The AI Paradox: Mapping the Unintended Disruptions in IT and Beyond

In the realm of Artificial Intelligence (AI), there exists a complex landscape where promises of efficiency and innovation clash with unforeseen disruptions across Information Technology (IT) and broader societal realms. This paper sets out on a journey to explore the intricate paradoxes inherent in AI, focusing on the unintended consequences that ripple through IT and beyond. Through a thorough examination of literature and analysis of related works, this study aims to shed light on the complexities surrounding the AI paradox. It delves into how this paradox appears in various domains, such as algorithmic biases, job displacement, ethical dilemmas, and privacy concerns. By mapping out these unintended disruptions, this research seeks to offer a nuanced understanding of the challenges brought forth by AI-driven transformations. Ultimately, its goal is to pave the way for the responsible development and deployment of AI, fostering a harmonious integration of technological progress with societal values and priorities.

Supply chain coordination mechanisms under asymmetric information with retailer cost disruptions

A two-level supply chain model involving one supplier and one retailer with linear demand is developed, and supply chain coordination mechanisms under asymmetric information （the retailer＇ s cost structure is asymmetric information） are proposed by employing game theory in two scenarios： coordination mechanisms under asymmetric information in a regular scenario （without disruption）; and coordination mechanisms under asymmetric information in an irregular scenario （ with retailer cost disruptions）. It is optimal for the supply chain to maintain the original production plan and to guarantee a steadily running system if variations of retailer costs are sufficiently low and do not exceed an upper bound. This shows that the original production plan has certain robustness under disruptions. Decisions must be re-made if a retailer＇ s cost change is greater and exceeds an upper bound. Impacts of retailer cost disruptions on the order quantity, the retail price, the wholesale price and each party＇ s as well as the system＇ s expected profits are investigated through numerical analyses.

Supply Chain Network Equilibrium with Revenue Sharing Contract under Demand Disruptions

Contract is a common and effective mechanism for supply chain coordination,which has been studied extensively in recent years.For a supply chain network model,contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition.In order to achieve equilibrium,we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper.Then,we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies.When demand disruptions happen,the supply chain network equilibrium state will be broken and change to a new one,so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining.Finally,a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.

Coordinating pricing strategies in supply chain under asymmetric information and disruptions

The coordinating pricing strategies with asymmetric cost information under disruptions are investigated in a one-supplier-one-retailer supply chain system.While the retailer's cost structure is asymmetric information,supply chain pricing contract models(a wholesale price contract and an all-unit quantity discount contract)under asymmetric information are proposed by employing the principal-agent principle in a regular scenario.When the retailer's cost distribution is fluctuated by disruptions,we obtain the optimal emergency strategies of the supply chain under asymmetric information by considering deviation costs and show how to effectively handle the cost uncertainty.Using numerical methods,impacts of cost disruptions on the optimal wholesale price,the retailer price,the order quantity and the expected profits of the retailer,the supplier,as well as the total system are analyzed.It is found that the all-unit quantity discount policy can obtain better performance than the wholesale pricing policy.

Rolling Partial Rescheduling with Dual Objectives for Single Machine Subject to Disruptions

This paper discusses the single-machine rescheduling problem with efficiency and stability as criteria, where more than one disruption arises in large-scale dynamic circumstances. Partial rescheduling (PR) strategy is adopted after each disruption and a rolling mechanism is driven by events in response to disruptions. Two kinds of objective functions are designed respectively for PR sub-problem involving in the interim and the terminal of unfinished jobs. The analytical result demonstrates that each local objective is consistent with the global one. Extensive computational experiment was performed and the computational results show that the rolling PR strategy with dual objectives can greatly improve schedule stability with little sacrifice in efficiency and provide a reasonable trade-off between solution quality and computational efforts.

Simulation of Plasma Disruptions for HL-2M with the DINA Code

Plasma disruption is often an unavoidable aspect of tokamak operations. It may cause severe damage to in-vessel components such as the vacuum vessel conductors, the first wall and the divertor target plates. Two types of disruption, the hot-plasma vertical displacement event and the major disruption with a cold-plasma vertical displacement event, are simulated by the DINA code for HL-2M. The time evolutions of the plasma current, the halo current, the magnetic axis, the minor radius, the elongation as well as the electromagnetic force and eddy currents on the vacuum vessel during the thermal quench and the current quench are investigated. By comparing the electromagnetic forces before and after the disruption, we find that the disruption causes great damage to the vacuum vessel conductors. In addition, the hot-plasma vertical displacement event is more dangerous than the major disruption with the cold-plasma vertical displacement event.

Automatic Surveillance and Control System Framework-DPS-KA-AT for Alleviating Disruptions of Social Media in Higher Learning Institutions

The worldwide change and transformations are taking place in socio-techno cultures. In the epicenter of all these Information and Communication Technologies (ICTs), the Internet is the backbone and paving salient communications and computations Medias like the emergence of social networking sites (SNSs). These SNSs are facilitating globalized entertainment, socialization, communications, and information sharing over hand-held electronic gazettes/mobiles like Facebook, Twitter, Instagram, Skype, and WhatsApp etc. The positive side of these SNSs is making the world a social village but apart from these positive aspects, there is another trait of multifold adversities/disruptions or negative effects which still have not been exposed and drawn attention. The remedial action for such adversities is needed to be designed and developed. The all age groups and genders are typically involved and resulting in wastage of time, money and peace of minds. The adverse effects of social media users in a Higher Learning Institutions are getting worse day-by-day. The prime aim of this research study is to design an automatic Surveillance System Framework for alleviation of the social media disruptions in these institutions. This framework aims to design and develop a surveillance system and access control guidelines for judiciously alleviating the misuse of social media. The study used MS form, Protopie, adobe XD and InVision for data collection, framework design and prototype development respectively. This research is an attempt to apply an explanatory and applied research design science approach using survey, interviews and technical observations-based primary data analytics. The study concluded with a cloud-based automatic surveillance, auto alerts and control system framework (DPS-KA-AT) and functionally validated by a system framework prototype. In the survey and interview, the 66% respondents’ response was “YES”, while 34% “NO” when enquired for the need assessment of the automatic surveillance and control system towards alleviation of the social media adversities or disruptions. This percentage indicates that the highest number of respondent or the highest number of higher learning institutions communities need an urgent automatic monitoring, surveillance and control system towards alleviation of such adversities/disruptions. The study concluded with a remark “a concrete and Automatic Surveillance and Control System Framework can be a great instrumental for minimizing the adversities of social media in higher learning institutions”.

Relationship between Disruptions of Carbon’s Cyclic Set Natural Transfers and the Upsurge of Weather Conditions with Strong Winds and Heavy Rains

The cyclic set of natural transfers of carbon (also called: Global Carbon Cycle) is built with the following physicochemical and bacteriological processes: 1) atmosphere to green plants or soil transfers;2) animals or plants to atmosphere transfers;3) burning fossil fuels to atmosphere transfers;4) animals (including humans) to soil transfers;5) atmosphere to oceans transfers, etc. This whole cycle (despite its obvious complexity), is a formal proof that disturbances recorded by carbon cycle described above, inevitably alter the chemical composition of the atmosphere and, therefore, lead to climate change whose magnitude depends on the sensitivity of the atmosphere relative to the changed settings. The weather models used to assess climate change caused by CFCs, have the annoying tendency to neglect the contribution of clouds to the global carbon balance. Yet it has been proven by C. Mbane in 2015 that clouds are composed of only two elements (dry air and saturated water vapor);and that clouds’ saturated water vapor may form precipitation (solid or liquid) if and only if they met and dissolve condensation nuclei (mainly the carbon dioxide (CO2) in the case of Troposphere). In other words, atmosphere absorbs a significant amount of CO2 in the formation of rains. The purpose of our work is to make it clear to the international opinion that cloud’s saturated water vapor is the true lung of our planet, far ahead of the green plants respiration or photosynthesis those take place only under the influence of sunlight and in the very lower layers of the troposphere (e.g., well below 25 meters from the surface of the earth). Each of us could then easily understand the link between GCCD (Global Carbon Cycle Disruptions) and the upsurge of WCWSWHR (weather conditions with strong winds and heavy rains).

Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control

This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.

Investigating the physics of disruptions with real-time tomography at JET

As JET is developing and testing operational scenarios for higher fusion performance,an increase in pulse disruptivity is being observed.On a deeper analysis,we find that several radiative phenomena play an active role in determining the outcome of the pulse.The analysis is enabled by the use of real-time tomography based on the bolometer diagnostic.Even though plasma tomography is an inverse problem,we use machine learning to train a forward model that provides the radiation profile directly,based on a single matrix multiplication step.This model is used to investigate radiative phenomena including sawtooth crashes,ELMs and MARFE,and their relationship to the radiated power in different regions of interest.In particular,we use realtime tomography to monitor the core region,and to throw an alarm whenever core radiation exceeds a certain threshold.Our results suggest that this measure alone can anticipate a significant fraction of disruptions in the JET baseline scenario.

Chaos and Disruptions as the Challenge to Urban Transportation in Tanzania

Transportation is a key to the economy and production;it makes mobility more accessible and enhances the social and economic interactions.On the other hand,the increase of urban population,pollution and other negative impacts directly compromise the existing transportation systems and endanger the future transportation systems in developing countries.This paper examines chaos as the challenge facing urban transportation in Tanzania cities and provides some suggestions to reduce the existing problem.This has been done by looking at the design and plan of the Tanzania cities,coordination of transportation systems and car dependency.Environmental and social impacts which include congestions,air pollution,traffic accidents and energy consumption have been described.Suggestions for addressing the challenges facing urban transportation in developed countries like Tanzania have been examined by adopting the holistic approach.Such approach has shown to be effective in solving the challenges facing urban transportation in the cities of developing countries such as improving public transport,provision of off-street parking,enforcement of traffic laws and regulations and restrict car use.Moreover,approaches to alleviate challenges facing urban transportation should be designed for specific cities and urban transport planners must understand that models and solutions used for cities in the developed countries may not be applicable to cities of developing countries.

Supply Chain Coordination with Demand Disruptions under Convex Production Cost Function

This paper investigates the problem of how to handling demand disruptions ina one-supplier-one-retailer supply chain, where production cost is a convex function of productionquantity andprice-demand relationship is linear. Our results show that, ifdemand is disrupted, underthe new price-demand relationship, all-unit wholesale quantity discount policies combiningcapacitated linear pricingpolicies can also fully coordinate the supply chain.

Characterization of plasma current quench during disruptions at HL-2A

The most essential assumptions of physics for the evaluation of electromagnetic forces on the plasma-facing components due to a disruption-induced eddy current are characteristics of plasma current quenches including the current quench rate or its waveforms. The characteristics of plasma current quenches at HL-2A have been analyzed during spontaneous disruptions. Both linear decay and exponential decay are found in the disruptions with the fastest current quenches.However, there are two stages of current quench in the slow current quench case. The first stage with an exponential decay and the second stage followed by a rapid linear decay. The faster current quench rate corresponds to the faster movement of plasma displacement. The parameter regimes on the current quench time and the current quench rates have been obtained from disruption statistics at HL-2A. There exists no remarkable difference for distributions obtained between the limiter and the divertor configuration. This data from HL-2A provides basic data of the derivation of design criteria for a large-sized machine during the current decay phase of the disruptions.

Numerical Analyses of Electromagnetic Forces on the ITER Blanket Module Shield Block During Major Disruptions

Electromagnetic（EM） load is one of the key design drivers for the blanket shield block（SB） and other in-vessel components. In this article, an EM analysis method was developed to address the EM force on the SB. The plasma currents, which vary spatially and temporally,are loaded as a filament at each time point. The standard blanket module No.04（BM04） under major disruption（MD） is selected to perform the analyses. The analyses results are validated by comparing currents on the passive structure. To better understand the effects of cooling channels and slits on the EM force, the case of SB without cooling channel and the case without slits are calculated to make comparisons. The results show that the slits play an important role in controlling the EM load on SB.

Neural Network Prediction of Disruptions Caused by Locked Modes on J-TEXT Tokamak

Prediction of disruptions caused by locked modes using the Back-Propagation （BP） neural network is completed on J-TEXT tokamak. The network, which is based on the BP neural network, uses Mirnov coils and locked mode coils signals as input data, and outputs a signal including information of prediction of locked mode. The rate of successful prediction of locked modes is more than 90%. For intrinsic locked mode disruptions, the network can give a prewarning signal about 1 ms ahead of the locking-time. For the disruption caused by resonant magnetic perturbation （RMPs） locked modes, the network can give a prewarning signal about 10 ms ahead of the locking-time.

Quantity discount contracts for supply chain coordination under asymmetric information and disruptions

The quantity discount contracts are investigated for a one-supplier-one-retailer supply chain with asymmetric information when the retailer's cost is disrupted. While the retailer's cost structure is asymmetric information, two all-unit quantity discount contract models, fixed expected-profit percentage discount(FEPD) and fixed wholesale-pricing percentage discount(FWPD) under asymmetric information are proposed in a regular scenario. When the retailer's cost distribution fluctuates due to disruptions, the optimal emergency strategies of supply chains are obtained under asymmetric information. Using numerical methods, the impact of cost disruptions on decisions about the regular wholesale price, discount wholesale price, order quantity and expected profits of the retailer, the supplier as well as the total system are analyzed. It is found that the FEPD policy is more robust and adaptable than the FWPD policy in disruption circumstances.

Coronavirus Pandemic and the Coming Disruptions in the Global Economy:Insights From Jeremy Rifkin’s Theory of Third Industrial Revolution

As the coronavirus pandemic spreads through the continents,it has dramatically disrupted everything in the global economy from stock markets and supply chains to oil and food prices,and in seeking to restrict the spread of COVID-19,governments are shutting down whole commercial sectors which could cause a huge recession in some countries as the United Nations have already warned.All these new circumstances have raised again the fundamental questions about the future of our global economy.Therefore,this paper has tried to make sense of how the post-pandemic global economy would look like by shedding light on Jeremy Rifkin’s theory of the new industrial revolution and the coming disruption in the global market.

Intelligent control for predicting and mitigating major disruptions in magnetic confinement fusion

Magnetic confinement fusion is believed to be one of the promising paths that provides us with an infinite supply of an environment-friendly energy source,naturally contributing to a green economy and low-carbon development.Nevertheless,the major disruption of high temperature plasmas,a big threat to fusion devices,is still in the way of mankind accessing to fusion energy.Although a bunch of individual techniques have been proved to be feasible for the control,mitigation,and prediction of disruptions,complicated experimental environments make it hard to decide on specific control strategies.The traditional control approach,designing a series of independent controllers in a nested structure,cannot meet the needs of real-time complicated plasma control,which requires extended engineering expertise and complicated evaluation of system states referring to multiple plasma parameters.For-tunately,artificial intelligence(AI)offers potential solutions towards entirely resolving this troublesome issue.To simplify the control system,a radically novel idea for designing controllers via AI is brought forward in this work.Envisioned intelligent controllers should be developed to replace the traditional nested structure.The successful development of intelligent control is expected to effectively predict and mitigate major disruptions,which would definitely enhance fusion performance,and thus offers inspiring odds to improve the accessibility of sustainable fusion energy.

Observations of Runaway Electron Generation during Disruptions on HL-2A Tokamak

The major disruption can not only lead to the great heat loads and produce the large electromagnetic force on the first wall and divertor plates, but also can generate the runaway electrons. The runaway electrongeneration is a dangerous event for tokamak operation.

Beyond wrecking a wall:revisiting the concept of blood–brain barrier breakdown in ischemic stroke

The blood–brain barrier constitutes a dynamic and interactive boundary separating the central nervous system and the peripheral circulation.It tightly modulates the ion transport and nutrient influx,while restricting the entry of harmful factors,and selectively limiting the migration of immune cells,thereby maintaining brain homeostasis.Despite the well-established association between blood–brain barrier disruption and most neurodegenerative/neuroinflammatory diseases,much remains unknown about the factors influencing its physiology and the mechanisms underlying its breakdown.Moreover,the role of blood–brain barrier breakdown in the translational failure underlying therapies for brain disorders is just starting to be understood.This review aims to revisit this concept of“blood–brain barrier breakdown,”delving into the most controversial aspects,prevalent challenges,and knowledge gaps concerning the lack of blood–brain barrier integrity.By moving beyond the oversimplistic dichotomy of an“open”/“bad”or a“closed”/“good”barrier,our objective is to provide a more comprehensive insight into blood–brain barrier dynamics,to identify novel targets and/or therapeutic approaches aimed at mitigating blood–brain barrier dysfunction.Furthermore,in this review,we advocate for considering the diverse time-and location-dependent alterations in the blood–brain barrier,which go beyond tight-junction disruption or brain endothelial cell breakdown,illustrated through the dynamics of ischemic stroke as a case study.Through this exploration,we seek to underscore the complexity of blood–brain barrier dysfunction and its implications for the pathogenesis and therapy of brain diseases.