Kinds Of Disruptions Research Articles

Machine Learning for Accurate Prediction of Cardiac Arrhythmia

Cardiac Arrhythmia is a state within the heart that is caused due to irregular waveforms generated from sinoatrial node. Around 17.3 million people die due o cardiac arrhythmia as indicated by World Health Organization (WHO), the kind of disruptions that is caused by sinoatrial is easily captured in Electrocardiography (ECG) readings; it records in all the disruptions and makes a record in form of images, waveforms, numerical data and categorical data. The noisy data’s collected during a patient examination is recorded in form of a special character to prompt the missing data. With different set of distinct patients having different classes of arrhythmia the ECG easily records in all the arrhythmia class as Y dependent variable’s that is used to pass the collected data from the ECG to the proposed system in the research study, which give’s in an architectural model for detecting arrhythmia with considering a combination of Machine Learning Techniques. Random Forest is mainly used in for feature extraction for the dataset that is trained and tested followed by passing the updated dataset to a combination of different Machine Learning Techniques in order to provide accurate training and testing accuracy results from the dataset received. The use of the proposed model is in hospitals that have huge amount of dataset, with recursive training and testing of the model with the right Machine Learning Algorithm for huge amount of dataset it yields results fast in a short span of time, that can help save several life forms in a very short period of time.

COVID-19 War, Human Microbiota Function

COVID-19 War, Human Microbiota Function

A new robust possibilistic programming model for reliable supply chain network design: A case study of lead-acid battery supply chain

Nowadays, the importance of caring about tremendous undesirable economical and technological effects of disruptions has impelled many researchers to design reliable supply chain networks. Moreover, the issue of intrinsic imprecision of input parameters should be gingerly regarded in the design of supply chain networks because it could have inverse impact on the quality of long-term planning decisions. Consequently, to handle the noted problems, in this paper, a reliable closed-loop supply chain network is formulated in which a new reliability method is introduced. The proposed formulation can effectively enable the design of a reliable network under different kinds of disruptions besides seeking for minimum overall costs of network design. On the one hand, a new effectual robust possibilistic programming (RPP) model is developed to confront with business-as-usual uncertainty in input parameters. Lastly, a real industrial case study is employed to validate the utility and practicability of the rendered model as well as presenting the efficiency and felicity of the developed RPP model.

Towards a data-driven predictive-reactive production scheduling approach based on inventory availability

To survive in a competitive business environment, manufacturing systems require the proper deployment of advanced technologies coming from Industry 4.0. These technologies allow access to quasi-real-time data that provide a continuously updated picture of the production system, including the state of available inventory. Data-driven predictive-reactive production scheduling has the potential to support the anticipation and prompt reaction to overcome different kinds of disruptions that occur in production execution nowadays. This research paper aims to propose a conceptual model for a data-driven predictive-reactive production scheduling approach combining machine learning and simulation-based optimization, considering current inventory of raw material, work in process and final products inventory to characterize a job-shop production execution state. The approach supports decision-making in dynamic situations related to inventory availability that can affect production schedules.

Digital Market Perfection

Google’s, Apple’s, and other companies’ automated assistants are increasingly serving as personal shoppers. These digital intermediaries will save us time by purchasing grocery items, transferring bank accounts, and subscribing to cable. The literature has only begun to hint at the paradigm shift needed to navigate the legal risks and rewards of this coming era of automated commerce. This Article begins to fill that gap by surveying legal battles related to contract exit, data access, and deception that will determine the extent to which automated assistants are able to help consumers to search and switch, potentially bringing tremendous societal benefits. Whereas observers have largely focused on protecting consumers and sellers from digital intermediaries’ market power, sellers like Amazon, Comcast, and Wells Fargo can also harm consumers by obstructing automated assistants. Advancing consumer welfare in the automated era requires not just consumer protection, but digital intermediary protection. The Article also shows the unpredictable side of eliminating switching costs. If digital assistants become pervasive, they could gain the ability to rapidly direct millions of consumers to new purchases whenever a lower price or new innovation becomes available. Significantly accelerated consumer switching—what I call hyperswitching—does not inevitably harm society. But in the extreme it could make some large markets more volatile, raising unemployment costs or financial stability concerns as more firms fail. This new kind of disruption could pose challenges for commercial and banking regulators akin to those familiar to securities regulators, who deploy idiosyncratic tools such as a pause button for the stock market. Even if sellers prevent extreme hyperswitching, managers may strategically prepare for hyperswitching with economically costly behavior such as hoarding liquid assets or forming conglomerates to provide insurance against a sudden exodus of customers. The transaction-cost-focused literature has missed macro-level drawbacks. The regulatory architecture reflects these scholarly gaps. One set of agencies regulates automated assistants for consumer protection and antitrust violations but does not go beyond those microeconomic inquiries. Nor do they prioritize strengthening digital intermediaries. Regulators with more macroeconomic missions lack jurisdiction over automated assistants. The intellectual framework and regulatory architecture should expand to encompass both the upsides and downsides of digital consumer sovereignty.

Molecular oxidative stress markers in olive ridley turtles (Lepidochelys olivacea) and their relation to metal concentrations in wild populations.

Due to their longevity and extensive migration areas, marine turtles are able to accumulate diverse contaminants over many years and as a consequence they represent an interesting bioindicator species for marine ecosystem pollution. Metals provoke toxicological effects in many aquatic animal species, but marine turtles have been under-investigated in this area. Thus, we have determined the presence of certain inorganic elements (As, Cd, Cu, Ni, Pb, Se and Zn) in olive ridley turtles (Lepidochelys olivacea) and related them to metallothionein (MT), superoxide dismutase (SOD), catalase (CAT) and glutathione reductase (GR) transcription and/or enzymatic activities. Gene expression of sod, cat and gr was found to be higher in blood than liver or kidney but most of the significant relationships were found in liver, not only for gene expression but also for enzyme activities. This must be related to the role the liver has as the first filter organ. Several positive relationships of sod, cat and gr gene expression in the different tissues were found in this population, as well as very high Cd concentrations. This could mean that these turtles are adapting to the metals-production of ROS and damage through a high transcription of these antioxidants. Multiple positive relationships with GR seem to be part of its compensatory effect due to the decrease of SOD production against the high and chronic exposure to certain xenobiotics. CAT, on the other hand, seems not to be used much, and glutathione detoxification of H2O2 may be more important in this species. Finally, despite the very high Cd concentrations found in this population, no significant relationship was found in any tissue with metallothionein gene expression. These results, along with very high Cd concentrations and a negative relationship with Cu, lead us to consider some kind of disruption in mt gene expression in these turtles.

Effects of Family Structure on Mental Health of Children: A Preliminary Study.

Background:To find any association between family structure and rates of hospitalization as an indicator for behavior problems in children.Methods:Retrospective chart review of 154 patients who were admitted to the preadolescent unit at Lincoln Prairie Behavioral Health Center between July and December 2012.Results:We found that only 11% of children came from intact families living with biological parents while 89% had some kind of disruption in their family structure. Two-third of the children in the study population had been exposed to trauma with physical abuse seen in 36% of cases. Seventy-one percent had reported either a parent or a sibling with a psychiatric disorder. Children coming from biologically family were less likely to have been exposed to trauma. Children coming from single/divorced families were less likely to have been exposed to sexual abuse but more likely to have a diagnosis of attention deficit hyperactivity disorder (ADHD) compared to other types of families. Strong association was found between exposure to trauma and certain diagnoses in respect to hospitalization. ADHD predicted a 4 times likelihood of having more than one previous hospitalization, with mood disorder, oppositional defiant disorder, and physical abuse increasing the risk by more than twice.Conclusions:Significant differences in family structure were demonstrated in our study of children being admitted to inpatient psychiatric hospitalization. The presence of trauma and family psychiatric history predicted higher rates of readmission. Our study highlighted the role of psychosocial factors, namely, family structure and its adverse effects on the mental well-being of children.

От “несостоявшихся государств” к “неустойчивым состояниям”: логика понятийной эквилибристики

This paper tracks the evolution and interactions of Western policy and academic discourses on statehood. With help of scientometrics it demonstrates that dynamics and trajectory of conceptualization of these terms were first framed by the end of the Cold War and later by the terrorist attacks of 9/11. However, the adoption of the first doctrinal documents on international engagement in fragile states in 2005 substantially altered the discourse. Instrumentalization of the ‘fragile state’ concept made it subject to a rigorous critique that revealed several drawbacks – political bias, normativity, state-centrism etc. Seeking to mitigate these limitations, scholars, experts and policymakers switched attention from ‘fragile states’ to ‘states of fragility’, elaborated multi-dimensional typology of fragility and borrowed the ‘resilience’ concept and a number of related terms from the theory of complex adaptive systems. These changes – influenced partly by geopolitical shifts – might help abandon outdated reductionist interpretations of state failure and de-dogmatize the discourse. Use of such concepts as ‘resilience’, ‘stability’, ‘external disruptions’, ‘risks’ favors a holistic approach to political systems which will take into account their complex interactions with the international system and the environment. However, it seems highly probable that the new concept might suffer from the same drawbacks, such as ambivalence. To avoid this risk, scholars will have to develop new techniques of measuring resilience of social systems to various kinds of disruptions, which, in turn, might help build efficient systems of early warning.

Robust job shop scheduling problem: Mathematical models, exact and heuristic algorithms

Job shop scheduling problem is very important one in real application of many kind of industries. In the real world applications, there exist many different kinds of disruptions with different sizes. In this situation, beyond the optimality of the final solution, its ability to absorb disruptions is vital, so that the final solution remains feasible in the case of occurring predicted disruptions. In this paper a robust job shop scheduling problem under disruptions is considered. It is intended to generate robust schedules which are able to absorb a predefined range of disruptions. For this reason, two robustness indices are proposed and the related formulas for computing the required buffer times to reach the desired robustness level are proposed. For this purpose, four methods are proposed to solve the variant defined robust job shop scheduling problem, including (1) a mathematical model, (2) a Branch and Bound algorithm, (3) a beam search algorithm, and (4) a meta-heuristic algorithm based on the particle swarm optimization (PSO) method. The first and second methods result in optimum solution. As the size of the problem increases, the required time to find the optimum solutions raises, so that no solutions can be achieved in rational amount of time, e.g. one hour. Therefore, the third and fourth methods are proposed to find good solutions even for large-scale problem in a limited amount of time. Finally, the algorithms are compared using some randomly generated instances. The results show that each algorithm can outperform the others in different conditions.

When disruptive behavior meets outcome-based education

Disruptive behavior is a major concern for most educational systems. Schools often respond to disruptive students with exclusionary and punitive approaches that have limited effect or value. Moreover, recent neoliberal trends with increased focus on student learning outcome change the attitudes towards disruptive student behavior and also narrow down and homogenize the range of what is considered as ?acceptable student behavior?. In this article we discuss the interrelationship between an outcome-based, neoliberal school approach and notions of disruptive behavior. We claim that the outcome-based and neoliberal approach to education basically promotes an un-educational way of thinking about education that also has a huge influence on perceptions of and tolerance towards all kinds of disruptions in schools - whether they come from students, parents, teachers or researchers.

Using immune designed ontologies to monitor disruptions in manufacturing systems

Manufacturing systems are subject to several kinds of disruptions and risks, which may break the continuity of workflows, disturb pre-set organization, and prevent the production system from reaching its expected levels of performance. Several approaches were proposed to deal with manufacturing system disruptions and risks. Unfortunately, most of them focus more on explaining the causes of the disruption/risk, rather than on determining disruption/risk effects on workflows, pre-set organization and expected performance. Existing approaches usually operate off-line, thus missing current and accurate data about plant activities and changing conditions. Most of them do not offer concepts that allow the design of computerized tools dedicated to disruption/risk monitoring and control. In this paper, we rely on biological immunity to guide the design of a knowledge-based approach, and to use it to monitor disruptions and risks in manufacturing systems. The suggested approach involves functions specifically dedicated to deal with a variety of disruptions and risks, such as detection, identification of consequences and reaction to disruptions. This architecture is intended to be embedded within industrial information and decision support systems, such as ERP (« Enterprise Resource Planning ») and MES (« Manufacturing Execution System »). A prototype implementation using ontologies and multi-agent systems shows the relevance of the suggested approach in monitoring disruptions and risks. A simplified example from the steel industry illustrates the kind of support that can be provided to decision makers.

Computing Minimal Update Sequences for Graceful Router-Wide Reconfigurations

Manageability and high availability are critical properties for IP networks. Unfortunately, with link-state routing protocols commonly used in such networks, topological changes lead to transient forwarding loops inducing service disruption. This reduces the frequency at which operators can adapt their network. Prior works proved that it is possible to avoid disruptions due to the planned reconfiguration of a link by progressively changing its weight, leading to a solution that does not require changing protocol specification. In this paper, we study the more general problem of gracefully modifying the logical state of multiple interfaces of a router, while minimizing the number of weight updates. Compared to single-link modifications, the router update problem is $k$ -dimensional for a router having $k$ neighbors. We also show that multidimensional updates may trigger new kinds of disruptions that make the problem more challenging than the single-link case. We then present and evaluate efficient algorithms that compute minimal sequences of weights enabling disruption-free router reconfigurations. Based on analysis of real IP network topologies, we show that both the size of such sequences and the computing time taken by our algorithms are limited.

Evaluation of Disturbances in Mechanized Tunneling Using Process Simulation

AbstractProduction in mechanized tunneling frequently encounters disruptions due to sensitive process interdependencies. Reasons can be technical failures, insufficient capacity dimensioning, organizational deficiencies, or sensitive supply chains. These unproductive times could be reduced by an adequately designed project setup including logistical aspects. Therefore, possible disturbances must be identified and analyzed in detail. Based on this investigation, the machine and logistics setup can be changed to cope with unforeseen events. We present a modeling and simulation approach to analyze production and logistic processes of mechanized tunneling processes in a transparent and understandable way. The system is formalized in the modeling standard SysML. Thereby, we consider relevant system elements and process interdependencies to assess the effect of disturbances and to identify bottlenecks. We distinguish three kinds of disruptions: (i) technical failure of main elements related to the production processes, (ii) issues resulting from an insufficient supply chain, and (iii) cascading disturbances. The implementation in a simulation environment and the processing of relevant input data are presented hereupon. The presented approach is then illustrated by means of an application example based on a completed metro project. Three extending simulation studies quantify the impact of the identified disturbance categories.

Disruptions management of a supply chain under strategic subsidy policy for the demand-stimulating inventory

This paper introduces a game model of one manufacturer and one retailer with the demand depending on the amount of inventory displayed on the retailer’s shelf. We study coordination mechanisms of the supply chain with the two kinds of disruptions. To coordinate the channel as well as make a profit, the manufacturer needs to augment the wholesale price lever by another, i.e., an inventory-holding cost subsidy to the retailer. We show that the inventory-subsidy contract for disruption(s) situation has its rationality and limitation: from the perspective of feasibility analysis, we find that when the disrupted amount of inventory-holding cost is larger than a certain threshold value, both players can achieve win–win by using inventory-subsidy contract. Otherwise, it may be ineffective. For two-factor disruptions, there are some mutual restraints between the disrupted inventory-holding cost and the disrupted demand when the coordination mechanism is used. We also find that both disruption situations have their own robust scales, in which the manufacturer should not change the original production plan but at the expense of providing a more attractive subsidy scheme to the retailer. Interestingly, some counter-intuitive managerial insights can be observed in robust scales. For example, the market demand increases with the displayed inventory level in the setting of the demand-stimulating inventory. However, the higher the demand, the less displayed inventory level will be in the robust scale.

Analysing legislative performance: a plebeian perspective

Legislative performance can be understood in terms of results (the quality of the laws enacted) or in terms of the literal performativity of legislators (the quality of their appearances on the public stage). This article examines two different ethical frameworks for evaluating legislative performance in this latter, performative sense: a deliberative model, which restricts just political performances to deliberative exchanges among citizens, and a plebeian model, which expands just political performances to include those where political and economic elites endure special burdens as a condition of their elevated status. Given certain drawbacks of the deliberative model and parallel advantages of the plebeian model, I endorse the plebeian approach to political performativity. The article concludes by elaborating one of the key contrasts between the two models with regard to political communication, namely the plebeian model's embrace of a distinct form of legislative disruption. Beyond the way deliberation itself disrupts non-communicative forms of power and beyond the way protests physically disrupt governmental processes, plebeianism invokes a third kind of disruption – non-deliberative speech – intended to rebuke and humble leaders rather than reach mutual understanding about issues.

One strange colonial thing: material remembering and the Bark Shield of Botany Bay

Declared objects of colonialism are strange things. They confirm colonialism but also repudiate it, resist it and persist beyond it. This paper is called by and follows one strange thing, the Bark Shield of Botany Bay, while exploring the idea of material remembering. The remembered colonial object does not always stand apart from consciousness or the embodied subject but helps to produce both. It both confirms and rearranges. When we remember materially we are reorganizing (for the remembered is never as it was before) that metaphysical arrangement in the present. This reorganization enables the shield to emerge as a particular kind of disruption to a colonial culture that has used material artefacts to mark strict divides between the Indigenous and the modern, past and present and between Indigenous ownership and white possession. The multiple ways in which this shield has been silenced, contained and hidden through multiple representations suggest the ongoing effectivity of this particular ‘thing’ and its persistent call for justice.

Modelling and intelligent solving of foodstuff distribution VRP based on disruption management

VRP problem is one of the key issues which affects the foodstuff distribution cost. Based on the features of foodstuff distribution and requirement of customer satisfaction, we construct a basic model that can be easily extended. In order to achieve the minimum cost of all kinds of disruptions, we add restrictions of cost and time, etc., introduce virtual task point and build a foodstuff distribution VRP model based on the disruption management. For the requirement of the complexity, timeliness of the model solution, we develop an improved Particle Swarm Optimisation algorithm adopting the Guided Local Search algorithm, and give the basic steps for solving the model. The research results of the case study show that, in dealing with disruptive VRP events, the model can effectively avoid the global adjustment of the foodstuff distribution VRP program.

The Tactical Disruptiveness of Social Movements

This article examines factors associated with social movements’ abilities to disrupt corporate targets. I identify two kinds of disruption: market disruption and mediated disruption. Market disruption deters the ability of the corporate target to effectively accrue and use market resources, while mediated disruption occurs as a tactic communicates a movement's claims about the target through third party intermediaries, like the media, thereby disrupting the target's image and reputation. Using data on corporate boycotts in the United States from 1990 to 2005, the analyses assess the extent to which movement characteristics or target characteristics cause stock price declines of boycotted companies—i.e., market disruption—and the frequency of national media attention given to boycotts—i.e., mediated disruption. The analyses indicate that target characteristics matter more in shaping a boycott's initial market disruption; however, both movement and target characteristics affect mediated disruption. Certain movement characteristics, like social movement organization (SMO) formality, public demonstrations, and celebrity endorsements, enable mediated disruption but have no effect on market disruption. A firm's size makes it vulnerable to both market and mediated disruption, while slack resources help a firm avoid market disruption. A target's reputational ranking initially buffers it from market disruption but increases its vulnerability to mediated disruption. The results indicate that the two kinds of disruption are interrelated. Market disruption has a marginal effect on the intensity of subsequent media coverage and ongoing media attention accentuates further market disruption.

Disrupting Representational Infrastructure in Conversations Across Disciplines

In this article, we analyze conversations in consulting meetings where people work across disciplines to design things. We focus on interactional processes through which people disrupt and attempt to change representational technologies for scientific and technical classification. Our case material is drawn from ethnographic and cognitive studies of work in field entomology and architectural design. In both cases, we find common structures of interaction when people work across disciplines. These include selective use of talk, embodied action, and inscription to animate representational states that make up design alternatives. Participants from different disciplines animate situations in strikingly different ways, but these differences can either go unremarked or be put into coordinated use without explicit, shared understandings. Differences become remarkable either when a design proposal runs counter to deeply held disciplinary objectives or threatens to destabilize a wider network of representational technologies. These kinds of disruptions, and their consequences for representational infrastructure, are a central problem for research on distributed cognition.

David Rabe and the female figure: The body in the boom boom room

The closing scene of David Rate's play In the Boom Boom Room employs a female nude in its rhetorical attack on sexism; the principal character resigns herself to the emotional and economic pressures of the male dominated order and appears finally on stage as a topless dancer. Although Rabe's play clearly evinces a didactic aspect, one that argues for female advancement, the work may reproduce the oppression it repudiates. The play's formal style and structure may involve an element of subjection, whereby the female figure experiences a textual appropriation. Nonetheless, Rabe's play works oppositionally in that the nude actor may also incite a kind of disruption. In Chrissy's go‐go dance, the fictive (signified) component of the character is suppressed and displaced by the material (signifier) aspect of the performer's own body—this phenomenon may promise the overthrow of textual authority and the expression of female agency. This essay in essence explores the equivocal implications of Chrissy's enactment...