1,721,113 research outputs found
The AstraZeneca affair. How the junk news regime affected the public debate on the COVID-19 vaccination controversy in Italy
Full text linkIn recent years, there has been a notable increase in the presence of techno-scientific issues within public discourse, particularly during the COVID-19 pandemic. This proliferation has been attributed to the pervasive attention economy, which drives actors in hybrid media ecosystems to seek attention-grabbing topics. Socio-technical issues, known to evoke strong emotions like outrage and rivalry, have become recurring themes in both news and social media discussions. However, the regulatory mechanisms of the attention economy often impede the full exploration of these controversies in the public sphere, as news cycles and audience attention accelerate due to the prioritization of engaging content on social media platforms. This trend towards attention-driven content has compelled news organizations to adapt their business models, resulting in an environment where citizens may rely on confirmation bias, ultimately leading to polarization of public opinion. Consequently, effectively addressing controversies in today’s public debate has become increasingly challenging. To understand the extent of influence exerted by junk news – a transient form of content that distracts rather than nourishes public discourse – we conducted a case study focused on the controversy surrounding the adverse and lethal side effects of the AstraZeneca COVID-19 vaccine during the vaccination campaign in Italy. Our analysis, based on a comprehensive dataset of 798,954 tweets and 31,169 news articles spanning a six-month period, reveals three interconnected information disorders. Firstly, the vaccine debate displayed a relatively stagnant progression punctuated by sporadic spikes of attention. Secondly, the peaks of the debate involved sensationalized coverage in journalism and amplified discussions on Twitter, primarily centred around suspected vaccine-related deaths. Lastly, reports of these deaths by legacy media accounts on Twitter correlated with an increasing ideological and partisan reaction from social media users over time, contributing to polarization. These findings shed light on how the junk news regime can impede the shaping of public debates, particularly on contentious socio-technical issues such as vaccination campaigns. The implications of this research extend to the broader understanding of public engagement with science and the challenges posed by attention-driven media ecosystems
The use of artificial intelligence in counter-disinformation: a world wide (web) mapping
Full text linkDisinformation has recently become a subject of widespread concerns across the globe. To combat this issue, various initiatives have emerged, aimed at identifying, tracking, and debunking disinformation. Artificial intelligence (AI) has been incorporated as a tool to counter disinformation, but its implementation has not always been successful and may even be counterproductive. Thus, there is a growing recognition of the need for benchmarking the various ongoing efforts to ensure greater efficacy and coordination in the use of AI and assure that this does not lead to forms of algorithmic censorship. Our goal is to provide a mapping of the projects that use AI to counter disinformation by means of their hyperlink network analysis to shed light on their aims, approaches, and challenges
The link between reported cases of COVID-19 and the Infodemic Risk Index: A worldwide perspective
Full text linkIn this brief report we followed the evolution of the COVID-19 Infodemic Risk Index during 2020 and clarified its connection with the epidemic waves, focusing specifically on their co-evolution in Europe, South America, and South-eastern Asia. Using 640 million tweets collected by the Infodemic Observatory and the open access dataset published by Our World in Data regarding COVID-19 worldwide reported cases, we analyze the COVID-19 infodemic vs. pandemic co-evolution from January 2020 to December 2020. We find that a characteristic pattern emerges at the global scale: a decrease in misinformation on Twitter as the number of COVID-19 confirmed cases increases. Similar local variations highlight how this pattern could be influenced both by the strong content moderation policy enforced by Twitter after the first pandemic wave and by the phenomenon of selective exposure that drives users to pick the most visible and reliable news sources available
A new approach for performance assessment of parallel and non-bottleneck machines in a dynamic job shop environment
No full texturpose: The current study aims to propose a new analytical approach by considering energy consumption (EC), maximum tardiness and completion time as the primary objective functions to assess the performance of parallel, non-bottleneck and multitasking machines operating in dynamic job shops. Design/methodology/approach: An analytical and iterative method is presented to optimize a novel dynamic job shop under technical constraints. The machine’s performance is analyzed by considering the setup energy. An optimization model from initial processing until scheduling and planning is proposed, and data sets consisting of design parameters are fed into the model. Findings: Significant variations of EC and tardiness are observed. The minimum EC was calculated to be 141.5 hp.s when the defined decision variables were constantly increasing. Analysis of the optimum completion time has shown that among all studied methods, first come first served (FCFS), earliest due date (EDD) and shortest processing time (SPT) have resulted in the least completion time with a value of 20 s. Originality/value: Considerable amount of energy can be dissipated when parallel, non-bottleneck and multitasking machines operate in lower-power modes. Additionally, in a dynamic job shop, adjusting the trend and arrangement of decision variables plays a crucial role in enhancing the system’s reliability. Such issues have never caught the attention of scientists for addressing the aforementioned problems. Therefore, with these underlying goals, this paper presents a new approach for evaluating and optimizing the system’s performance, considering different objective functions and technical constraints
Absenteeism and turnover as motivation factors for segmenting assembly lines
Full text linkMany assembly lines for complex products are divided into segments (zones and sections), each with its own manager. While zones are usually large and derived from the nature of the process, the segmentation into smaller sections is less obvious. This paper explores the relationship between the effects of absenteeism and turnover (requiring a slowdown because of the substitute workers' learning period) and the segments length. The paper analyses and discusses the effect of dissecting the assembly line into sections in curbing the slowdowns due to absenteeism and turnover in large assembly lines. Quantitative model is developed to represent this factor, and bounds are found for the sections length. An important implication of dividing several hundred stations into small sections is that each section can be efficiently designed and balanced independently, making the optimization complexity irrelevant
Digitization of assembly line for complex products - The digital nursery of workpiece digital twins
Full text linkDuring the last decade the use of digital twins has been spreading to various complex systems, such as assembly lines, and complex products such as aircraft, drones, satellites, vehicles and machinery. This paper discusses the considerations related to the interaction between the assembly-line digital twin and the digital twins of the evolving complex products (workpieces). The paper proposes hierarchical framework including the assembly-line digital twin at the top, that employs the workstation digital twins which are temporarily connected to their current workpiece digital twins. The result is a system that can accurately and efficiently synchronize these simultaneous digital twins. A shared data structure is proposed to facilitate the control and tracking of the assembly progress of each workpiece. This data structure is carried with the workpiece and is shared with the current station digital twin and if necessary the line digital twin
Assembly kits with variable part physical attributes: warehouse layout design and assignment procedure
No full textPurpose: The kitting feeding policy creates kits with the parts of each product to assemble. Each kit contains elements with heterogeneous physical properties imposing heterogeneous logistic facilities and management solutions for storage and handling. The purpose of this paper is to present and apply a two-step procedure to design the part warehouse layout and to assign locations in case of kitting with high-variety part attributes. The proposed procedure aims at reducing the kitting travelled distance, shortening the picker paths, best positioning the components in the warehouse to enhance the possibility of creating kits through a single corridor access. The saturation of the warehouse and the minimization of the required storage space are also considered. Design/methodology/approach: Starting from part categorization, the proposed two-step procedure, of general applicability, designs the component warehouse, sizing the corridors (Step 1) before clustering the kits in terms of part commonality and best-assigning clusters to corridors (Step 2) with the goal of reducing the travelled distance and saturating the available storage space. Findings: A comparison model considers the traditional versus the proposed warehouse layout highlighting the potential saving in the picker travelled distance. A case study taken from the harvesting machine agricultural sector exemplifies the applicability and the practical implications of this research. Originality/value: Elements of originality are the warehouse design strategy and the assignment model for parts based on their physical attributes and their occurrence in the assembly kits. Finally, the case study taken from industry, with a high number of components and part categories, adds value to the research making the proposed procedure able to address large-scale industrial problems
“Station-Sequence” parts feeding in mixed models assembly: Impact of variations and industry 4.0 possible solutions
Full text linkAbstract: Parts feeding is a complex logistic problem, stressed by the increasing product variety that
forces the assembly systems to manage a great number of models with a mixed model approach. In this
context a possible parts feeding policy is the “station-sequence”, sequences of parts supplied to the
assembly stations as function of the production models. This parts feeding policy can reduce stocks at the
assembly stations, but offers potential production stops due to its low robustness. Different external
elements can perturb the parts sequences (i.e. changing in production schedule, tasks times variation,
variable supply lead times, etc.). The aim of this paper is to study, through a simulation study and a
statistical analysis, the station-sequence part feeding policy considering its dynamic time-dependence the
impact of the model mix and time perturbations on the system performance. Authors discuss the possible
application of the real time events traceability, achievable through the I4.0 application, in order to
mitigate the variability influence on the system performances
Techno-economic modelling, analysis and simulation of a water distribution system integrated with pump and autoclave components
No full textWater distribution networks (WDNs), have a complex structure. Their least-cost design and simulation is therefore crucial to convey adequate quantities of water from sources to consumers using the most efficient way. The current research attempts to present an original approach to perform the technical and economic evaluation of a WDN integrated with an autoclave system. For this purpose, a mathematical modelling method is employed to investigate the techno-economic viability of the simulated water system under the effect of the system's design variables. The autoclave's minimum and maximum pressure values as well as the pump flow capacity rates are considered as the free variables of the system and then entered into the proposed analytical model. Afterwards, a tradeoff analysis among the primary components of the system, i.e., pump and autoclave cost has been performed. In the next step, an evaluation on the cost of energy was also carried out to demonstrate the cost variations according to the different pressure values. Results are indicative of the significant changes in the total system cost under the effect of the design variables. In the last stage of this paper, a sensitivity and graphical analysis of the decision variables was also performed to define the input parameters, thus determining the optimum maximum pressure of the autoclave system by which the total cost of the water system is minimized. The technical variables such as the autoclave volume and pump differential head were also investigated during the performed analysis
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