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Revolutionising financial portfolio management: the non-stationary transformer's fusion of macroeconomic indicators and sentiment analysis in a deep reinforcement learning framework
Get PDFIn the evolving landscape of portfolio management (PM), the fusion of advanced machine learning techniques with traditional financial methodologies has opened new avenues for innovation. Our study introduces a cutting-edge model combining deep reinforcement learning (DRL) with a non-stationary transformer architecture. This model is designed to decode complex patterns in financial time-series data, enhancing portfolio management strategies with deeper insights and robustness. It effectively tackles the challenges of data heterogeneity and market uncertainty, key obstacles in PM. Our approach integrates key macroeconomic indicators and targeted news sentiment analysis into its framework, capturing a comprehensive picture of market dynamics. This amalgamation of varied data types addresses the multifaceted nature of financial markets, enhancing the model’s ability to navigate the complexities of asset management. Rigorous testing demonstrates the model’s efficacy, highlighting the benefits of blending diverse data sources and sophisticated algorithmic approaches in mastering the nuances of PM
Our Voices University Network: a briefing on our PhD student forum
Get PDFThe Our Voices University Network (OVUN) formed one half of ‘Our Voices III’, a project coordinated by the Safer Young Lives Research Centre at the University of Bedfordshire. The OVUN was established to facilitate links between academics around the world in order to develop and share knowledge about the prevention of and response to child sexual abuse and exploitation. It was recognised that those undertaking doctorate studies related to the area of child sexual abuse and exploitation hold a wealth of knowledge on this topic. One strand of the OVUN therefore focussed on creating a space where doctoral students could come together to share knowledge and understanding. This briefing shares learning from the PhD student forum sessions that were held over the course of the project. Here, we reflect on what forum members have shared about: • the tensions and challenges of doing doctoral research on child sexual abuse and exploitation (or related topics/other forms of harm) • what they have valued about the forum • what support needs they have which are not being met It is hoped that the learning captured in this briefing will be of use to other PhD researchers and supervisors who are undertaking or supporting work in this field
The impact of ownership structure and investment decisions on capital structure: an empirical study from Jordan
No full textOrchestration of network applications using middleware for 5G enhanced autonomous robots
No full textA study of Fante-speaking students' learning of academic writing at the Methodist University College, Ghana (MUCG)
No full textRiver Project, an innovative way to reduce pollution on riverboats
Get PDFConsidering the EU environmental standards for non-road mobile machinery (NRMM), reducing pollutant emissions from inland waterway vessels is becoming increasingly important. The RIVER research project aims to find solutions to achieve nitrogen-free combustion in waterways transportation systems while also emitting zero CO2 emission. RIVER addresses these issues using Carbon Capture and Storage (CCS) technology and Oxy-fuel combustion (OFC). The project is co-financed by the European Union, as part of the Interreg North-West Europe program. There are ten partners involved in this project (FR, UK, GE, NL, LU). In OFC technology, pure oxygen is used instead of air. Due to the absence of N2 in the intake charge, NOx emissions will be eliminated. Consequently, the only products of combustion are CO2 and water vapor. To have a stable combustion process and avoid overheating problems caused by using pure oxygen, some part of the exhaust CO2 will be recirculated to the engine to create an oxygen-CO2 mixture for being fed into the engine. A detailed CFD simulation carried out in this project has revealed that 21% oxygen and 79% carbon dioxide is the ideal mixture for the engine to run at maximum efficiency. The remaining CO2 from the exhaust is collected. It is then condensed, compressed, and stored in a tank to be valorized later. It will be transformed into cosmetics, skincare products, and formic acid. These types of acids are used by the medical sector as an anti-rheumatic product. River's final demonstration will take place in Crewe, UK in July 2022
Getting connected: establishing direct communication between learning developers and PhD Students with teaching responsibilities
Get PDFMany PhD researchers have the opportunity to take up teaching responsibilities during their doctoral studies to enhance their employability and interest in academia. Aside from their formal teaching training, little is known about the types of resources and support from professional services that PhD students (PhDs) use to fulfil their teaching responsibilities. On the other hand, learning development is a relatively new profession within higher education. As such, there are varied perceptions on the necessity for PhDs with teaching responsibilities to engage with learning development support. This opinion piece shares the experience of a STEM UK PhD student with teaching responsibilities and a learning development practitioner when establishing support for modules taught by PhDs. Through a dialogue, the authors explore the challenges faced in the interaction between learning developers (LDs) and PhDs, in two different UK universities, and recommend how to further develop the relationship. Through this dialogue possible solutions like increasing the visibility of available LD support for PhDs with teaching responsibilities within higher education institutions (HEIs) and including LD support in PhDs teaching training were identified.<br/
Mental health disorders and recidivism among incarcerated adult offenders in a correctional facility in South Africa: a cluster analysis
Get PDFThe contribution of mental illness, substance use, and appetitive aggression to recidivism has significant policy and practice implications. Offenders with untreated mental illness have a higher recidivism rate and a greater number of criminogenic risk factors than those without mental illness. Previous research has demonstrated that the likelihood of appetitive aggression increases in violent contexts where individuals perpetrate aggressive acts. Using the Ecological Systems Theory, this study investigated the association between mental health disorders and recidivism among incarcerated adult offenders in South Africa, and the intervening role of appetitive aggression and substance use. Using a cross-sectional quantitative research design, a sample of 280 incarcerated male and female adult offenders aged 18-35 with no known psychiatric disorders were sampled at a correctional facility in South Africa. The re-incarceration rate, mental health disorders, substance use, and appetitive aggression symptomology were assessed using the Hopkins symptoms checklist, the CRAFFT measure of substance use, and the appetitive aggression scale. Findings indicate a 32.4% recidivism rate (n = 82). Cluster analysis indicated that the combination of anxiety, depression, substance use, and appetitive aggression increased the likelihood of recidivism. Appetitive aggression median differences between clusters 2 and 3 played a key role in distinguishing recidivism risk among recidivist and non-recidivist participants. Chi-square analysis highlighted group differences in education levels among the established clusters [x2 (3, n = 217) = 12.832, p = .005, which is < .05] as well as group differences in the type of criminal offence [x2 (3, n = 187) = 24.362, p = .000, which is < .05] and cluster membership. Combined factors that increase the likelihood of recidivism provide a typology for classifying offenders based on particular recidivism risk determinants, which offers insights for developing tailored interventions that address a combination of factors
Effect of probe lifting height in jumping mode AFM for living cell imaging
Get PDFAtomic force microscopy (AFM) is one of the effective methods for imaging the morphological and physical properties of living cells in a near-physiological environment. However, several problems caused by the adhesion of living cells and extension of the cell membranes seriously affect the image quality during living cell imaging, hindering the study of living cells. In this work, jumping mode AFM imaging was used to image living cells at varied probe lifting heights to meet image quality requirements, and image quality related to the probe lifting height is discussed in detail. The jumping mode was divided into three parts based on the varying heights of the lifted probe, namely near-contact mode, half-jumping mode, and full-jumping mode, and the causes of their imaging drawbacks were analyzed. At an appropriate lifting height, the probe can be completely free from the influence of cell adhesion and self-excited oscillation, thus avoiding the occurrence of “trail” phenomena and invalid points in the imaging of living cells and improving the image quality. Additionally, this work provides a new approach to calculating the lateral force through the adhesion of trace and retrace scanning at a low height, which is important for studying the extension characteristics of the cell membrane
Britain likes to think it ‘stood alone’ against the Nazis. So why did it convict so few for war crimes?
No full textOut of 274 suspects investigated in England, Wales and Scotland, there was only a single convictio
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