This paper offers a multi-dimensional analysis of the ways and extent to whichthe US president and UK prime minister have securitized the Covid-19 pandemic intheir public speeches. This assessment rests on, and illustrates the merits of,both an overdue theoretical consolidation of Securitization Theory’s (ST)conceptualization of securitizing language, and a new methodological blueprintfor the study of ‘securitizing semantic repertoire’. Comparing and contrastingthe two leaders’ respective securitizing semantic repertoires adopted in theearly months of the coronavirus outbreak shows that securitizing language, whilevery limited, has been more intense in the UK, whose repertoire was structuredby a biopolitical imperative to ‘save lives’ in contrast to the US repertoirecentred on the ‘war’ metaphor. In October 2019, exactly 45 days before the first Covid-19 case was detected, theNuclear Threat Initiative and the Johns Hopkins Center for Health Security launcheda brand-new benchmarking effort aiming at assessing health security across the195-state parties to the International Health Regulations. The Global HealthSecurity Index ranked states according to their level of preparedness to deal withserious outbreaks. In this list, the United States of America ranked first, theUnited Kingdom second. Yet, by summer 2020, both countries ranked in the top-10 ofthe states the worst hit by the Covid-19 pandemic. Much of the controversy thatensued centred on whether the two governments had initially downplayed the riskor/and been inconsistent in their decisions – and, crucially, communication – aboutthe pandemic.intensity and way in which the US Presidentand UK Prime Minister have securitized the Covid-19 pandemic intheir public speeches. In other words, how they framed it as an urgent securitythreat requiring extraordinary measures. This assessment rests on, and illustratesthe merits of, an overdue consolidation of ST’s conceptualization of securitizinglanguage, which allows us to compare and contrast the two leaders’ respective‘securitizing semantic repertoires’ – the specific combination of words they adoptedin the first months of the coronavirus outbreak to depict the virus as a securitythreat – and measure the intensity of their securitizing language over time.The present article sheds light on this puzzle, from the specific angle ofSecuritization Theory (ST). More precisely, we offer a multidimensional evaluationof the intensity of securitizing language in both countries wassurprisingly low. We show that while both the US President and UK Prime Minister didsecuritize the Covid-19 pandemic in their public speeches, they did not make anextensive use of securitizing language – with the exception of some noticeable andwidely mediatized spikes. Second, we reveal a paradox: while the intensity of thesecuritizing language has consistently been higher in the UK, it is in the US thatthe discourse of hard security has been more prominent. To investigate this, weundertake a granular analysis of each securitizing semantic repertoire and show thatthis variation is explained by a difference in the way each leadersecuritizes the issue. In particular, we show a variation in the referent object ofJohnson and Trump, that is, what is seen as ‘existentially threatened’ and as having‘a legitimate claim to survival’. Indeed, while the UK’s securitizing repertoire has been systematicallystructured by the biopolitical imperative of ‘saving lives’, the US’ repertoire ischaracterized by the use of the war metaphor. Perhaps counterintuitively, therefore,we show that using the war metaphor does not necessarily mean that the overalldiscourse over an issue will be highly securitized.In doing so, this research uncovers two main findings. First, the On the one hand, as the virus accelerated its propagation in the months ofJanuary–May 2020, almost every single government across the globe took extraordinaryemergency measures of a kind and scope unseen during 20th century peacetime: drasticlockdowns were ordered, massive liquidity was injected in national economies, thearmy was deployed in the streets, borders were closed, etc. On the other hand, thegovernments who deployed these measures were keen to present the disease as asecurity threat to be tackled urgently. To take a few examples, on 16 March 2020,Emmanuel Macron proclaimed France to be ‘at war’, stressing the unprecedented natureof his ‘decisions in time of peace’ and arguing that ‘all these measures arenecessary for our security’. Benjamin Netanyahu announced Israel to be at ‘war with an invisible enemy,the virus’, and Abdullah II claimed – in military uniform – that each Jordanian ‘isa soldier’ in the battle against the epidemic. The Covid-19 case thus appears to closely correspond to the ideal-type ofsecuritization.These findings might come as a surprise since the pandemic seems to present atextbook case of securitization, with extraordinary measures being implemented afterstate leaders pronounced powerful speech acts presenting the disease as afundamental threat. As the canonical formulation indeed goes, securitization happenswhen ‘an issue is presented as an existential threat, requiring emergency measuresand justifying actions outside the normal bounds of political procedure’. the Covid-19 case is an opportune starting point for strengthening ST’saccount of what is arguably its pivotal tenet: the question of what exactlyconstitutes ‘securitizing’ language. Surprisingly indeed, the substance of whatBuzan, Waever and De Wilde initially called the ‘rhetoric of existential threat’, that is, the language used by a securitizing actor to move an issue from‘normal’ politics to the realm of exceptional security politics, has been largelyunderspecified in securitization studies. Building on existing, but partial, attempts to describe the semanticdimension of this language, we suggest a consolidated framework for the study of‘securitizing semantic repertoires’, which comes with a tailored methodology. Thisapproach clarifies what securitizing language is and explains how to systematicallystudy it, paving the way for a finer understanding of the many instances wherepolitical leaders justify extraordinary policies with the rhetoric of securitythreat .The granular unpacking of the various formal dimensions of securitizing languageclears thus the path for a finer understanding of why this type of language is sucha frequent and powerful type of communication.With its seemingly clear-cut sequence of securitization, We detail and justify how we applied our methodology, which enables bothdiachronic and synchronic analyses, to the two cases evoked above: the publicspeeches on Covid-19 of Donald Trump, and Boris Johnson. Third, we present our results and discuss our findings, offering bothimportant insights on the Covid-19 case, and empirical evidence for our theoreticalintervention. By laying bare the semantic markers of what appears to be the mostremarkable instantiation of securitization in recent times, we also enrich theliterature on the securitization of global health.This endeavour proceeds in three steps, which correspond to the three contributionsof the paper . First, we explain why moreprecision is needed in ST’s description of securitizing language, especially itslexical and semantic dimensions, and we consolidate the already-existing concept ofsecuritizing ‘semantic repertoire’ to remedy this problem. Second, we explain themixed-method approach used to analyse these repertoires. The approach consists inthe use of two computer-assisted tools for content analysis (a co-occurrence networkand a dictionary-based measurement), complemented with qualitative readings ofsignificant texts. This combination strengthens and enriches the panel of methodsusually employed to study securitization, and offers a solution to theunderdevelopment of methods in securitization research. Speech acts are indeed the means used by a securitizing actor to convince anaudience of the ‘critical vulnerability of a referent object’, that is, for example,the state, society, an institution or another referent group, ‘by investing thereferent subject with such an aura of unprecedented threatening complexion that acustomized policy must be undertaken immediately to block its development’. The pivotal moment in this securitizing move sequence is the securitizingspeech act. As Williams clearly describes, ‘issues become “securitized”, treated assecurity issues, through these speech acts which do not simply describe an existingsecurity situation, but bring it into being as a security situation by successfullyrepresenting it as such’. The emphasis on one-shot speech acts ‘expresses a more recognizable political investment’ than other ST variants investigating the impact of language games, broadernarratives or discursive environments on security policies. But these other approaches still attribute to words the power of shapingthreat perceptions and security preferences.Language plays a central role in the securitization process conceptualized by theCopenhagen School.semantic dimension of securitizing language, the way wordsconvey the securitizing meaning, has not been conceptualized precisely. In theinitial formulation of ST, Waever claimed that ‘the word “security” is the act’. In their seminal book, Buzan, Waever and De Wilde added that securitizationnecessitated ‘a rhetoric of existential threat’ that is not necessarily ‘defined by uttering the word security’; there are‘instances in which the word security appears without this logic and other casesthat operate according to that logic with only a metaphorical security reference’. Although such an under-specification of securitizing language may well havebeen intentional, probably reflecting the acknowledgement that it varies acrosscontexts, a more in-depth and formal exploration of the potentially recurringfeatures of this rhetoric, what it can look like, what its major lexical markers canbe, was warranted. Surprisingly, such an exploration was yet to be done in asystematic way, contrasting with the kind of work done in other fields of criticalsecurity studies (e.g. constructivist feminism).Yet, in spite of the centrality of language and ST scholars’ in-depth study of theillocutionary and perlocutionary foundations of securitizing speech acts, what thislanguage actually looks like, lexically, remains unspecified. In other words, the three substantial contributions have paved the way for our framework. First,Balzacq acknowledged in his 2005 article that securitizing language wasmultifaceted, chiefly because a securitizing actor can use a series of different‘heuristic artifacts’  to gain traction. Together, these particular formulas constitute a ‘semantic repertoire ofsecurity’ that contains a cultural dimension. In his 2011 volume, Balzacq further highlighted metaphors and underlined theimportance of the ‘semantic regularity’ of ‘repertoires of security’. In the same volume, Vultee’s assimilation of securitizing language to mediaframes paved the way for a more detailed lexical analysis of the words used, more orless strategically, by securitizing actors when constructing an issue as a threat. Second, Klüfers adopted a socio-pragmatist perspective to further defineBalzacq’s ‘repertoires’. Defining acts of securitization as ‘discursive processeswhich evolve through one or more “security repertoires” [. . .which. . .] aresystematically related sets of terms’. He stressed that, instead of a single‘security repertoire’ being common to all cases of securitization, each instance ofsecuritizing language rests on a particular combination of words ‘organized aroundone or more central metaphors’. In line with Klüfers, securitization scholars thus ought to providefine-grained analyses of these specific sets of words that together construct themeaning of threat attached to the referent object. Third, Baele and Sterck arguedthat there is no such thing as a ‘pure’ securitizing language but rather ‘framingnarratives whose securitising intensity may be more or less strong’. Noting that each speech may contain a smaller or greater number of words thatbelong to the semantic field of security , they suggested measuring the saliency of this vocabulary to evaluate theintensity of the linguistic securitizing move. To do so, as explained below, theycreated a ‘Security Lexicon’ (SL) of 222 words unambiguously pertaining to the‘hard’ security lexical field.Our aim here is to offer a more detailed, formal and empirically operationalconceptualization of securitizing language. While quite a few scholars have offereddepictions of this language in action, This framework articulates what we suggest are the five main formal semanticdimensions of securitizing repertoires, based on the above literature as well asinfluential scholarship in the various fields studying language in social action:(1) ‘generic’ versus ‘contingent’ lexicons, (2) stylistic devices, (3) parts ofspeech, (4) associative networks and (5) semantic context. We consolidate the findings of these contributions into a coherent theoreticalframework for the study of securitizing semantic repertoires. Our frameworkconcentrates on one specific step in the securitization process, leaving aside whatcomes before  and after . We do not aim tooffer an overview of the whole process, but rather to clarify as much as possibleits pivotal moment.generic words are those thatdirectly evoke a security threat regardless of the context. On the other hand,securitizing semantic repertoires also contain contingent, lessdirectly and obviously securitizing terms that can nonetheless have asecuritizing effect because of their particular socio-cultural resonance. Forexample, the words ‘powerful chemical agent’ might not be immediately evident,generic securitizing words, but may nonetheless be highly securitizing in aplace such as Salisbury, UK, where Sergei Skripal was poisoned with a nerveagent in 2018. Even generic security words are not universally impactful: theireffect on the audience can vary across socio-cultural settings. In sum, wesuggest that any given securitizing semantic repertoire is a particularcombination of what we call a ‘generic lexicon’ (which corresponds to SL) and a‘contingent lexicon’ (which is particular to each case), each time of varyingproportions. Attuning, for each securitizing speech, to the saliency of genericlexicon, and simultaneously identifying which words constitute the contingentlexicon, provides rich information into the working mechanisms of securitypersuasion.We argue that a securitizing semantic repertoire is neither fully culturallydependent, nor totally universal. Each repertoire contains, on the one hand,some of the ‘hard security’ words making Baele and Sterck’s SL . These metaphors arein the construction of social and political meaning – and this holds true in securitization. As Lakoff summarizes, metaphorsare mental shortcuts, allowing to quickly ‘conceptualize one mental domain interms of another’. In this process, a particular meaning, coming from the root mentaldomain, is attached to a new domain, in such a way that any moral evaluationsand normative preferences pertaining to the root domain is assigned to the newone. Referring to migration as a wave, for example, or terrorism as a cancer,offers simplified understandings of these complex phenomena which imply specificsolutions and trigger particular emotions among the audience. The war metaphor,in particular, has already been identified as a major rhetoric device tosecuritize issues, such as drugs or crime. This is because war metaphors ‘draw on basic and widely shared schematicknowledge that efficiently structures our ability to reason and communicateabout many different types of situations, and reliably express an urgent,negatively valenced emotional tone that captures attention and motivates action’. Not only do war metaphors evoke a sense of fear which ‘can motivatepeople to pay attention, change their beliefs, and take action about importantsocial issues’, they also suggest that the efficient reaction to the issue against whicha ‘war’ is waged is necessarily uncompromising. War metaphors refers to a clearhierarchy of command, action and obedience. They also signal urgency, and therisk of a weak reaction. As such, ‘war’ is not only an unambiguous security word of the genericlexicon, it is also a convenient, and thus prominent, securitizing metaphor.Securitizing repertoires typically contain, and are usually organized around,stylistic devices like metaphors, historical analogies or personification. Eachplays a particular role in the rhetorical process, and serves as anchor toeither the contingent or generic repertoires. First, research in linguistics andsocial cognition consistently shows how important historical analogies are a recurring component of politicaldecision-making and discourse, which can play a significant role in securitizing semantic repertoires.They confer meaning to a new situation by transposing a simplifiedinterpretation of a past event onto a current one, and are thus important in twoways when it comes to securitization. Firstly, by invoking collective memory,they have the potential to bring together the community as an in-group beingthreatened by the referent object. Secondly, analogies serve not only adiagnostic function (explaining what is happening), but also a prescriptive andmoral function . For example, by claiming that a given issue creates ‘a new Verdun’, aFrench official is immediately understood by his/her audience as portraying thatissue as an attack of extreme violence that necessitates all forces of thenation to be redirected towards that single focal point. A British leaderreferring to the Blitz would suggest similar meaning and solutions. These twoexamples incidentally show the importance of the contingent lexicon insecuritization: culturally resonant words not belonging to the generic securitylexicon (e.g. ‘Verdun’) can be used to amplify or dramatize securitizing speechacts.Second, besides metaphors, with which they share the same comparative structure,personification is another recurring stylistic device inpolitical rhetoric, notably in its visual expressions, that can be used to enhance asecuritizing move in two different ways. One possibility is to assign humancharacteristics and agency to an abstract and non-agential threat, which makesit more tangible to the audience. The other possibility is to personify thegroup threatened by the issue, which can reinforce a sense of common, threatenedidentity among the audience, as well as conveniently locate the blame into astereotypical ‘other’. Nazi propagandists were, for instance, very prolix usersof personification, which at times morphed into animalization when it came totheir enemies.Third, We suggest that stylistic devices such as metaphors, historical analogies andpersonification cannot be ignored by securitization scholars who wish tounderstand why particular securitizing speech acts are used or gaintraction.Adverbs and adjectives do not belong tothe generic security lexicon, yet they can decisively strengthen securitizingsemantic repertoires by reinforcing the sense of urgency and threat, and byenhancing the impression that extraordinary measures need to be taken. A speechthat makes a repeated use of adverbs like ‘absolutely’, ‘uncompromisingly’ or‘urgently’, and adjectives like ‘life-threatening’, ‘dangerous’ or‘unprecedented’, conveys a more powerfully securitizing meaning than one thatdoes not. Adjectives help depict and specify the nature of the situation bycharacterizing protagonists and actions in ways that can construct very specificthreatening pictures. For example, characterizing the securitizing subject as‘vicious’ will entail different perceptions among the audience than depicting itas ‘brutal’. Verbs that denote a swift action, such as ‘react’,‘counter-attack’ or ‘move’, reinforce the urge to securitize more thannon-action verbs such as ‘ponder’, ‘consider’ or ‘collaborate’; their use istherefore more likely in securitizing semantic repertoires. Finally,pronouns also are of utmost importance in conveyingemotions and sense of belonging in speech. The use of ‘we’ by political leaders is particularly significant as itperformatively creates a sense of common in-group identity. In contrast,employing ‘they’ can conglomerate non-members into a single out-group.Words play a role in securitizing language without necessarily setting up astylistic device or evoking security. Indeed, attuning to the specific roles ofthe different ‘parts of speech’  is crucial inunderstanding the semantic dimension of securitizing repertoires, as indeed anypolitical statement.In sum, attuning to the frequency and positioning of parts of speech is key, notonly to evaluating the power of securitizing repertoires, but also toidentifying the particular securitizing objects and subjects they construct. The regular co-occurrence of a set of words in a series of messagesprimes the audience to understand these concepts as linked, and provides thebasic structure of the meaning of a situation or issue. For example, thesystematic co-occurrence of the word ‘mosque’ with concepts like ‘attack’,‘terrorist’ and ‘war’ in white supremacist blogs discussing the Ground Zeromosque initiative built an understanding of the project as a fundamentalsecurity threat, an interpretation that permeated mainstream media and public opinion. Similarly, the relentless association by Salafi-jihadist propagandists ofthe out-group labels ‘Crusader’ and ‘Americans’ with descriptions of childrenkilled by airstrikes creates an image of an exceptionally cruel enemyconsistently harming the most vulnerable of their in-group. Securitizationscholars thus ought to attune not only to lexical units of analysis but also tohow they are connected together to create the particular meaning of an issuethrough priming – and thus imply a particular desired response. In that way, important insights can be gained regarding the particularways securitizing speech acts construct the threat: what is/are the threatenedobjects, what constitutes the broader logic and domain of the threat , andmuch more.The presence of stylistic devices and parts of speech is not enough to convey asecuritizing message. Rather, it is the relationship between these units, howthey are organized together to convey meaning, that truly constitutessecuritizing semantic repertoires. As Kunda and other cognitive scientistsemphasize, the meaning of a message results from its ‘interconceptorganization’, in other words, from the ‘associative network’ whereby conceptscomposing the message take their meaning from the other concepts that accompany them. This is because, as soon as another repertoire is used, the overallmeaning of the speech starts to be determined by a wider associative network ofconcepts. In other words, what matters is not just if, but how much,proportionally, ‘security words’ are uttered, and how they build, withcoexisting repertoires, a more or less threatening picture of a situation.Finally, securitizing semantic repertoires rarely occur in isolation from otherrepertoires. Securitizing repertoires generally co-exist within a givenspeech/text with non-securitizing language, which can have implications for howthe message is understood and interpreted by the audience: indeed diluting asecuritizing repertoire within a long intervention blending other repertoirescould carry less weight than entirely containing the allocution within theboundaries of the securitizing repertoire.The five dimensions are schematically represented together in To study securitizing semantic repertoires, we suggest a methodology based on thecombination of two existing computational tools for the study of textual content –dictionary-based approaches and co-occurrence networks – together with a closequalitative reading of particular interventions identified as important by thequantitative inquiry. Dictionary-based approaches and co-occurrence networks areclosely related (they both compute word frequencies) but each captures differentdimensions of semantic repertoires. They therefore answer different questions andshould be combined to offer a granular analysis. In particular, it rests on the conviction that quantitative content analysiscan powerfully complement the qualitative techniques usually employed bysecuritization scholars. More specifically, it follows calls to ‘diversify [ST’s]methodological toolbox’ towards quantitative methods. The present effort thus stands in line with previous contributions thatsuccessfully combined computational content analysis and critical discourse analysis, diversifying the existing effort to fruitfully deploy multi-method designs insecuritization research  in order to address securitization research’s ‘bias in favour of high-leveltheorizing and evaluative procedures at the detriment of empirics-driven knowledgerelying on constructive procedures’.This mixed-methods approach embraces the practice of ‘triangulation’ in security studies.generic lexicon of the securitizing semantic repertoire.Dictionary-based approaches are commonly used to calculate the weight of a givenlist of theoretically significant words in a corpus. Dictionaries have beenbuilt to measure the emotional tone of authoritarian leaders’ speeches, the saliency of racial slurs in texts, or variations in terrorist ideologies over time, among others. As noted above, a dictionary evaluating the intensity ofsecuritizing language already exists: Baele and Sterck’s Security Lexicon (SL)has been developed to ‘measure the saliency within texts of the security“semantic regularity”’, whereby ‘the more a political actor makes use of wordstaken out of this set, the more his or her narrative establishes a securitising move’.The first step is to use a dictionary measuring the intensity of the to calculate the ratio of the words making the SL out of the total numberof words for each one of the 126 segments constituting our corpus (see below). This allows us to compare variations of this ratio in each one of thesesegments. In doing so, we follow Smith, Stohl and al-Gharbi’s demonstration thatthe SL is best used diachronically to reveal shifts in the intensity ofsecuritizing language over time. Measuring the saliency of generic security words in such a wayimportantly approximates the strength of the securitizing speech act  andprovides a clear indication as to whether or not securitization is a sporadiclinguistic practice or a sustained one.We use the Linguistic Inquiry and Word Count (LIWC)This first step thus serves three goals: to gain a general overview of theintensity of the generic lexicon in our securitizing semantic repertoires, totrace the evolution of this lexicon across time, and to identify textswarranting further qualitative analysis.contingent lexicon escapes the SL, which cannotcapture non-generic elements constituting the securitizing semantic repertoires.Furthermore, the SL does not reveal important parts of speech or stylisticdevices, nor does it highlight the repertoire’s associative network or exposeits semantic context. The second step of our method secures these three jobssimultaneously.By design, the  or political ‘narratives’ and ‘discourses’. They have recently been used to reveal dominant frames of health issues and to offer sharp comparative evidence of the differentiated framing ofan epidemic outbreak (the 2015 measles epidemic) by internet users in two countries.We use co-occurrence networks (semantic networks) to visualize a givenrepertoire’s most prominent terms and their relationships. Not yet used insecuritization studies, this tool is a particularly powerful addition to ST’smethodological toolbox. Semantic networks, which are based on co-occurrencematrix tables, carry out two tasks simultaneously and allow for an intuitivevisualization of both tasks’ results: they represent, in a single graph, themost frequent words of a corpus and show how often they are associated insentences or paragraphs. Co-occurrence networks are therefore built to identify‘policy frames’associativenetworks within a corpus, revealing a corpus’s most frequent termsin a way that allows for a qualitative analysis of parts ofspeech and stylistic devices. Clusters offrequently co-occurring words appear that approximate the presence ofnon-securitizing repertoires around the securitizing one(s), that is, thesemantic context of the repertoire. To sum up, applyingco-occurrence networks to securitizing speech displays not only the genericlexicon, common to most cases of securitization, but also the specific lexicon,particular to each case, as well as the meaning-giving relationships thatconnect the words of both lexicons.In co-occurrence networks, each word is represented as a node whose size variesproportionally to frequency. The links between nodes represent theirco-occurrence, with their thickness symbolizing the probability of theco-occurrence, and their length the average distance between the words.Co-occurrence networks therefore directly display the For a given corpus, an option is to ‘seed’ a co-occurrence network, that is, tobuild a more focused network that displays the terms with the highestprobability to be co-occurring with a certain word or set of words deemedtheoretically important (the ‘seeded’ words). This technique allows a moregranular visualization of the lexical field surrounding the seeded words, whichis useful when one wants to zoom in on a particular object evoked in the corpus.Working on a corpus of ISIS propaganda magazines, researchers have for examplegenerated a seeded network focusing on the word ‘West’ that allowed them todemonstrate how the organization frames the West as a decadent and aggressive ‘non-civilization’. The networks include the top 150 edges between these words, a numberfound, after attempts with lower and higher numbers, to correspond to the ‘sweetspot’ between the amount of information provided and the readability of thegraph.For the present inquiry, we built two seeded networks – one for the US, one forthe UK – visualizing the terms that have the highest probability to beco-occurring with the words ‘coronavirus’, ‘covid’ or ‘virus’ in the same paragraph. ‘coronavirus’, ‘covid*’) made by US President Donald Trump and UK PrimeMinister Boris Johnson. These two states were selected because, while neitherinitially opted for a clear securitization  of the disease, both changed their rhetoric at one point and implemented extraordinarymeasures. The rationale for selecting these otherwise different cases is thus tomaximize the chance of detecting and visualizing these changes in therepertoires. The US and the UK also constitute seemingly anomalous cases: whilethe two countries were the best prepared to tackle a pandemic, with 535 and 610 deaths per million inhabitants respectively (as per 20August 2020) they both rank in the top-10 of worst-hit countries in the world atthe time of writing. While we neither examine here the policies taken or not bythe Trump and Johnson administrations, nor establish a causal chain fromsecuritizing language to these policies, our analysis nonetheless provides afirst step towards understanding this puzzle.To study the securitizing semantic repertoires of Covid-19, we compiled astructured corpus made of all recorded public statements mentioning the pandemic  without the PrimeMinister being present himself. As we will see, this is partially reflected inthe securitizing repertoire. Second, Covid speeches in the UK followed astandardized format that left little room for improvization, or for discussingother political issues, whereas the US president’s interventions lacked arecurring structure. This means that some of the US president’s interventionswere very long and other extremely short, with longer speeches regularlyoccurring during questions time and frequently veering off-course on othertopics. This results in the US section of the corpus being much longer than theUK one, as shown by  Analyses of official communications during the previous pandemics indeedrevealed how different political/social actors put forward differing discursive practices. Our aim here is not to open the lens to encompass what Chong and Druckmancall the ‘competitive elite environment’ of framing, but rather to narrow the focal point to the central, most importantrepertoire defining the political game.It should be noted that the following analysis limits its ambition to theofficial securitizing semantic repertoires of Trump and Johnson. As scholarssuch as Stritzel and Chang have rightly shown, official securitizing speech actsand practices are always parts of ‘prolonged political game[s] of moves andcountermoves marked by securitizing and counter-securitizing speech acts’.We discuss our results in two main sections corresponding to the computational toolsdescribed above, with the qualitative analysis of relevant segments directlyembedded in the presentation. Overall, we make two main observations. First, theintensity of securitizing language has generally been low in both the UK and the US,yet with several spikes evidencing particularly important securitizing speech acts.Second, and even though the UK corpus displays a higher saliency of the genericsecurity lexicon, the classical war metaphor is more prevalent in the US corpus. TheUK, by contrast, has used a very specific contingent securitizing repertoirearticulating a different logic than the one implied by the war metaphor: thebiopolitical imperative to ‘save lives’. This has been done in a systematic andsustained way, whereas the use of the war metaphor in the US has been sporadic anddiluted in a disordered semantic repertoire.Our dictionary-based analysis of the two corpora reveals three main results see below. FSecond, while these ratios undoubtedly denote the presence of securitizinglanguage, they are surprisingly low in absolute terms. Indeed, previous uses ofthe SL show, on the one hand, that ‘fully securitized’ texts, such as EUdirectives directly dedicated to so-called ‘hard’ security matters, obtainscores around 5. On the other hand, a very large random corpus received a scoreof 1.26.These findings indicate that there has not been a strong and sustainedsecuritization of the pandemic by the UK and US heads of government, at leastthrough the use of the hard security words included in the generic lexicon. Theabsence of high and sustained levels of securitizing language, which would havereflected a stronger and less ambiguous stance on the virus, might constitute asmall but non-negligible part of the answer to the puzzle of the two states’poor performance in limiting fatalities.Third, the analysis shows the presence of sharp ‘spikes’, that is, particularspeeches that contain a higher-than-normal ratio of words from the genericsecurity lexicon. Such an observation is important as it potentially revealsunique speeches that may correspond to the kind of clear securitizing speechacts initially envisioned by the Copenhagen School.Today, I have issued an order under the Defense Production Act to morefully ensure that domestic manufacturers can produce ventilators neededto save American lives. My order to the Secretary of Health and HumanServices and the Secretary of Homeland Security will help domesticmanufacturers like General Electric, Hill-Rom, Medtronic, ResMed, RoyalPhilips, and Vyaire Medical secure the supplies they need to buildventilators needed to defeat the virus. I am grateful to these and otherdomestic manufacturers for ramping up their production of ventilatorsduring this difficult time. Today’s order will save lives by removingobstacles in the supply chain that threaten the rapid production ofventilators.A qualitative examination of these specific speeches is therefore warranted. TheUS corpus has a generally low SL but displays a single spike at 3.54 – more thanthree times its average. This spike matches a statement given by Donald Trump on2 April 2020, where he announced an executive order to bring production ofmedical supplies within the realm of the Defense Production Act. We transcribethe speech in extenso below: So even though the speech uses securitizing language to acknowledgeparticular possibilities opened by the DPA, the speeches and actions thatfollowed fell back to the initial line of very limited securitization.This speech has three major features that make it a clear securitizing move inthe sense found in the original ST literature. First, Trump’s use of genericsecurity words is high . Second, the speech is very short andstraightforward, with no other issues discussed. In other words, the semanticcontext is empty, giving the impression of a sharp and important statement.Together, these first two features explain the high SL score . This is an interesting insight, which wouldrequire further investigation: the relative strength of a securitizingrepertoire is higher when the repertoire is isolated than when a comparablerepertoire co-exists alongside other repertoires in longer speeches. Third, thisspeech does in fact operationalize an extraordinary measure through executiveaction: the nationalization of economic production is a decision that stands outof normal politics, even more so in the US. In this regard, this is a typicalexample of a securitizing move in the original acceptation of the term by theCopenhagen School. Yet at the same time, attuning to the context and processesleading up to this speech helps us understand why it is at odds with theremainder of the corpus: while clearly securitizing, this statement was mostlymade by Trump in reply to mounting pressures to do so, and was not followed bythorough measures based on the DPA .Unlike the US corpus, the UK corpus has four spikes. The first spike correspondsto Boris Johnson’s pivotal speech on 17 March, which matches the implementationof lockdown. In this speech, Johnson makes a heavy use of the generic securitylexicon, with words like ‘dangerous’, ‘overwhelm’, ‘war’ or ‘enemy’ pointing toa classic use of the war metaphor. ‘We must act like any wartime government’,Johnson proclaimed, with ‘a sense of urgency’. The historical analogy with WorldWar II is used to allow the audience to instantly appraise the seriousness ofthe crisis, and the necessity of the extraordinary measures to come. Johnsonuses many parts of speeches that do not appear in the generic dictionary butthat further accentuate his securitizing move: adjectives such as ‘drastic’,‘deadly’, ‘extreme’, ‘fast’, ‘severe’ or ‘unprecedented’; adverbs such as‘quickly’; nouns like ‘fight’ or ‘crisis’; and verbs like ‘beat’ or ‘shielding’.All these parts of speech reinforce the sense of urgency and threat. Crucially,this speech corresponds, like Trump’s 2 April speech, to the arrival of whatJohnson himself call ‘extreme measures’, which unambiguously belong to the realmof extraordinary politics. It therefore represents a clear case of asecuritizing speech act as originally conceptualized by the Copenhagen School,and further demonstrates the usefulness of the SL to spot such language.Yet the three other spikes in the UK corpus do not match with speeches of similarrhetoric. This is explained by the fact that, on 11 and 15 April 2020, PritiPatel delivered the speeches, in lieu of Johnson (see above): as Secretary ofState for the Home Department, her addresses had a strong emphasis onCovid-related criminality. The 5 May 2020 speech, delivered by Secretary ofState for Foreign and Commonwealth Affairs Dominic Raab, contained a series ofstatements related to UK-US collaboration on cyber-attacks that drove the SLhigher. While making use of many generic security words, these are notsecuritizing speech acts.the – key speech in each corpus, with the qualitativeanalysis showing that both speeches clearly match the sort of securitizingspeech act originally conceptualized by the Copenhagen School and make use ofwhat has been presented as the main metaphor of securitizing repertoires: war.However, as explained earlier, this approach is only an evaluation of thegeneric lexicon; it ignores the more contingent language participating tosecuritization. And it also brought about a puzzle: why is there such adifference in the SL ratio, with UK scores consistently higher than US scores?The second step of our analysis turns to the contingent lexicon and explainsthis puzzle.In sum, the SL dictionary proved a powerful tool in three ways. First, itdemonstrated that the intensity of generic securitizing language wassurprisingly low. Second, it showed that the UK scores were significantly higherthan those of the US. Third, it successfully identified a – perhapshow the virus is portrayed in both countries. In otherwords, it allows us to detect and visualize the different repertoires used tosecuritize it. referent object, that is, what is being threatened andneeds protection, is the state.Generating seeded co-occurrence networks allows for a granular analysis ofexactly  The US historical references are also made in reference to an enemy,which is blamed for the situation: China. This is consistent with Buzan, Waeverand De Wilde’s intuition that ‘whatever is presented as the cause of securityproblems is most likely also actorized’. As it goes in the theory, the source of the threat is presented as anagent who made a choice that led to the untoward situation:This is really the worst attack we’ve ever had. This is worse than PearlHarbor. This is worse than the World Trade Center. There’s never been anattack like this. And it should have never happened. It could have beenstopped at the source. It could have been stopped in China. It shouldhave been stopped right at the source, and it wasn’t. [. . .] I view theinvisible enemy as a war. I don’t like how it got here because it couldhave been stopped. But, no, I view the invisible enemy like a war. Hey,it’s killed more people than Pearl Harbor, and it’s killed more peoplethan the World Trade Center. World Trade Center was close to 3,000.Well, we’re going to beat that by many times, unfortunately. So, yeah.This — we view it as a war. This is a mobilization against a war. It’s a— in many ways, it’s a tougher enemy. (6 May 2020)A qualitative reading of the texts containing the word ‘war’ shows that the USpresident used two historical analogies several times to add resonance to thewar metaphor: Pearl Harbor and 9/11. These analogies lead the audience to readthe Covid-19 crisis as a surprise attack on American soil that requires a rapidand uncompromising reaction. This use of the war metaphor as a structuringstylistic device parallels the militaristic tone of Israeli and Jordanianleaders highlighted by Hoffman, with the Israeli Defence Minister linking the‘First Corona War’ to the ‘previous Israeli wars’ and the Jordanian KingAbdullah II evoking, while wearing a military uniform, the 1968 War of Attritionand battle of Karameh.Second, it is striking to note that the US securitizing repertoire is merely oneamong several others, less (or even non-) securitizing repertoires. Two clustersshow the importance of a medico-scientific discourse centred chiefly ontherapies and treatments , but also economicconsiderations . In addition, a lot of un-thematic, some might evensay ‘empty’, talks took place, which is evidenced by the biggest purple group ofwords on the right .Such a large amount of unspecified language when talking about the virus,together with the coexistence of several non-securitizing repertoires, had, weargue, a major effect: it significantly diluted the securitizing language withina mass of talk which was either non-securitizing or ‘empty’.In sum, the co-occurrence network analysis of the US corpus does reveal thepresence of a securitizing semantic repertoire centred on the war metaphor andarticulating a series of powerfully securitizing historical analogies. However,it shows simultaneously that this repertoire is diluted alongside other less (ornon-) securitizing repertoires and a large amount of un-thematic talk.Turning to the UK corpus, life and death. The repertoire therefore comescloser to Huysmans’s understanding of security as ‘a strategy constituting andmediating our relation to death’. Words like ‘die’, ‘fatality’ or ‘life’ are among the most likely toco-occur in a paragraph discussing the virus, and have an obvious securitizingpotential. While some of these terms, chiefly ‘protect’, actually belong to thegeneric dictionary, and explain the consistently high UK score, most do not, andthus constitute a contingent securitizing semantic repertoire, which articulatesa biopolitical logic. This logic rests on the diffusion and internalization of norms ofself-care and well-being as well as on the sacralization of life, rather than onhard security measures necessarily involving heavy sacrifices and life loss.Biopower, as Foucault summarized, is a ‘technology of power which takes life asboth its object and its objective, [. . .] its basic function is to improvelife, to prolong its duration, to improve its chances, to avoid accidents, andto compensate for failings’.The network clearly shows the coherence of the semantic repertoire used by the UKleaders: in contrast to the US network, all clusters link scientific-medicalterms, with no other issue raised when discussing the virus, and little emptytalk. UK officials focus on the pandemic figures  andpeople admitted to hospitals , the government’s action plan toslow the spread of the epidemic and thereby reduce the strain on the NHS  and the efforts to prevent deaths from a second peak .This is where the specificity of the UK’s securitizing repertoire lies: ratherthan resting on a classic, hard security lexicon centred on the war metaphor andrelated stylistic figures and parts of speech, it uses a range of securitizingterms related to  we observe here that, unlike the US, the UK has centred its speech aboutthe virus on the biopolitical necessity to ‘save lives’. This tendency, whichbecame fully dominant after the UK government read a model predicting 260,000 deaths, is encapsulated in the last tenet of the constantly repeated and ‘too successful’ triad ‘Stay Home, Protect the NHS, Save Lives’. To translate this in theterms of ST, the referent object of the UK securitizing move onCovid-19 is not the state – like with the war metaphor – but the individual andthe institution that protects his or her life, the NHS.Echoing Elbe’s assimilation of the securitization of HIV/AIDS to biopower, With biopolitical risk, policy decisions differ from those taken bygovernments that adopt a more disciplinary stance, as the aim shifts from‘waging war from the defence of the sovereign to securing the existence of a population’. The onus is on citizens to ‘become an active partner in the drive forhealth, accepting their responsibility for securing their own well-being,[. . .] the health-related aspirations and conduct of individuals is governed“at a distance”, by shaping the ways they understand and enact their own freedom’. Predictive surveillance and monitoring systems to which citizensthemselves subscribe and share their data are the typical policy of such a logicof government. This UK stance is not unprecedented. Indeed, the biopoliticalapproach to pandemics has already been noticed in the cases of H1N1 and HIV/AIDS.The UK securitizing repertoire constitutes the epitome of what Rose coined ‘riskpolitics’, that is, a particular accentuation of biopolitics that has developedin advanced liberal societies, whereby political strategies aimed at maximizinglife rest on ‘calculations about probable futures in the present, followed byinterventions into the present in order to control that potential future’.This is where the semantic difference between the US and UK repertoires reallymatters. On the one hand, Trump developed a hard security frame constructing thepandemic as a warlike attack justifying a retaliatory action against an outsideenemy, a top-down hierarchy, and disciplinary measures, with more considerationto sacrifice in order to save the US referent object, the state, than to thepreservation of life. This stands in line with the US president’s usual emphasison law and order, and hard borders, but also with a pre-election context pushinghim to deflect the blame on others, chiefly China. On the other hand, the UKgovernment adopted a biopolitical framing urging individuals to participate inthe maximization of life. Johnson used the war metaphor in what was arguably his strongest speech,while Trump did discuss fatality rates. It remains, though, that our analysisreveals how both states relied on noticeably different securitizing semanticrepertoires.Both repertoires are securitizing, and have been used to move the pandemic out ofthe realm of ordinary politics, but their underpinning logic, consequences andreferent objects are different. Of course, as Knauft warned the two logics arenever purely at play in contemporary societies, but rather always enmeshed intonew power-knowledge nexuses.intensity and way in which Donald Trump andBoris Johnson have securitized the virus in their public speeches.In this paper, we strengthened Securitization Theory’s conceptualization of itspivotal component, securitizing language, by putting forward a consolidated theoryof securitizing semantic repertoires. We suggested a multi-dimensional model andused this framework to study the securitization of Covid-19 in the US and the UKduring the initial period of the pandemic: from January (for the US) and March 2020(for the UK) until May 2020. This focus allows us to shed light on the controversycentred on whether the two governments, who ranked as first and second states thebest prepared to deal with a major outbreak, had initially downplayed the risk ofthe disease. Accordingly, we did not aim to offer an overview of the wholesecuritization process, but rather to clarify as much as possible the pivotal momentwhen a securitizing actor (the head of state) frames an object (Covid-19) as anexistential threat requiring the implementation of extraordinary measures in orderto protect a referent object. Thanks to a combination of dictionary-based andco-occurrence analyses reinforced by qualitative checks – a combination which, webelieve, has the potential to solve some of the methodological shortcomings ofsecuritization research – our multidimensional theory allowed us to evaluate boththe intensity, we found, first, that the UK corpusdisplayed a higher saliency of the generic lexicon compared to the US, and that thistendency was consistent over time. Second, and despite this observation, we showedthat neither leader has opted in favour of a strong and sustained securitization ofthe disease, the ratio of their securitizing language remaining relatively low.Despite this low intensity, our analysis allowed us to spot several spikesevidencing particularly significant securitizing speech acts. Third, we conducted aqualitative analysis to investigate these particular speeches and found out thatthey tended to correspond to the arrival of extreme measures to deal with thethreat; thereby showing the effectiveness of our model in identifying these keymoments. Our US data also indicated that the relative strength of a securitizingrepertoire is higher when the repertoire is isolated, like with Trump’s 2 Aprilstatement, compared to when the same repertoire co-exists alongside otherrepertoires in longer speeches.With regard to the way both leaders have securitized Covid-19 in their publicspeeches. In particular, we found out that the securitizing repertoire mobilized byeach leader was framed around the protection of a different referent object. On theUS side, we first revealed the presence of a securitizing semantic repertoire makinguse of the war metaphor and articulating a series of powerfully securitizinghistorical analogies, as well as the identification of China as the bearer of blamefor the situation. This latter finding, in particular in a pre-election context,suggests an interesting link between securitization and blame avoidance behavioursthat ought to be further investigated. Second, while the presence of this ‘hardsecurity’ repertoire was undeniable in the US, it was diluted alongside other less(or non-) securitizing repertoires, and a large amount of un-thematic talk, whichlinks back to, and explains, the low intensity of the US securitizing language. Onthe UK side, we identified what could be called a ‘biopolitical repertoire’, centredon the preservation of life. Accordingly, to go back to ST, while the referentobject in the US repertoire seems to be the state under attack, the referent objectin the UK repertoire is the individual and the institution that protects its life,the NHS. Finally, unlike the US corpus, this repertoire is not scattered and dilutedbut exists in an orderly and structured manner in the speeches of Johnson and UKcabinet members.Our seeded co-occurrence analysis shows significant variation in theAltogether, these findings lead us to the compelling observation that otherrepertoires than those centred on ‘hard security’ war metaphor can be used tosecuritize an issue. In our comparison, the biopolitical repertoire of the UK evenscores higher on a generic measurement of securitizing language than the US warrepertoire.Theoreticallyspeaking, a case like the Covid-19 pandemic seems to bring back withforce the initial formulation of ST by the Copenhagen School, with its emphasis onwell-delineated speech acts followed by extraordinary measures. This does not mean,however, that other approaches to securitization are wrong, but rather than ST isbest understood as a plural framework containing several lenses, each one of them best suited to explain andinterpret a specific case. Empirically speaking, further researchshould widen the empirical universe covered here. Other cases, for example includingcountries that notoriously resisted the language of war and security, like Sweden orNew Zealand, would need to be examined in order to fine-tune the theory ofsecuritizing repertoires. An analysis of the ‘visual repertoire’ of Covid-19 couldalso be carried out, investigating how pictures of biosuits, extenuated doctors andnurses, and other prominent visual tropes connect with securitizing language. An evaluation of the actual impact of various securitizing repertoires ondifferent audiences, as well as the tracing of the dissemination and modificationsof these repertoires when echoed by the press or social media, could be undertaken.Relatedly, and as acknowledged, the question of the relationship betweensecuritizing repertoires and the policies adopted is voluntarily left unexploredhere, as we primarily sought to strengthen the theory’s take on language, but couldbecome the focus of future research.In spite of these clear findings, our intervention does not close the debate on thelanguage of securitization or the Covid-19 case.


Based on the combination of quaternion numbers, residual matrices, and chaotic attractors, a new cryptosystem is proposed for multimedia processing files such as images and audio. The key employed in this encryption schema consists of an image with a wide and sensitive range, obtained from the Julia Quaternion set rendered using a computational tool. Due to the use of quaternion matrices mixing the information between RGB layers and audio samples was possible, whereas using XOR operation and residual matrices modulus 257, added high sensitivity to small perturbations during encryption, key preparation and decryption processes, to such an extent that a minimal change in the image or in the audio leads to a totally different encryption result. The use of dynamic programming also reduced the processing time for matrix operations on the  During recent times consumption of multimedia on Internet has increased drastically, COVID-19 pandemic has also contributed in this sense, reason why the scientific community continues developing mathematical and engineering strategies that lead to cryptographic solutions each time more secure and efficient. In the current work, quaternions, chaotic attractors and modular arithmetic are employed in order to design a cryptographic scheme focused on multimedia files (audio and images).The increase in information volume exchange through public channels has raised the need to protect data confidentiality. The ever-increasing flux of multimedia files on the Internet has been reported by FileCatalyst (a firm responsible for providing software services to speed up and optimize the transmission of multimedia files), showing the range of sizes for different types of multimedia files in 2020. This data is consolidated in Table The Canadian company Sandvine, specialized in providing solutions for network policies and control of landline and mobile communications services, with emphasis on cyber security, in its annual report, shows that multimedia consumption all over the world had reached almost 45% in 2018 and 60% in 2020, so therefore it is necessary to strengthen encryption schemes for multimedia files by providing academic solutions that are applicable to the industry .Growing concern for the protection of information led to traditional encryption schemes such as Advanced Encryption Standard (AES) and Data Encryption Standard (DES) emerged, however, due to limitations such as the handling of high-volume information, low levels of entropy and the high correlation of data, these traditional algorithms are less suitable for multimedia encryption , 27. TheQuaternion numbers have a non-commutative ring structure, which makes them useful in cryptography and image processing, since RGB channels are handled jointly by each quaternion component and rotations require less computational processing compared to their vectorial counterpart.These numbers have been use in the last decade as a language in a variety of cryptography applications such as security schemes for multimedia files, key generation, public key algorithms, digital signatures, and hashing. Some related works are described below.In , 17, an A meaningful work in the medical sector was proposed in , the autHowever, authors subsequently identified a weaknesses in their original proposal, that led them to design an encryption model with similar characteristics at  trying tMoreover, chaos properties are very useful in cryptographic systems because its applications comprehend from key generation and system synchronization schemas to pseudo-random number generation algorithms.There are also works focused on application of logical operations such as XOR to provide new security layers based on pseudo-random number generators (PRNG); such is the case of , in whicIn , a LorenLikewise in , they usIn this direction, proposals presented by  and 27]27] on whFor example, works proposed in , 55, 56 Moreover, although in , 29, 32 Another interesting concept that has been applied in cryptography and science is the use of residual classes, leading among other things to formalization of residual matrix theory, such concept originated with the proposal of Rabin’s asymmetric cryptosystem, and has evolved thanks to the introduction of the latest generation of computers. At  they sugBased on related works as well as on approaches found in , 14–17, An advantage of this paper lies in the use of a quaternion matrix to perform simultaneous operations between RGB layers and audio samples which are handled through the quaternion real component, decreasing the processing of diffusion and permutation operations as they are performed using parallel computing.When images are generated from chaotic systems with 3 or more dimensions, a huge number of possibilities are added to guarantee the uniqueness of each image, such as its initial conditions (sensitivity), cutting planes, iterations (periodicity), texture material of the chaotic system, colors, patterns, objects in space, their physical properties  and how they interact, all of these guarantee a large and secure key space.If an equally unique sequence of pseudo-random numbers can be created from each unique rendered image that is sensitive to even the smallest bit change, then it will serve as a key in a cryptosystem. In this proposal, the key image is obtained from Julia’s quaternion set whereby its dynamic nature constitutes an advantage in key’s security.On the other hand, modular inverse 257 is employed because adding the unity to all RGB values in each component results in a range between , thus guaranteeing the uniqueness of modular inverse, this fact is exploited in order to increase pixel’s sensitivity and ensure that the slightest change in key image generates a different bit-stream. Additionally, the algorithm is designed in such way that every key’s pixel is relevant to the whole encryption process.In order to safely manipulate multimedia information of this proposal, the encryption mechanism handles quaternion matrix multiplication with integer entries, and also relies in modulus 257 residual classes calculations through parallel processing and dynamic programming, simplifying the computational cost which is an advantage related to computational complexity.The necessary concepts are explained in Section The cryptosystem proposed in this paper involves two main components, encryption algorithm and key generation. The theoretical basis for the proposed algorithm is described below.H is defined by three imaginary units i,j,k; a Quaternion q has a form as shown in ; a and v are named real and vectorial part of Quaternion respectively. If the real part of Quaternion is zero, the resulting number is known as a pure Quaternion.The Quaternion number set shown in :1\documH, addition and multiplication operations are defined and fulfill the structure of a non-commutative division ring  [On Quaternion set of this) .x,y,m positive integers, x is congruent with y module m  if m dim if and only if they are in the same family, they are known as residual classes module m, and they are designated by m residual classes module m, and that This notion satisfies the properties of an equivalence relation, which eases the grouping of integers in disjunct families given the fact that two positive integers are congruent module for them .Residual classes have also brought up the need to solve congruential equations from the simplest ones like those of linear and quadratic type, to simultaneous congruence systems. This is where the Chinese Theorem of the remainder proposed by mathematician Sun Tzu comes into place as a powerful tool to find solutions for linear congruence systems which is also applied for solving polynomial congruencies for composite modules.Theory of residual classes has been widely applied into cryptography mainly to reduce the number of operations through congruencies when dealing with excessively long values, as a consequence it results into a decrease of computational speed, making room for cryptographic model proposals based on them and the notion of residual and inverse matrices.strange attractor, as explained in dynamical systems literature. The chaotic behavior of such systems is an advantage in order to propose key generation schemes using Quaternions. Such proposal is possible due to the similarity between chaotic dynamical systems properties and permutation/diffusion features for cryptographic systems.The chaotic dynamical system definition adopted in this document was proposed in 1948 by Robert Devaney . Chaos if(z) = z2 + c over the Quaternion set, which results into the Julia Quaternion set (in honor of mathematician Gaston Julia), where c is an arbitrary parameter. Figure An example of a chaotic system can be seen by iterating the quadratic function This paper proposes an encryption system for the processing of multimedia files based on Quaternion numbers set, Julia Quaternion chaotic attractor, and residual matrices. Figure c in f(z) function, number of iterations, the cutting plane, the camera location, as well as visual parameters like lighting, rendering texture, image background, among others.The key generated was obtained from Julia Quaternion set on which a 4-dimensional fractal is yield and intercepted by a cutting plane in order to retrieve a f(z) = z2 + c was used with c and z both being Quaternions. The cutting plane is denoted as pc and the number of iterations corresponds to n. Four RGB vectors were used for color depth. The radial frequency is denoted as Fr and the size of the multimedia object to be encrypted is specified in all cases. An example of a key obtained from PovRay is shown in Fig. In this paper, function ki, where i refers to the required key generation parameters to be sent.In this paper, the cryptosystem implemented 9 independent sub-keys in order to send all the necessary key parameters. Each parameter uses a different key denoted by c; cutting plane pc; random generated Quaternions that are associated to the RGB color percentage for background texture RGB1, RGB2, RGB3 and RGB4; Quaternion p, which is the combination of the radial frequency Fr, number of iterations, n and two M, N values corresponding to the image height and width; Quaternion t which is composed from the audio sample, frequency as for framerates and snake algorithm displacement snk; and finally a Quaternion s, which corresponds to the CSPRNG seed. The key is then obtained from , , 9), whiij with i = 1,...,nj = 1,...,m at layers R, G, B, respectively.Decompose the key image into its RGB components A having all of its entries equal to one in order to suppress possible zero values that may exist and interfere with the modular operation of next step thus obtaining Add matrix D = (dij) which is obtained by applying operation mod 257 to the product of each component in Qc1 at ij position, in other words Define matrix Qc1 noted by Calculate the (mod 257) modular inverses for each RGB layer entries present in matrix mentclasspt{minimaQc2||) mod 257 = 0 as a consequence of adding the value dij, zeros are removed from matrix Qc2, applying function at , in this case a = 0, subsequently the original image matrix is masked by a quaterion matrix with random integer entries Qm obtained from a CSPRNG instantiated by seed s specified at , which consists in the XOR operation application between vector’s adjacent quaternions, starting from snk vector position according to . If there is only an audio sample to be processed, an arbitrary white noise image is used in order to implement the same mask and snake process carried out for images.esent at , the 32-For video: A combination of the previous cases is applied. However, to ensure synchronization, audio component is divided into small samples according to the number of frames per second.Depending on multimedia type, one of the following processes is carried out: Q3.Up to this step multimedia information has been hidden in quaternion matrix Q3 and two invertible residual square matrices M, N with m and n sizes respectively in Using matrix ribed at  is applid mod 257 being different than zero.The main purpose for calculations to happen in qij4 present at   specificm blocks out of n bits [This test consists of 15 different statistical measures that evaluate the chaotic bit-stream sequence on a statistical level, P-values establish whether a sequence pass the tests successfully or not, for this, such value must be greater than 0.01 at each one of the tests applied on f n bits .5 bits, results presented at Table NIST tests on this work were performed with the “sts-2_1_2” Suite, by using as input file four-component data blocks corresponding to each quaternion matrix entry specified at , the libDistribution frequency histograms were plotted for each one of the RGB layers and audio channel in Fig. χ2 test was used in order to establish the pixels distribution uniformity in encrypted image, a small value of this indicator means high pixel uniformity, which is desirable into a cryptographic process. The expression for this test is given by , D(x), D(y) are given by  an ancov is the mean given by , C2 are two encrypted images, the first one corresponds to original image and the second one to the same image with one altered pixel; M and N correspond to image’s size.Where A and L corresponds to audio vector length.Where %, 33.46% and 100%, 33.3% [Results obtained are presented in Tables %, 33.3% , 54.TabValues obtained in this paper are similar to those of other references presented in Table EQ), where oi(P) and oi(C) correspond to the number of pixel with i intensity in original and encrypted images respectively.This type of analysis measures the difference between repetition frequency for each pixel value of plaintext and encrypted image, expression given in  describeN,M the image’s width and height.According to reference  the maxiTable RGB1 vector and constant c of f(z) function. In both scenarios using such non-significant variations, decryption of original information was unsuccessful. Results obtained are shown in Figs. − 11 ≈ 2− 33, result being useful for key space calculation in next section.In order to evaluate the key sensitivity in proposed cryptosystem, elements used in Fig. As it can be seen on results obtained, knowing even one of the parameters isn’t enough to decipher the original multimedia file, therefore it is possible to assure that the proposed system is resistant to brute-force attacks. In addition to that, a small variation in any of key parameters, causes totally different results. This was experimentally corroborated by calculating the correlation between two key images with insignificant changes in their parameters, obtaining an average correlation of 0.0153, which implies that even if the algorithm is known, but there is no certainty about all parameters used in the encryption process, it is impossible to recover the original information.snk shift and the different parameters involved in key generation such as c, pc  the mi probability of occurrence [An entropy value means the level of resistance to statistical attacks as well as the randomness level of encrypted information, this value is calculated using , where Mcurrence . In the currence , 54.34\Values obtained in this proposal for image layers and audio channels are close to 8, showing that ciphered information has a high confusion level and are very similar to results found on different references, indicating a high disorder degree. Results are presented in Table Sometimes Shannon entropy is not a reliable indicator of randomness level, for this reason it is necessary to calculate different local entropies that reflect a more accurate randomness level of pixels .N finite blocks number ml, l = 1,...,N choosen randomly to calculate the corresponding entropy value, then the average Shannon entropies are calculated and synthesized in expression Local Shannon entropy takes a H(ml) is given by  is zero, because the two images are identical, therefore PSNR has a tendency to infinity, indicating that during the decryption process there are no alterations in original information.Peak signal-to-noise ratio (PSNR) is a measure that indicates the noise that can be added in a decryption process, a larger value in this indicator evidences a lower noise proportion in the recovered information. Equation Also Figs. Four common cipher attack types are Ciphertext-Only, known-plaintext, chosen-ciphertext and chosen-plaintext, with chosen-plaintext being the most effective one. According to , a systeNM, residual matrix product 128 bits.Furthermore, proposed algorithm also features brute force attack resistance because key is an image generated from 360 bits according to Section O(n2), nevertheless as information increases, time increases proportionally to matrix size.Computational complexity of an algorithm refers to the time measurement an algorithm execution takes with respect to data size, which is an indicator of the algorithm’s efficiency and represents its computational boundary. In this article using the computer described in Section An encryption method applied to multimedia files was proposed based on the properties of chaotic attractors in a 3D space, using an image generated from the Julia Quatertion attractor as a key ensuring with this a wide space and sensibility.Quaternion numbers were used to take cryptographic advantage of various properties such as the non-commutative product, which avoids typical issues with traditional encryption schemes such as the discrete logarithm problem and faster calculation for rotation operations. Also using this set of numbers made it possible to design an integrated structure for audio and images, ensuring that a variation in any part of the process produces changes in the whole information.Using the congruence theory properties and modulus 257 residual matrices, it was achieved that small changes in pixels generate totally different keys increasing its sensibility. In addition, the use of residual matrices made it possible to take advantage of their inverse and non-commutational product, making it easier to include the modified information within the Combination of quaternions and residual matrices in this proposal contributed, firstly, by adding a highly sensitive, fast and nonlinear layer, which led to find safety and performance indicators comparable with similar works, this allows application of the proposed method in real world environments. On the other hand, computation time was reduced by the usage of dynamic programming and existence of an unique inverse element in Aiming at improving results of this proposal, future work should explore the use of other security layers, chaotic images and attractors along with its behavior on 3D environments in order to improve the algorithm and its security, especially as it related to salt & pepper and occlusion tests. In the same way the proposed algorithm could be implemented using parallel programming reducing its computational requirements.


Dear Editor,We have read the very recent case report of Zamani et al. entitled “Intraocular lymphoma masquerading as unilateral hypopyon anterior uveitis: a case report” published in the Journal of Ophthalmic Inflammation and Infection in 2022 . The autThe case of the authors is most timely for the differential diagnosis of “hypopyon” and “pseudohypopyon”, particularly for a prompt diagnosis of tumoral masquerading syndromes. However, we have a few observations on the anterior chamber precipitation and suggestions to make it a remarkable read for the assistance of oncologists and ophthalmologists interested in ocular complications of lymphoma or leukemia. Indeed, Fig. First, the shape of the uveitic collections in the anterior chamber is pathognomonic, which results in horizontally layered white meniscus formation typically heaped up centrally rather than at its edges. The ocular presentation of the woman in Fig. Second, Fig. Third, the differential diagnosis between “hypopyon” and “pseudohypopyon” is very important for clinicians since their managements and prognoses are entirely different [within seconds upon head-tilting or leaning to one side, which is a pathognomonic observation called “shifting/mobile pseudohypopyon”. So, if the authors had changed the position of the woman to one side, they would possibly have encountered the shifting feature of the collection. On the other hand, hypopyon from uveitic etiologies has “non-shifting” characteristics, which are totally immobile, possibly like in Fig. ifferent . Indeed,ifferent . ActuallFinally, the color of the anterior chamber sediment can direct oncologists and ophthalmologists to a certain etiology [etiology . Zamani etiology . Howeveretiology . TherefoTaken together, if anterior chamber collections are examined with their full characteristics  and perilimbal status, oncologists and ophthalmologists can diagnose (or exclude) intraocular lymphoma (or leukemia) on time and direct such patients to the proper physician for prompt therapy.


Efforts to contain the COVID-19 virus resulted in various stay-at-home orders and school closures around the globe, causing unprecedented disruption to the lives of children and generating grave concern for their well-being. This study draws on phone interviews with 12 teachers and 6 school leaders from 13 government schools in New South Wales, Australia, to provide insight into how students fared on their return to school after the first wave of COVID-19 in 2020. The interviews highlighted negative consequences for many students including increased stress and anxiety and decreased engagement. This evidence suggests that even a comparatively short period of school closure can drive troubling changes in students’ well-being and behaviour following their return to school. Given far more challenging conditions arising from the pandemic, both elsewhere in Australia and globally, we argue that attending to student well-being is as important as ensuring academic achievement and must be a key focus of policy makers and education systems moving forward. The COVID-19 pandemic has disrupted schooling and the lives of students on an unprecedented scale. To help contain the virus, governments around the world have periodically closed entire schooling systems, ordering parents to keep their children home, where possible, during periods of high virus transmission. These mandates have affected more than 90% of the global student population, disrupting the lives of more than 1.5 billion students in 2020 alone . As a result, students in NSW experienced comparatively shorter lockdowns than those internationally, particularly during the first year of the pandemic  were invited to take part in an alternative project examining the effects of COVID-19 on student achievement  examining the effects of Quality Teaching Rounds professional development on student achievement and the quality of teaching, which had to be postponed . Rather than waste the baseline data collected in early 2020 (prior to the pandemic), teachers and school leaders in participating schools  that takes into account physical, mental, emotional, and social aspects of health as well as individuals’ capacity to achieve balance between facing challenges and having the resources needed to meet those challenges  and school leaders (n = 6) from NSW government primary (elementary) schools (n = 13) was invited to participate in telephone interviews during September and October 2020 (Term 3 of a four-term school year). In Australia, the school year commences in late January and concludes in mid-December.A sub-sample of teachers (Teachers in this study were working with Year 3 and 4 students (aged 8–10 years) while school leaders brought a school wide perspective from their entire student cohort . Teachers have long been valued as informants on the experiences of students in general . All interviews lasted between 30 min and one hour.n = 4) and outer regional (n = 3) areas and in major cities (n = 6) .The school Index of Community Socio-Educational Advantage (ICSEA) ranged from 810 (least advantaged school) to 1141 (most advantaged). The percentage of students with a language background other than English (LBOTE) ranged from 0% Schools 2 and 4) to 98% (School 5). Aboriginal and Torres Strait Islander student enrolment ranged from 1% in School 5 to 61% in School 1. The number of classroom teachers in schools ranged from 3 (School 4) to 41 (School 13) and student enrolments ranged from 29 (School 4) to 777 (School 13) The rapid move to learning at home caused significant stress, frustration, and anxiety for families, as one teacher explains:The problem is some of the kids got frustrated. … was getting frustrated because his mum wouldn’t log in and help him and she said, “Oh, I can’t do this”… Then we had other [students] who couldn’t [connect online] because they were out on farms and the Internet connection they had was so poor, it would drop out… and then they’d be frustrated because they’d spend the rest of their time trying to get back in and they couldn’t. …So, it was a bit of a debacle. As Jessica points out, learning from home added multiple layers of frustration—student frustration with parents, parent frustration with technology, and shared frustration with schooling at home.The unanticipated move to relying on new forms of technology caused further discontent for some students, and a sense of failure and disempowerment for many parents. This was particularly the case in regional areas, where access to the Internet was an ongoing challenge. Jessica, who teaches in a low ICSEA school, captures the multiple frustrations experienced by her students:[In] KindergartenKelly is clearly concerned that the loss of those activities associated with major transition points in schooling  will have lasting negative effects on students.Other teachers, such as Kelly, highlighted the disruption to schooling-as-usual caused by placing key rituals and celebrations on indefinite hold, even when students returned to school.sort of like Groundhog Day, day-in, day-out’ :I’ve mentioned previously, we had a lot of extracurricular programs—they’ve all been stopped. So there’s nothing for the kids to look forward to. …Our [student] school leaders have had no reason to be publicly speaking or no reason to hold any events because you’re not allowed to hold any events. Teachers not being able to have their buddy classes going because you can’t mix stages [year groups]. So, there’s not much for the kids to look forward to. As a school leader with responsibility for ensuring the well-being of students in her school, Kylie paints a bleak picture associated with shutting down extracurricular life—leaving students with little to look forward to.While such curricular curtailment may help students catch up in specific key learning areas, such as the high stakes numeracy and literacy, the lack of extracurricular activities led to what one school leader described as ‘that didn’t take off and have a life of its own. And we were very, very concerned about the impact on the welfare and well-being of our families, that there may have been some… racism is probably not the right word, but some over-concern, some misguided concern. There was an enormous amount of angst here at the very beginning…both within our Chinese community and our non-Chinese community, that we might have been an at-risk school [of spreading the virus]…I think one of the primary things we had to do was make sure that Although such circumstances were reported by participants from all schools, the upheaval to schooling varied based on the specific location and student population. School leader Rachel points to the vexing impact of anti-Chinese racism in Australia, fuelled by political commentary, such as that provided by US President Trump, who repeatedly called COVID-19 the “Chinese virus” Tan, . The impWe had a lot of families just go, “I’m sending my kids” and I think it was due to our geographic location of going, “there’s no COVID around, I feel safe, they’re going to school.” So, sort of from I think it was about Week 2 in Term 2 when we were sort of open for essential workers, the moment that that occurred we had 75% of our kids on site at least four days a week. While there is little doubt that the pandemic caused considerable upheaval to schooling, the commentary provided by Rachel and James indicates how factors such as race and geography contributed to greatly varying experiences for students during the first wave of the COVID-19 pandemic in NSW.At the same time as schools like Rachel’s grappled with the destabilising effects of anti-Chinese sentiment, others in regional areas where there were no reported COVID-19 cases, felt relatively safe. In some instances, students were back at school long before the formal end to the school lockdown period:In sum, the first round of school closures in 2020 caused a major upheaval to schooling which included rapid adaptation to new forms of learning, loss of key milestones, and once they returned to school, a significantly reduced curriculum. Next, we turn to how teachers and school leaders understood the impact of these changes on student well-being.“trends around student stress” , another reported “more aggressive behaviours” , and a third observed “self-harm and threatening self-harm” among her student population . Here, Chris articulates how COVID-19 seemed to compound pre-existing behavioural issues:I had a lot more behaviour issues creeping up, and I’ve got students with anxiety. I’ve got students that are medicated. I’ve got students with learning needs…And I think all of it’s just being genuinely compounded by the stresses and pressures and the general not knowing what it’s going to look like… I would say, there’s a lot more anxiety. There were students [who are now] probably a bit less confident, which is probably a result of anxiety. I think that there was just generally worse behaviour when they came back. Almost all teachers and school leaders in our sample had significant concerns for the well-being of students after they returned to school, manifest in increased anxiety and aggression in the classroom, poor social interaction, decreased engagement, and a range of day-to-day behavioural issues. One school leader indicated she was seeing couldn’t talk or interact with their peers anymore, like they’d lost it” . Samantha, a classroom teacher from a low ICSEA school, concurred:I think it has really impacted them socially more than anything, and how they are engaging and relating to others. I feel that… the students are getting quite fatigued… they seem to be a bit more tired, not engaging as much, lots of behaviour issues, and stuff like that. While great concern has been expressed about the effect of lockdowns on student academic achievement, this teacher commentary highlights the less publicised impact of a lack of social interaction, resulting in high levels of fatigue, increases in challenging behaviour, and a lowered capacity to engage in learning once students returned to the classroom.Teachers also reported poor social interaction among students on return to school, which they attributed to the lack of direct contact with peers during lockdown. One teacher went so far as to say that students “mental well-being:So, students who didn’t engage during distance learning, have continued with a high level of difficulty re-engaging back in the classroom. So, yes, my staff has seen that COVID-19 has had a major impact on the mental well-being of the students who feel that they’re unable to keep up. … They just don’t try anymore. Teachers, such as Mateo, concurred:Such commentary highlights how unsettled students were as they returned to school.“diminished well-being” across schools as children returned to classrooms , there was some variability. In particular, regional and remote areas appeared relatively protected by fewer COVID-19 cases in their communities. School leader, James, who was located in an outer regional community, testifies to the experience of students in rural communities:I think probably the impacts for our students, I don’t believe they would have been as severe as someone from a city area as such. Like we had a lot of farming kids who were like ‘okay I’m just helping around the farm’… It was entirely okay, it’s a different learning yes, but they were connecting with their mum and dad, they were connecting with people that they don’t always get to connect with. Yet, despite consistent accounts of In sum, while teachers overwhelmingly expressed concern about student well-being and reported increased stress and anxiety, poor social interaction, and decreased student engagement on return to school, it is worth noting that the impact on student well-being was not uniform. This is to be expected given differing circumstances in schools and families, differing challenges faced, and differing capacities for and ways of responding to the pressures.Given international evidence that the well-being of young people and children is especially vulnerable to the effects of crises OECD, , it is uAs we have documented, during the learning from home period, teachers and school leaders reported that student well-being was substantially impacted by high levels of anxiety in the broader community and within households  in a state where there is a workforce of more than 30,000 primary school teachers. Even with this small sample, we have captured considerable diversity of experience and uncovered deeply worrying consequences of the school closure period.Two key limitations of our study must be acknowledged. First, we are reporting on a single eight-week lockdown in one Australian state where the impact of the pandemic  was much less severe than in other locations. Our participants came from widely diverse schools that are broadly representative of the schools in our larger sample. But we conducted a relatively small number of interviews  and the added risk of exacerbating the considerable angst community members were already feeling due to conditions created by the pandemic.Given school closures in many parts of the world, concern for both student learning and student well-being has been profound throughout the COVID-19 pandemic. Substantial research has been conducted on student learning, with most studies reporting negative effects, particularly for younger children and those from low socio-economic backgrounds  indicating the pandemic negatively affected their mental health (Mission Australia,