Search Results (72)

This study explores the role of populist leaders as gatekeepers on social media, seeking to understand how André Ventura, president of Chega!, uses news to legitimize his political discourse. The methodology involved collecting 90 tweets containing legacy media news features, posted by Ventura on the social media platform X. These tweets cover key political events such as the resignation of Portugal’s Prime Minister, the dissolution of the Portuguese Parliament, and European elections. Quantitative analysis using Voyant Tools identified key terms related to Ventura’s ideological stance, while Critical Discourse Analysis (CDA) examined how these terms support his political narrative. The findings reveal a strategic use of news to promote themes like nationalism, immigration control, corruption and social dichotomy between “us” and “them”. Ventura’s tweets leverage news headlines to enhance his persuasive appeal, acting as heuristic shortcuts to reinforce his political messages. This study highlights the relevance of understanding social media’s role in promoting populism and suggests avenues for future research, including comparative analyses of other populist leaders and the impact of these narratives on voter behavior and perceptions. Full article

The aim of this study is to investigate how amplifiers are used in Twitter (now called “$\mathbb{X}$”) during election campaigns. Specifically, the main purpose is to identify the role and engagement of Twitter amplifiers in the 2019 European elections, the visibility of political parties and leaders, and the way in which automated tools are used to manipulate public opinion by influencing voting decisions. The countries considered in the study are two economic powers of Western Europe, France and Germany, as well as two countries of the European South, which are affected by the economic and financial crisis, Greece and Italy. The countries from Southern Europe were included in the sample as they are often used by mass media as political campaign tools. This paper emphasizes the Twitter platform through which the data collection was implemented using the official API of the social networking tool, focusing on the 2019 European elections. We collected data on 88 party leaders and MEP candidates between 10 May and 30 May 2019, as well as on 44,651 accounts that retweeted them. We concluded using 237,813 election-related tweets and used network theory to analyze and visualize the data. The results demonstrate that all political parties use amplifiers to promote their tweets, and some use the same amplifiers between different countries. Full article

Background: The COVID-19 pandemic has impacted nursing theatre staff, departmental activity, and delivery of services to patients. This work-based project aimed to investigate the challenges of nursing leadership in an elective orthopaedic department at current times. Methods: The study collected qualitative data exploring theatre staff’s expectations from leadership, offering insight on how the pandemic has influenced the way of working and exploring how the future in this unit may look. The answers from 20 practitioners to an anonymised open-ended survey were examined using thematic analysis. Results: The participants described a leader as a good communicator who focuses on empowering others and supporting the team, identified by the majority as a senior team member. From the findings, three topics were identified: immediate changes, delayed changes, and pre-existing conditions. The answers painted a reality that is complex and multifaceted, where numerous variables play a part in the physical and mental health of each candidate, impacting their performance as well as their work/life balance. Overall, the strongest subjects recurring in the findings were the need for nursing leadership to focus on supporting staff with training opportunities, to actively plan for a reduction in staffing shortages, and to be constantly mindful of staff well-being. Conclusions: This study pointed out that the need for constant communication with their staff, building honest relationships, and being a reliable leader, focused on empowering others and supporting the team were important factors for the nursing management during the COVID-19 pandemic and post-COVID-19 era. Full article

This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is designed for indoor settings like historical buildings and museums, tracking visitors and identifying points of interest. It serves as an evacuation aid by monitoring occupancy and gauging the popularity of specific areas, subjects, or art exhibitions. The middleware employs a basic form of the MapReduce algorithm to gather WSN data and distribute it across available computer nodes. Data collected by RFID sensors on visitor badges is stored on mini-computers placed in exhibition rooms and then transmitted to a remote database after a preset time frame. Utilizing MapReduce for data analysis and a leader election algorithm for fault tolerance, this middleware showcases its viability through metrics, demonstrating applications like swift prototyping and accurate validation of findings. Despite using simpler hardware, its performance matches resource-intensive methods involving audiovisual and AI techniques. This design’s innovation lies in its fault-tolerant, distributed setup using budget-friendly, low-power devices rather than resource-heavy hardware or methods. Successfully tested at a historical building in Greece (M. Hatzidakis’ residence), it is tailored for indoor spaces. This paper compares its algorithmic application layer with other implementations, highlighting its technical strengths and advantages. Particularly relevant in the wake of the COVID-19 pandemic and general monitoring middleware for indoor locations, this middleware holds promise in tracking visitor counts and overall building occupancy. Full article

It is expected that the number of elected female mayors in local government will increase globally, yet no major progress has been registered lately despite the increased focus on the topic. At the European level, no country exceeds 40% female mayors or other leaders of the municipal council (or equivalent), with the highest descriptive representation of 39.1% in Iceland. Following the 2020 elections in Romania, only around 5% of mayors were female with a strong over-representation of male mayors. The current study aims to analyze the male–female distribution of mayors, the degree of re-election, the relationship between the number of candidates and re-election of incumbents, and how these factors impact female political representation at the local level in Romania. Thus, we argue that a high degree of re-election of incumbents may be a barrier to women’s access to the position of mayor. In addition, it is important to determine whether female incumbents are as successful as their male counterparts in being re-elected. While there is an extensive body of literature on incumbency that covers a range of topics, there is a gap in the literature regarding the proposed subject. The present research aims to fill the gap and contribute to a better understanding of the political representation of women in Eastern Europe. We utilized a dataset of Romanian elections from 2008 to 2020 to test our hypotheses. Our findings indicate that during the studied period, more than 95% of mayors were male, the re-election was a frequent occurrence in Romania with a percentage ranging from 70.82% (2008–2012) to 72% (2012–2016 and 2016–2020), and female incumbents were just as likely to be re-elected as their male counterparts. Full article

In response to the problems of random selection of primary nodes, high communication complexity, and low consensus efficiency in the current consensus mechanism for intellectual property transactions, a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm based on the Affinity-Propagation (AP) clustering algorithm, termed AP-PBFT, is proposed. Firstly, the election strategy of the leader node is constructed based on the reputation mechanism; the reward and punishment mechanism is designed to achieve the dynamic adjustment of the reputation value of the nodes in the PBFT consensus process, and the number of votes among the nodes is introduced to determine the node’s reputation value in collaboration with the reward and punishment mechanism to guarantee the precise ordering of the nodes. Secondly, nodes with high reputation values are selected as cluster centers to run the AP clustering algorithm, and clustering groups of knowledge property transaction nodes are constructed based on responsibility and availability. Finally, the three-stage consensus process of the PBFT consensus algorithm is optimized, and the consensus task is decomposed into two layers: the intra-consensus group and the inter-leader node group, reducing the communication complexity of transaction data in the blockchain. Experimental findings indicate a significant performance improvement of the algorithm over the PBFT consensus algorithm in communication complexity, throughput, and consensus efficiency in the simulation environment of multiple types of transactions in intellectual property transactions, including different types of large-scale transaction scenarios, such as purchases, sales, licenses, and transfers. Full article

City centers and riverfronts across the Atlantic Ocean have undergone substantial transformation over the last two decades. This paper analyzes walk-only precincts and waterfront revitalization in two pairwise cases (PCs) of small city exemplars on two continents in locations at about the same latitude but separated by the Atlantic Ocean. The argument is twofold. First, to be fully effective, city center revitalization interventions need to be coordinated with appropriate institutional programs to create collaborative management opportunities among multiple civic and business agents. Second, multiple cultural offerings, environmental amenities, and pro-active leadership positionalities have contributed positively to the evolution of waterfront community economic redevelopment opportunities in riverfront locations. The methods involved multiple site visits to cities of various sizes on the Iberian Peninsula and the Northeast of the United States at different times during the last twenty years, extensive literature reviews and syntheses, data analyses, assessment of policy priorities, and interviews with employees in various economic sectors, business owners, residents, elected officials, planning professionals, and community leaders. Two of the main conclusions are that, to be fully effective, the public space interventions on the Iberian Peninsula had to be coordinated with appropriate regulatory and institutional programs to generate collaborations with multiple civic and business agents and that the Northeastern cities have attempted to revitalize their riverfronts by conserving water-based and urban historic assets and amenities from further erosion due to downpours and floods as well as socio-economic and cultural transformations. Full article

Today, intelligent drone technology is rapidly expanding, particularly in the defense industry. A swarm of drones can communicate, share data, and make the best decisions on their own. Drone swarms can swiftly and effectively carry out missions like surveillance, reconnaissance, and rescue operations, without exposing military troops to hostile conditions. However, there are still significant problems that need to be resolved. One of them is to protect communications on these systems from threat actors. In this paper, we use blockchain technology as a defense mechanism against such issues. Drones can communicate data safely, without the need for a centralized authority (ground station), when using a blockchain to facilitate communication between them in a leader–follower hierarchy structure. Solidity has been used to create a compact, lightweight, and effective smart contract that automates the process of choosing a position in a certain swarm formation structure. Additionally, a mechanism for electing a new leader is proposed. The effectiveness of the presented model is assessed through a simulation that makes use of a DApp we created and Gazebo software. The purpose of this work is to develop a reliable and secure UAV swarm communication system that will enable widespread global adoption by numerous sectors. Full article

Party leaders are increasingly relevant to voters’ choices in parliamentary systems. However, most studies addressing the electoral impact of leaders have largely ignored voters’ emotional responses to party leaders. Additionally, little is known about the effect of party leaders in subnational or regional elections. Using data from a specific election survey, this article examines the effect of emotions towards party leaders on regional voting. It assesses whether emotional responses to party leaders not only have direct effects, but whether they also have indirect effects through partisanship on voting. We found evidence that emotions towards party leaders have both direct and indirect effects through partisanship on vote choice. Full article

Following the presidential announcement of Zimbabwe’s harmonized 2023 electoral date, most Christian, African Traditional, and other religious leaders commendably resumed advocating for peaceful, free, and fair elections. However, as history usually repeats itself, the tables eventually turned. Some of the leaders regressively became divided, submitted to political infiltration, aligned themselves with oppressive politicians, betrayed their fellow leaders as well as God and humanity, and inadvertently supported totalitarianism. By employing Richard Osmer’s practical theological methodology and engaging with the existing literature, this paper reviewed the (dis)unity and (dis)engagement between Christian and African Traditional Religious (ATR) leaders. It also endeavored to address the underlying (dis)connections in view of Jesus Christ’s all-encompassing servant leadership model, diaconal mission, and the African Ubuntu philosophy. Observing that Zimbabwean religious leaders are retrogressively divided by their varying spiritualities, leadership styles, and political orientations, it is recommended to embrace inclusivity and unity amidst diversity. This can be achieved by resisting selfishness and promoting selflessness, unconditional love, generosity, hospitality, tolerance, peace-making, justice, and social cohesion. These values collectively play a role in the democratization of Zimbabwe and are imperative for its advancement. Full article

This theoretical article argues that megachurches are an inadequately problematised factor in the Zimbabwean crisis and uses, as examples of violent and corrupt megachurch leaders, Emmanuel Makandiwa, Uebert Angel, and Passion Java. As Zimbabwe moves towards elections in 2023, ZANU-PF has resorted to using megachurches to enact propaganda, create voter empathy, and stir up violence, dividing the religious electorate along party lines in the process. The article is couched in decoloniality theory to position megachurch leaders within instability and as thwarting democracy in Zimbabwe. I respond to two questions: how do Makandiwa, Angel, and Java contribute to thwarting democracy while promoting corruption and violence? And, how can religion be approached from the perspective of decolonial thinking to reverse the crisis that has been created by prophets in Zimbabwe? I end by arguing that the Zimbabwean crisis takes various forms and that the role of megachurch leaders in finding a solution and in reconstructing narratives of peace and good governance in Zimbabwe cannot be ignored. Full article

In 2022, two regional elections were held that initiated a new electoral cycle in Spain. The first, in February, took place in Castilla y León where, for the first time, the extreme right-wing party, VOX, formed a coalition in a regional government with the right-wing Partido Popular, while, simultaneously, the extreme left-wing party Podemos was barely left with parliamentary representation. The second, in June in Andalusia, led to VOX increasing its representation by two seats and beginning its national level electoral growth; the far-left that was split in two parties, finding that the dynamic that began in Castilla y León also affected them as they lost 10 representatives. This article seeks to compare the emotional strategies of these extremist parties in the 2022 regional elections, focusing especially on leaders’ and parties’ communication strategies on X, formerly Twitter, during the electoral campaign. We expect to find differences between political parties but also between regions. To test this, we carried out an ‘X account content analysis’. We selected those accounts representing the candidates to the regional President and also the main political party accounts in the regions: namely VOX in both regions, Podemos in Castilla y León, and Adelante Andalucía and Por Andalucía in Andalusia. Full article

The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH’s routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network’s lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique’s throughput and energy efficiency. Full article

Among existing studies on formation reconfiguration for multiple unmanned aerial vehicles (multi-UAVs), the majority are conducted on the assumption that the swarm scale is stationary. In fact, because of emergencies, such as communication malfunctions, physical destruction, and mission alteration, the scale of the multi-UAVs can fluctuate. In these cases, the achievements of formation reconfiguration for fixed-scale multi-UAVs are no longer applicable. As such, in this article, the formation reconfiguration problem of leader–follower multi-UAVs is investigated with a variable swarm scale taken into consideration. First, a streamlined topological structure is designed on the basis of the parity of the vertex numbers. Then, three formation reconfiguration strategies corresponding to the scenarios covering leader disengagement, follower detachment, and new member additions are developed with the aim of reducing the frequency of connection changes. Moreover, in terms of the leader election link of the leader disengagement scenario, a knowledge-based performance assessment model for UAVs is constructed with the help of the hierarchical belief rule base (BRB). Finally, the proposed formation reconfiguration strategies for leader disengagement, new member addition, and follower disengagement are demonstrated through simulations. The connection retention rate (CRR) for swarm communication topology under the three formation reconfiguration strategies can reach 67%, 90%, and 100%, respectively. Full article

Crash fault tolerance describes the capability of a distributed system to maintain its proper function despite the occurrence of crashes or failures in one or more of its components. When a distributed system possesses crash fault tolerance, it can be further fortified to achieve Byzantine fault tolerance. Byzantine fault tolerance empowers a distributed system to establish consensus among participants, even when faced with faulty or malicious behavior. Consensus plays a critical role in various tasks, including determining the accurate value of a shared variable, electing a leader, or validating the integrity of a business transaction. Compared to crash fault tolerance, Byzantine fault tolerance instills greater trust because it enables consensus even in the presence of malicious entities. This paper focuses on the performance evaluation of two blockchain solutions that exhibit Byzantine fault tolerance, in contrast to a blockchain solution that demonstrates crash fault tolerance. Specifically, the paper investigates the additional performance requirements associated with the enhanced trust resulting from Byzantine fault tolerance in e-business trading on both national and transnational scales. We analyze the resources needed to operate a business-to-business/business-to-government (B2B/B2G) compliance framework in two distinct geographic scenarios. The first examines the national scale, using Denmark as an example, which is the eleventh largest European country by GDP. The second scenario considers the scale of the European Union (EU) with its 27 member states (plus the United Kingdom). Full article