Vital Asset Research Articles

Railway embankment failure trends and monitoring – lessons learned from the Anglia route

UK railways were constructed with little consideration of engineering practice and with climate change and the associated greater frequency of extreme weather events, comes the impact on earthworks stability and risk to public safety. Many embankments on Network Rail’s Anglia route have shown a gradual degradation through their steep upper slopes and progressive failure within predominantly clay embankment material and underlying soft deposits. A regional wholistic view allows identification of common geotechnical trends and risk categorisation to better enable prioritisation of asset management. Understanding when to intervene is crucial and monitoring the behaviour of earthworks is a vital asset management tool to control risk and extend lifespan. To be a wise investment, slope instrumentation must be properly thought out in line with a detailed interrogation of the site and alongside a well-developed conceptual model. Automated monitoring can bring greater control and allow more accurate evaluation of intervention but must be assessed in line with prioritising large areas with limited budgets. Correct targeting of ground investigation and ensuring sufficient and reliable data can optimise mitigation and provide confidence the solution has provided resilience to railway infrastructure.

Enhanced ANN-based ensemble method for bridge damage characterization using limited dataset

Bridges are vital assets of transport infrastructure, systems, and communities. Damage characterization is critical in ensuring safety and planning adaptation measures. Nondestructive methods offer an efficient means towards assessing the condition of bridges, without causing harm or disruption to transport services, and these can deploy measurable evidence of bridge deterioration, e.g., deflections due to tendon loss. This paper presents an enhanced input-doubling technique and the Artificial Neural Network (ANN)-based cascade ensemble method for bridge damage state identification and is exclusively relying on small datasets, that are common in structural assessments. A new data augmentation scheme rooted in the principles of linearizing response surfaces is introduced, which significantly boosts the efficiency of intelligent data analysis when faced with limited volumes of data. Furthermore, improvements to a two-step ANN-based ensemble method, designed for solving the stated task, are presented. By adding the improved input-doubling methods as simple predictors in the first part of the cascade ensemble and optimizing it, we significantly boost accuracy (7%, 0.5%, and 8% based on R2 in predicting tendon losses for three critical zones that were defined across the deck of a real deteriorated prestressed balanced cantilever bridge). This improvement is strong evidence of the accuracy of the proposed method for the task at hand that is proven to be more accurate than other methods available in the international literature.

Unmanned surface vehicles for naval warfare and maritime security

There is a growing need to implement maritime defensive systems, covering both medium-range and close-in defenses. This is in response to the escalating threat posed by unmanned surface vehicles (USVs) in a rapidly changing environment. As unmanned technologies become more widespread and advanced, the proactive deployment of these defensive measures is becoming imperative. This strategic approach aims to reduce risks, protect vital assets, and bolster the Navy’s flexibility in adapting to the evolving dynamics of contemporary naval warfare. This initiative aligns with broader goals of upholding maritime security and contributing to regional stability amid rapidly shifting conditions in warfare. This perspective covers the relevant aspects of USV development, and the countermeasures being considered.

Sustainable Development and Traditional Knowledge with Special Reference to the Bodo Community

Traditional Knowledge of local or indigenous communities are developed and nurtured over many generations. Its wisdom has enabled communities to adapt and interact with their environment. The knowledge system of indigenous communities is embedded in their traditions, customs and practices. In many cases, such knowledge is orally transmitted through folklore, art, customary laws and rituals. Indigenous communities possess a wide array of traditional knowledge developed through the collection of insights of their surroundings and as a response to it. This has allowed them to sustain and reduce risks, thus enabling them to co-exist, utilize and adapt with their surroundings. Traditional knowledge, therefore, forms a vital asset for the indigenous communities such as the Bodos of North-east India. Due to globalization and the development of modern sciences and technology, the traditional knowledge of indigenous societies faces multiple challenges and have witnessed the reduction in its importance. However, the growing emphasis on sustainable development has begun to shed a new light in its direction. This paper, therefore, is an attempt to study the relevance of traditional knowledge in the achievement of sustainable existence of human beings with an emphasis on the Bodos community.

Follower persuade Leader Green Commitment: Exploring Sustainability in Pharma Companies

This study investigates the impact of follower green knowledge (FGK) on leader green commitment through moderation (follower perceived organizational support) and mediation (leader motivation toward sustainable development goals). A total of 429 respondents from large pharmaceutical companies operating in different regions of Pakistan were selected. PLS-SEM and Johnson–Neyman plots were used for the conditional moderation mediation model. The results of the hypotheses including the conditional moderation mediation model were significant. Moreover, follower knowledge is a vital asset for persuading leader commitment when followers receive organizational support and leaders are motivated to adopt sustainable development goals. This study opens new avenues for leadership development programs. Moreover, enhancing green awareness and knowledge through training stimulates innovation and promotes experimentation with new environmentally friendly practices within the organization. Organizations must recruit new employees who possess green knowledge. This study adopts a leadership perspective based on the concept of sustainable followership. This study reveals the importance of followers in bringing leaders’ internal willingness toward sustainability development goals. This study uses leader–member exchange theory to highlight the importance of followers in creating a sustainable culture through their knowledge, awareness and support from peers.

Community voices in health literacy: a qualitative exploration into perceptions of a health literacy mediator.

Health literacy is a vital asset needed to empower individuals to take control of their health. An individual's health literacy is the ability to find, use and apply health information and services to manage their health. They interact with the health services and members of their community who can offer additional support. Creating the role of a health literacy mediator (HLM) may help to improve health literacy outcomes for all. For this role to be accepted by individuals within a community, the community itself should be involved in the development of the roles and associated responsibilities. The aim of this study was to engage with community members to acquire their perspectives on the potential of this role. Qualitative semi-structured online interviews were used to engage in discussions with local community members. This study implemented a constructivist epistemology with qualitative research design. Data were thematically analysed to identify evolving themes that were important to the HLM role. The analysis identified three main themes that need to be considered when adopting an HLM role: (i) health empowerment of individuals, organizations and communities, (ii) meeting the needs of the community and (iii) addressing the existing barriers in navigating and accessing the healthcare system. Those working in the health promotion space must adopt novel and innovative ways to improve HL on both a local and an international scale. This study concluded that for the role of a HLM to be accepted, it would need to encompass these attributes.

Research on Mental Health Assessment and Intervention Methods for College Students based on Big Data Analysis

This study introduces the novel Fuzzy-Enhanced Predictive Neural System for Student Mental Health (FEPS-MH) approach to mental health assessment and intervention for college students. FEPS-MH synergistically combines a Backpropagation (BP) Neural Network with a Deep Fuzzy-Based Neural Network (DFBNN), leveraging the strengths of both systems to handle the complexities of mental health data in the context of big data analytics. The BP Neural Network, known for its effective learning and generalization capabilities, is integrated with the DFBNN to process imprecise, uncertain, or subjective data, typical in mental health assessments. The core objective of FEPS-MH is to provide a more accurate, robust, and sensitive analysis of mental health states, incorporating the nuanced variations and uncertainties inherent in psychological data. This system is designed to analyze a vast array of data sources, including but not limited to, behavioral patterns, self-reported questionnaires, and social media interactions, to identify potential mental health issues among college students. FEPS-MH’s capabilities extend beyond mere assessment; it is also equipped to recommend personalized intervention strategies. Utilizing big data analysis, the system not only predicts potential mental health crises but also suggests tailored intervention approaches based on the unique psychological profile of each student. This study demonstrates the feasibility and effectiveness of FEPS-MH through a series of tests and validations using real-world data. The results indicate a significant improvement in both the accuracy of mental health assessments and the efficacy of suggested interventions. FEPS-MH stands as a promising tool for educational institutions, offering a data-driven, sensitive, and comprehensive approach to student mental health care. Its implementation could revolutionize the field of mental health support in college environments, making it a vital asset for proactive psychological wellness in educational settings.

The Influence of Work Engagement and Knowledge Sharing on Nurse Performance

Human resources who serve as officers or employees in a company or institutional organization are always considered a vital asset for an organization. Performance or work achievement can be interpreted as achieving work results in accordance with the rules and standards that apply to each organization. Performance can also be said to be the result or output of a process. The purpose of this research is to find out directly the influence of work engagement and knowledge sharing on employee performance at RSD dr. Soebandi Jember. The total sample in this study was 171 inpatient nurse respondents with a minimum work period of 3 years. Descriptive analysis is used to determine the respondent's description. Validity test and reliability test for the validity and reliability of research data. Hypothesis testing was also carried out in this research. The research results show that work engagement and knowledge sharing partially have a positive and significant effect on the performance of RSD dr. Soebandi Jember.

Insights into the visitations of oceanic manta rays at cleaning stations on coral reefs in the Bird's Head Seascape, eastern Indonesia

The globally endangered oceanic manta ray Mobula birostris is believed to spend significantly more time in the open ocean than in coastal areas. Nonetheless, the Bird's Head Seascape (BHS) in eastern Indonesia hosts a large population of this species (over 850 individuals), frequently sighted at coral reef cleaning stations and forming a vital asset for marine tourism in the region. Despite this, detailed understanding of the movements and habitat use of this wide-ranging species within shallow (< 30 m) coral reef ecosystems remains limited. Addressing this knowledge gap is urgently required for the sustainable management of oceanic manta ray-focused tourism in the region. Here, we report the results of an initial passive acoustic telemetry study investigating the use of coral reef cleaning stations by oceanic manta rays. Forty-one rays were acoustically tracked from February 2016 to August 2019 in an array of 28 acoustic receivers deployed at known cleaning stations and hypothesized transit points across the BHS (including the regions of Raja Ampat, Fakfak, and Kaimana). A total of 5,822 detections were recorded by 16 of the 28 receivers from all tagged individuals, and 421 visitation events were documented from 37 out of the 41 tagged individuals, providing valuable insights into their visitation patterns at cleaning stations. Tagged individuals were detected at receiver stations for durations ranging from 0.2 to 427.0 min (mean ± SD = 48 ± 64 min). Notably, 94% of detections were recorded during daylight hours (reaching a peak at noon), underscoring an apparent diurnal pattern in time spent around cleaning stations. The study documented frequent short-range movements between adjacent receivers (5–12 km apart), with two-thirds of all 191 tracked movements occurring between neighboring stations in southern Raja Ampat. Notably, tagged individuals were detected repeatedly at three cleaning stations which were previously only known for hosting reef manta rays, suggesting oceanic manta rays likely also utilize these cleaning stations. Our study provides important insights into the visitations and local movements of oceanic manta rays between coral reef cleaning stations, which will inform effective oceanic manta ray conservation efforts and tourism management in the BHS.

ASSESSING CONSERVATION APPROACHES FOR SUSTAINING HERITAGE BUILDINGS: A CASE STUDY OF IPOH OLD TOWN, PERAK, MALAYSIA

The worldwide emphasis on heritage building conservation has become one of the strategies to effectively conserve the values of heritage buildings and preserve their historic significance. Heritage buildings, acknowledged as vital assets for local development, particularly in the realm of tourism and cultural enrichment, require conservation efforts aligned with urban regeneration initiatives. Despite these international efforts, challenges persist in implementing effective conservation strategies, resulting in continuing deterioration. Therefore, a better understanding of the approach needed to conserve heritage building is important for its long-term sustainability. This qualitative study, involving site observation and semi-structured interviews with the Ipoh City Council and caretakers of selected heritage buildings, focuses on Ipoh Old Town as a case study as it is a historical area abundant in heritage and cultural elements. The findings highlight preservation and rehabilitation as prevalent conservation approaches, while restoration poses notable challenges in sustaining heritage buildings in Ipoh Old Town.

The Application of Infrared Thermography for Enhancing Maintenance in Public University

A university’s main function is to produce quality graduates, and in doing so, university buildings do play significant roles and are vital assets and resources. Hence, to prolong a university building lifecycle to ensure all university activities to continue performing at an optimum level, building maintenance management is central. Eventhough previous studies have been conducted in this area, university buildings maintenance is still viewed as insignificant. The research about utilization of infrared thermography in term of maintenance in public universities is still lacking. The objective of this research was to provide recommendations for areas within the public universities that can benefit from the application of infrared thermography to enhance maintenance. The research method used in this research was a qualitative method. Three public universities that were established for more than 50 years were chosen as case studies. The data was collected through narrative review and then analyzed. The findings highlighted the benefits of implementing infrared thermography in older building maintenance within public universities, particularly in improving energy efficiency and identifying hidden issues such as moisture intrusion and structural defects. The study emphasized the importance of timely maintenance actions based on infrared thermography assessments to reduce energy consumption and apply predictive maintenance strategies. By conducting in-depth analyses at three established public universities in Malaysia, the researchers demonstrate the effectiveness of infrared thermography in enhancing maintenance practices and prolonging the lifecycle of university buildings.

Wealth in Water: A Blueprint for Sustainable Global Ocean Research

Pushing forward with leveraging water resources, promoting international cooperation, and ensuring transparency in deep-sea mining operations. There is also a concern about where to discharge the toxins of unpurified water. Artificial Intelligence has created a dominance in the applications field with a totally automated system. Out of a thorough analysis completed with indicators, satellite radar, and A Journals, there are 30 years of research and 8 years of monitored testing to achieve accuracy and relevance. The patents in place are, Oceanic Mining System (4446636), Flexible Solar Skin in Combination with an Airplane (4768738), Cargo Torpedo (4421050), Oceanic seaplow system (4398362), and previous articles like “Is Extracting Lithium and deep-sea mining more sustainable?”, “AI as a Means of Water Purification Protection”, “Global Water Distribution”, and “Can Deep Sea Water be Processed into Potable Water and Distributed into the Middle East’? To report some ballpark numbers on the proposal and how we would navigate these projects, there will be an exact location of where the plant will be built as well as a water/salinity report of the water being treated. There are still issues with analyzing the cost of desalination compared to other alternatives. Deep Sea Water proves to be a higher quality water and the investment is well worth it. The surveys lean toward clients preferring the International Standards Operating Procedure. All recipients agree there should be a sense of urgency on water shortages. Currently, AI has proven to be a vital asset in eliminating biases and expenses.

Malaria Slide Bank to Strengthen and Improve the Quality of Malaria Diagnosis: A National Slide Repository in India.

Malaria elimination is one of the top health care priorities in India, necessitating accessible and accurate diagnosis for effective treatment. A malaria slide bank in India is a collection of quality-controlled malaria-positive and -negative slides and is considered a vital asset for quality diagnosis. The collection of blood samples, preparation of blood smears, staining, quality control, molecular characterizations, and slide validation were carried out according to standard operating procedures in accordance with the WHO reference laboratory. The true count and parasite density per microliter were computed in accordance with WHO guidelines. Over 27 months, 48 batches (8,196 slides) were prepared. Overall, the majority of slide batches were Plasmodium vivax (45.9%; 22/48), followed by Plasmodium falciparum (25%; 12/48), malaria-negative infections (25%; 12/48), and mixed infections (4.1%; 2/48). All 48 batches passed internal validation by WHO-certified level-1 microscopists. For a batch, the true count was the median of the validators' counts (range, 111-280,795 parasites/µL). Except for mixed infections, the PCR results agreed with the verified microscopy results. Malaria slide bank slides would be a valuable tool for quality control, assurance, and microscopist training.

Optimizing maintenance logistics on offshore platforms with AI: Current strategies and future innovations

Offshore platforms are vital assets for the oil and gas industry, serving as the primary facilities for exploration, extraction, and processing. Maintenance logistics plays a crucial role in ensuring these platforms operate efficiently and safely. However, the remote and harsh environments of offshore platforms present significant challenges for maintenance activities. Traditional maintenance strategies often struggle to meet the demands of these environments, leading to inefficiencies, increased costs, and potential safety risks. This review discusses the application of Artificial Intelligence (AI) in optimizing maintenance logistics on offshore platforms. Current strategies involve a combination of preventive, predictive, and corrective maintenance approaches. Preventive maintenance schedules regular inspections and replacements based on predetermined intervals, while predictive maintenance utilizes data analytics to predict equipment failures and plan maintenance activities accordingly. Corrective maintenance addresses issues as they arise, often in response to unexpected failures. AI offers opportunities to enhance these strategies by leveraging advanced data analytics, machine learning, and optimization algorithms. AI-enabled predictive maintenance can analyze vast amounts of data from sensors, historical maintenance records, and environmental factors to forecast equipment failures with greater accuracy. This allows for proactive maintenance planning, minimizing downtime and reducing maintenance costs. Furthermore, AI can optimize maintenance logistics by improving resource allocation and scheduling. Through real-time monitoring and analysis, AI systems can prioritize maintenance tasks based on urgency, equipment criticality, and resource availability. This ensures that maintenance crews are deployed efficiently, reducing idle time and improving overall productivity. Future innovations in AI for maintenance logistics on offshore platforms include the integration of Internet of Things (IoT) devices and autonomous systems. IoT sensors can provide real-time data on equipment condition and environmental factors, enabling more precise predictive maintenance models. Autonomous maintenance robots equipped with AI algorithms can perform routine inspections and minor repairs, reducing the need for human intervention in hazardous environments. However, implementing AI in offshore maintenance logistics also poses challenges, including data quality, cybersecurity, and workforce readiness. Ensuring data accuracy and reliability is crucial for effective AI models, requiring robust data collection and management processes. Cybersecurity measures must be strengthened to protect AI systems from malicious attacks that could disrupt operations or compromise safety. Additionally, workforce training and education are essential to prepare personnel for working alongside AI systems and interpreting AI-generated insights. Optimizing maintenance logistics on offshore platforms with AI offers significant benefits in terms of efficiency, cost savings, and safety. By leveraging AI technologies, current maintenance strategies can be enhanced, and future innovations can revolutionize offshore maintenance practices, making operations more sustainable and resilient in the face of evolving challenges.

Energy Efficiency Examination and Analysation in Wireless Sensor Networks

Wireless sensor networks (WSNs) have risen as a vital innovation empowering a horde of applications extending from natural checking to mechanization. In any case, the constrained vitality assets of sensor hubs pose critical challenges to the life span and execution of these systems. This theory presents a comprehensive audit of procedures and techniques to move vitality proficiency forward in WSNs. The survey starts by analyzing power efficient equipment plan approaches, counting low power microcontrollers, energy harvesting frameworks, and ultra low power communication conventions. Besides, it investigates energy aware steering conventions that optimize information transmission ways to minimize vitality utilization, such as Filter (Moo Vitality Versatile Clustering Progression) and its variations. Moreover, rest planning instruments are examined, which permit sensor hubs to interchange between dynamic and rest states to preserve vitality while keeping up an organized network. Additionally, the theoretical dives into the part of information conglomeration and compression procedures in decreasing excess transmissions and maintaining vitality at the arranged level. It highlights the importance of versatile obligation cycling instruments, where sensor hubs powerfully alter their obligation cycles based on natural conditions and application prerequisites. Moreover, progressions in energy efficient MAC (Medium Get to Control) conventions are analyzed, centring on conventions like IEEE 802.15.4 and their improvements for WSNs. Furthermore, the integration of machine learning and optimization calculations for energy efficient operation and asset assignment in WSNs is examined. At last, the theory concludes with a viewpoint on rising patterns and future headings in the field, counting the integration of energy harvesting advances, the improvement of self sustainable sensor hubs, and the investigation of novel communication standards such as unmistakable light communication.

MAINTENANCE STRATEGY REVIEW (MSR) BASED ON ISO 14224:2016 IN INDONESIA OIL AND NATURAL GAS COMPANIES

<p>The oil and gas industry is vital for Indonesia, and the safety and effectiveness of work in processing and exploring the oil and gas that operate in Indonesia must comply with existing regulations. This safety and effectiveness are inseparable from how the company maintains the assets and instruments used at the oil and gas production and exploration site. Maintenance of pipes and instruments for production is one of the company's most vital assets. In addition to having appropriate productivity, pipes and instruments must be maintained optimally so that maintenance costs do not exceed the value of the oil and gas production. This study's research subject is a natural gas refinery from an oil and gas company operating in the Madura Strait, East Java, Indonesia. The object of research limited to the company's piping system (pipeline system). This study uses a quantitative assessment using the calculated Mean Time Before Failure (MTBF) method and a qualitative assessment using the asset maintenance standard to reveals how the maintenance cycle that has been implemented can be optimized. The author carried out a criticality assessment using Maintenance Strategy Review (MSR) to calculate the risk level of asset. This study found that 78 assets must be maintained in their maintenance cycle, two cash assets must be reduced in their maintenance cycle, and seven assets can be extended for their maintenance cycle. The two assets that need to be reduced in maintenance cycles are the shutdown valve asset that goes to the temporary pig receiver and the shutdown valve that goes to the HP flare header. An asset that can be extended its maintenance cycle is a transmitter for flow indicators.</p><div><div><p> </p></div></div>

Exploratory Data Analysis Based Design and Implementation of Student Stress Detection Using Machine Learning Approaches

The administration of stress is fundamental in perceiving the degrees of stress that can prevent our own and social prosperity. As per the World Wellbeing Association, roughly one of every four people experience pressure related mental issues, prompting mental and financial issues, unfortunate working environment connections, and even self-destruction in serious cases. Guiding is a vital asset to assist people with adapting to pressure. While stress can't be totally kept away from, preventive measures can help with overseeing feelings of anxiety. At the moment, only experts in medicine and physiology can tell if someone is stressed or not. Nonetheless, the conventional technique for distinguishing pressure in view of self-revealed replies from people is untrustworthy. Using physiological signals to automate the detection of stress levels, a more accurate and objective strategy for reducing health risks and enhancing society's well-being is available. A significant social contribution that can improve people's lives is the detection of stress levels. The IT business has presented new advancements and items that guide in the recognition of feelings of anxiety in workers, which is basic in upgrading their presentation. Albeit a few associations offer emotional well-being plans for their workers, the issue stays testing to make due. The machine is subjected to exploratory data analysis (EDA) in order to determine its accuracy. EDA is utilized on dataset so individual boundaries will be broke down with exactness and plotted in graph.The organization of stress is central in seeing the levels of pressure that can forestall our own and social success. According to the World Prosperity Affiliation, around one of each and every four individuals experience pressure related mental issues, provoking mental and monetary issues, lamentable work space associations, and, surprisingly, implosion in serious cases. Directing is an essential resource for help individuals with adjusting to pressure. While stress can't be completely avoided, preventive measures can assist with supervising sensations of nervousness. At this time, only specialists in physiology and medicine can determine whether a person is stressed or not. Regardless, the regular method for recognizing tension considering self-uncovered answers from individuals is conniving. Utilizing physiological signs to robotize the discovery of feelings of anxiety, a more precise and objective procedure for decreasing wellbeing chances and upgrading society's prosperity is accessible. A critical social commitment that can further develop individuals' lives is the location of feelings of anxiety. The IT business has introduced new progressions and things that aide in the acknowledgment of sensations of nervousness in laborers, which is fundamental in redesigning their show. Yet a couple of affiliations offer close to home prosperity plans for their laborers, the issue stays testing to make due. The machine is exposed to exploratory information examination (EDA) to decide its precision. EDA is used on dataset so individual limits will be destitute down with precision and plotted in chart.

Enhancing Damage Detection in 2D Concrete Plates: A Comprehensive Study on Interpolation Methods and Parameters

In an era marked by increasing demands for stability and durability in construction, the importance of damage detection in concrete structures cannot be overstated. As these structures underpin the safety and longevity of vital assets, this paper embarks on a comprehensive exploration of methodologies to enhance precision and reliability in 2D concrete plate damage detection. By focusing on the interpolation of damage index values and leveraging the insights gained from energy loss analysis and the characterization of the time of arrival of signals, we address the pressing need for improved non-destructive damage detection techniques. Our study encompasses a range of simulation attempts, each involving various interpolation parameters, and systematically evaluates their performance. The culmination of this research identifies the most effective combination of techniques and parameters, leading to the best results in damage detection. This multidimensional investigation promises to provide valuable contributions to the field of structural health monitoring, benefiting both researchers and practitioners engaged in the evaluation of concrete structures.

The Potential Hazards of Fake Accounts and Buzzer Behaviour on Deliberative Democracy

The most famous political system globally is deliberative democracy, which involves the participatory engagement of free and fair citizens to achieve common interests through discussion-based reasoning and societal consensus. This system places all citizens on an equal footing in expressing their opinions and is a crucial indicator of the quality of deliberative democracy. The dynamics of deliberative democracy are also mirrored in the digital realm and often serve as indicators of public support. However, the digital sphere of democracy faces a severe threat today due to the proliferation of fake accounts and the practice of paying for buzzer behaviour. This phenomenon necessitates stringent regulation to ensure the continued quality and authenticity of deliberative democracy. This research describes the potential dangers of using fake accounts and paying for buzzer behaviour in politics concerning deliberative democracy. The researchers adopted an interpretive phenomenology approach, drawing data from various relevant sources. The research findings reveal that using fake accounts and paying for buzzer behaviour undermine deliberative democracy as they generate false information, manipulate public opinion, and hinder healthy dialogue. Additionally, using fake accounts and buzzer behaviour has severe psychological and social repercussions, including a decline in public trust and an increase in political polarization, all threatening the quality of democratic decision-making. The results of this research carry significant implications for designing relevant regulations to safeguard the agreed-upon and high-quality deliberative democracy, a vital asset of public governance. Keywords: Fake accounts, buzzer behaviour, cyber trooper, deliberative democracy, virality.

The Role of Threat Intelligence in Enhancing Cybersecurity Posture

Organizations confront more complex and persistent cyberattacks in the quickly changing cyber threat landscape of today. Through the provision of actionable insights on emerging threats, adversary tactics, and vulnerabilities, cyber threat intelligence (CTI) becomes an increasingly important component in strengthening the cybersecurity posture of organizational networks. The importance of CTI and its useful uses in enhancing cybersecurity defences are examined in this research study. It explores the several kinds of threat intelligence, methods for compiling and evaluating threat information, and proactive steps that businesses may take to make the most of CTI. This study emphasizes the significance of incorporating CTI into cybersecurity plans to more effectively identify, prevent, and respond to cyber attacks through a thorough review of industry practices and case studies. Organizations may improve their defences against cyberattacks and enhance vital assets and data by comprehending the role that CTI plays in cybersecurity.