Bank of New York Mellon

The world is facing a lack of freshwater because of high population growth rates, and an increase in industrial activities. Therefore, new approaches to wastewater treatment and recycling are essential in sustainable water management. This chapter focuses on the integration of adsorption, which is an economically feasible method of pollutant removal, and Artificial Neural Networks (ANNs), known for their exceptional skills in complex system modeling and process optimization. ANN aids in increasing the efficiency and flexibility of adsorption systems to ensure appropriate water quality for reuse. This integration is feasible and beneficial not only from an environmental perspective, but also from an economic one, as shown through its practical implementation in municipal and industrial settings.

The pharmaceutical industry faces significant cybersecurity challenges, increasing threats to sensitive data, intellectual property, and patient information. Traditional cybersecurity models, including signature-based and threshold-based intrusion detection systems (IDS), often fail to address cyber threats’ dynamic and evolving nature. This paper introduces a novel Artificial Intelligence (AI-driven) cryptographic system designed to enhance cybersecurity in the pharmaceutical sector. The proposed model integrates advanced AI techniques, including reinforcement learning, game theory, and C*-algebra, to optimize resource allocation, improve threat detection, and enhance cryptographic protocols. Through a comprehensive evaluation, the AI model demonstrates superior performance over traditional methods, achieving a detection rate of 97.4%, significantly reducing false positive rates (2.6%) and response time (50ms), and achieving an F1-score of 0.95. Additionally, the AI model’s ability to continuously adapt to emerging cyber threats makes it a future-proof solution for the pharmaceutical industry. The model’s scalability ensures its applicability across various organizational sizes. Future research directions include the integration of blockchain, cloud computing, and post-quantum cryptography to strengthen the system’s resilience further. This paper presents a scalable, adaptive, and efficient solution to address the growing cybersecurity challenges in the pharmaceutical industry, ensuring critical data protection in an increasingly complex threat landscape.

The last several decades have witnessed tremendous changes in algorithmic trading and quantitative finance due to advances in data analytics, computing capacity, and technology. This study examines how these industries will evolve in the future while providing a thorough overview of recent advancements and upcoming trends. The paper starts with a historical review that traces the development of algorithmic trading methods and quantitative finance, emphasizing significant turning points and technical innovations. We examine the latest developments in high-frequency trading (HFT), the use of big data analytics, and the fusion of artificial intelligence and machine learning as they relate to quantitative finance. The study looks at a number of algorithmic trading techniques, including as sentiment-based trading, statistical arbitrage, trend following, mean reversion, and market creating. The potential for developing technologies to transform financial markets and trading methods is also taken into account, including the influence of blockchain, quantum computing, and sophisticated data visualization tools.

Growing urbanisation and technological integration have made smart cities vital worldwide. Modern ICT will boost efficiency, sustainability, and quality of life in these cities. Smart cities are exposed to a wide range of cybersecurity assaults that could threaten their operational integrity and people' well-being due to their growing reliance on digital infrastructure. The many cybersecurity issues in smart cities are examined in this paper. It examines urban information and communication technology (ICT) system vulnerabilities and how cyber events could affect transportation, electricity, and public safety services. We examine smart city cybersecurity and find gaps that make them vulnerable to hackers. We propose integrating cutting-edge technologies with smart city cybersecurity infrastructure to overcome these issues. This framework uses AI and machine learning for threat detection and predictive analytics, blockchain technology for secure data sharing and authentication, and powerful encryption protocols for data protection. We also stress the importance of merging technology and policy to address cybersecurity. Cybersecurity standards, laws, and international cooperation agreements should be created. We believe such an all-encompassing approach is necessary to build resilient smart cities that can withstand changing cyber threats. The report also emphasises the need for ongoing education and awareness initiatives to ensure that all stakeholders, from city authorities to the public, understand cybersecurity and their role in maintaining a safe urban ecology. In conclusion, this research provides a roadmap for smart city cybersecurity by strategically merging cutting-edge technologies and applying the best cybersecurity governance approaches. This document gives policymakers, urban planners, and technology professionals a basic resource to assure the digital future of our urban surroundings.

In the world of enterprise-level applications, the construction and utilisation of large language models (LLMs) carry a paramount significance, accompanied by the crucial task of mitigating hallucinations. These instances of generating factually inaccurate information pose challenges during both the initial development phase of LLMs and the subsequent refinement process through prompt engineering. This paper delves into a variety of approaches such as retrieval augmented generation, advanced prompting methodologies, harnessing the power of knowledge graphs, construction of entirely new LLMs from scratch etc, aimed at alleviating these challenges. The paper also underscores the indispensable role of human oversight and user education in addressing this evolving issue. As the field continues to evolve, the importance of continuous vigilance and adaptation cannot be overstated, with a focus on refining strategies to effectively combat hallucinations within LLMs.

Electrification of car and passenger ferries is an important step towards maritime decarbonization. Charging profiles are generated using a probabilistic method for electric vehicles (EVs) and a deterministic method for electric ferries. A test scenario from western Norway is taken for analysis with 2 MW and 9 MW ferry charging together with high power EV charging. The ferry charging causes an increase in peak load which could be mitigated by installing a battery energy storage system (BESS). When high power EV charging is included in the two cases, the peak demands increase even more. Without a BESS, reinforcing the power grid would be required.

Engineering and technological developments are at the core of societal change, influencing and being influenced by society's cultural, political, economic, and socio-technical contexts. However, various engineering educators and philosophers have pointed out that traditional engineering ethics education tends to focus on micro-ethics rather than macro-ethical issues. Therefore, this panel aims to discuss the broader implications of engineering and technology in society using a human rights framework. The United Nation's Universal Declaration of Human Rights has served as a globally recognized standard that briefly outlines the fundamental rights, including life and liberty, and the right to work and education, among other civil, political, economic, social, and cultural rights. Those rights are realized within systems where governments and industry play a key role as duty-bearers, and academia plays a crucial role in educating and researching ethical principles and promoting and protecting human rights. All three form part of the triple helix innovation model, where a common theme is the protection and promotion of human rights.

O Dia de Campo presencial oferece interao valiosa, mas eventos online, como Dias de Campo virtuais, tm se destacado devido acessibilidade e flexibilidade das plataformas digitais.Este estudo analisa a substituio do Dia de Campo presencial por uma verso online, com foco nas implicaes para produtores rurais e profissionais da pecuria.Observou-se que, embora o TecLeite seja concebido para atender demandas regionais, a adaptao para o formato online possibilitou uma expanso significativa da abrangncia territorial,

The book, Strategic Human Resource Development in Practice, provides processes and tools that will help meet the needs of employees and the organization.

Abstract Providing learning interventions is at the heart of HRD practices, from onboarding people joining the workforce to continuing to develop them for advanced productivity and career progression. If learning interventions are going to provide value to the organization, they must translate into improved individual and organizational performance. Learning transfer refers to the extent to which the individual or team applies their learning beyond the learning event itself. This learning can be changed in knowledge, insight, understanding, meaning, attitudes, competencies, behaviors, and they may or not be connected depending on the goal/purpose of the learning intervention. Ultimately, the returns on investment for these learning and development interventions depend on whether the individual or team is able to transfer their learning to their workplace practices.