of contextualised education through the lens of MOOCs for such marginalised populations, and uses Knowledge Gap Theory as its theoretical framework whilst implementing Grounded Theory as its methodological approach. The findings gathered identifies 5 key factors which can contribute to the contextualisation of MOOCs for nations faced with poverty and the influx of displaced populations. In the identification of these 5 key factors, this thesis presents the generation of theory in the form of the “Contextualised MOOCs Model”. This model provides a how to framework for MOOCs to provide accessible educational opportunities, as it illustrates the interconnections and the impact which the 5 contextualised factors have upon each other, and thus upon the development and implementation of MOOCs for underprivileged and displaced populations

Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks

Histopathology tissue samples are widely available in two states: paraffin-embedded unstained and non-paraffin-embedded stained whole slide RGB images (WSRI). Hematoxylin and eosin stain (H&E) is one of the principal stains in histology but suffers from several shortcomings related to tissue preparation, staining protocols, slowness and human error. We report two novel approaches for training machine learning models for the computational H&E staining and destaining of prostate core biopsy RGB images. The staining model uses a conditional generative adversarial network that learns hierarchical non-linear mappings between whole slide RGB image (WSRI) pairs of prostate core biopsy before and after H&E staining. The trained staining model can then generate computationally H&E-stained prostate core WSRIs using previously unseen non-stained biopsy images as input. The destaining model, by learning mappings between an H&E stained WSRI and a non-stained WSRI of the same biopsy, can computationally destain previously unseen H&E-stained images. Structural and anatomical details of prostate tissue and colors, shapes, geometries, locations of nuclei, stroma, vessels, glands and other cellular components were generated by both models with structural similarity indices of 0.68 (staining) and 0.84 (destaining). The proposed staining and destaining models can engender computational H&E staining and destaining of WSRI biopsies without additional equipment and devices.Comment: Accepted for publication at 2018 IEEE International Conference on Machine Learning and Applications (ICMLA