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.

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.

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.

Assessing the Regional Economic Ripple Effect of Flood Disasters Based on a Spatial Computable General Equilibrium Model Considering Traffic Disruptions

With growing regional economic integration,transportation systems have become critical to regional development and economic vitality but vulnerable to disasters.However,the regional economic ripple effect of a disaster is difficult to quantify accurately,especially considering the cumulated influence of traffic disruptions.This study explored integrating transportation system analysis with economic modeling to capture the regional economic ripple effect.A state-of-the-art spatial computable general equilibrium model is leveraged to simulate the operation of the economic system,and the marginal rate of transport cost is introduced to reflect traffic network damage post-disaster.The model is applied to the 50-year return period flood in2020 in Hubei Province,China.The results show the following.First,when traffic disruption costs are considered,the total output loss of non-affected areas is 1.81 times than before,and non-negligible losses reach relatively remote zones of the country,such as the Northwest Comprehensive Economic Zone(36%of total ripple effects).Second,traffic disruptions have a significant hindering effect on regional trade activities,especially in the regional intermediate input—about three times more than before.The industries most sensitive to traffic disruptions were transportation,storage,and postal service(5 times),and processing and assembly manufacturing(4.4 times).Third,the longer the distance,the stronger traffic disruptions'impact on interregional intermediate inputs.Thus,increasing investment in transportation infrastructure significantly contributes to mitigating disaster ripple effects and accelerating the process of industrial recovery in affected areas.

Enhancing metformin-induced tumor metabolism destruction by glucose oxidase for triple-combination therapy

Despite decades of laboratory and clinical trials,breast cancer remains the main cause of cancer-related disease burden in women.Considering the metabolism destruction effect of metformin(Met)and cancer cell starvation induced by glucose oxidase(GOx),after their efficient delivery to tumor sites,GOx and Met may consume a large amount of glucose and produce sufficient hydrogen peroxide in situ.Herein,a pH-responsive epigallocatechin gallate(EGCG)-conjugated low-molecular-weight chitosan(LC-EGCG,LE)nanoparticle(Met–GOx/Fe@LE NPs)was constructed.The coordination between iron ions(Fe3+)and EGCG in this nanoplatform can enhance the efficacy of chemodynamic therapy via the Fenton reaction.Met–GOx/Fe@LE NPs allow GOx to retain its enzymatic activity while simultaneously improving its stability.Moreover,this pH-responsive nanoplatform presents controllable drug release behavior.An in vivo biodistribution study showed that the intracranial accumulation of GOx delivered by this nanoplatform was 3.6-fold higher than that of the free drug.The in vivo anticancer results indicated that this metabolism destruction/starvation/chemodynamic triple-combination therapy could induce increased apoptosis/death of tumor cells and reduce their proliferation.This triple-combination therapy approach is promising for efficient and targeted cancer treatment.

Effect of wall-disruption on nutrient composition and in vitro digestion of camellia and lotus bee pollens

The nutrient digestion,absorption and biological activity of bee pollen may be limited due to the complex pollen wall.Here,the effect of superfine grinding technology on the release of nutrients from bee pollen were investigated,and their antioxidant activities and in vitro digestion were explored in this study.Results showed that the content of nutrients in bee pollen increased after wall disruption.Among them,fat content increased by 22.55%-8.31%,protein content increased by 0.54%-4.91%,starch content increased by 36.31%-48.64%,soluble sugar content increased by 20.57%-29.67%,total phenolic acid content increased by 11.73%-86.98%and total flavonoids content increased by 14.29%-24.79%.At the same time,the antioxidant activity increased by 14.84%-46.00%.Furthermore,the active components such as phenolic compounds in the wall-disruption bee pollen were more readily to be released during the in vitro digestion,and easier to be absorbed because of their higher bioaccessibility.Antioxidant activities during in vitro digestion were also improved in walldisruption bee pollen.These findings provide evidence that bee pollen wall disruption was suggested,thus,it is more conducive to exerting the value of bee pollen in functional foods.

Design of pH-responsive antimicrobial peptide melittin analog-camptothecin conjugates for tumor therapy

Melittin,a classical antimicrobial peptide,is a highly potent antitumor agent.However,its significant toxicity seriously hampers its application in tumor therapy.In this study,we developed novel melittin analogs with pH-responsive,cell-penetrating and membranelytic activities by replacing arginine and lysine with histidine.After conjugation with camptothecin(CPT),CPT-AAM-1 and CPT-AAM-2 were capable of killing tumor cells by releasing CPT at low concentrations and disrupting cell membranes at high concentrations under acidic conditions.Notably,we found that the C-terminus of the melittin analogs was more suitable for drug conjugation than the N-terminus.CPT-AAM-1 significantly suppressed melanoma growth in vivo with relatively low toxicity.Collectively,the present study demonstrates that the development of antitumor drugs based on pH-responsive antimicrobial peptide-drug conjugates is a promising strategy.

CALD1 facilitates epithelial-mesenchymal transition progression in gastric cancer cells by modulating the PI3K-Akt pathway

BACKGROUND CALD1 has been discovered to be abnormally expressed in a variety of malignant tumors,including gastric cancer(GC),and is associated with tumor progression and immune infiltration;however,the roles and mechanisms of CALD1 in epithe-lial-mesenchymal transition(EMT)in GC are unknown.AIM To investigate the role and mechanism of CALD1 in GC progression,invasion,and migration.METHODS In this study,the relationship between CALD1 and GC,as well as the possible network regulatory mechanisms of CALD1,was investigated by bioinformatics and validated by experiments.CALD1-siRNA was synthesized and used to trans-fect GC cells.Cell activity was measured using the CCK-8 method,cell migration and invasive ability were measured using wound healing assay and Transwell assay,and the expression levels of relevant genes and proteins in each group of cells were measured using qRT-PCR and Western blot.A GC cell xenograft model RESULTS Bioinformatics results showed that CALD1 was highly expressed in GC tissues,and CALD1 was significantly higher in EMT-type GC tissues than in tissues of other types of GC.The prognosis of patients with high expression of CALD1 was worse than that of patients with low expression,and a prognostic model was constructed and evaluated.The experimental results were consistent with the results of the bioinformatics analysis.The expression level of CALD1 in GC cell lines was all higher than that in gastric epithelial cell line GES-1,with the strongest expression found in AGS and MKN45 cells.Cell activity was significantly reduced after CALD1-siRNA trans-fection of AGS and MKN45 cells.The ability of AGS and MKN45 cells to migrate and invade was reduced after CALD1-siRNA transfection,and the related mRNA and protein expression was altered.According to bioinfor-matics findings in GC samples,the CALD1 gene was significantly associated with the expression of members of the PI3K-AKT-mTOR signaling pathway as well as the EMT signaling pathway,and was closely related to the PI3K-Akt signaling pathway.Experimental validation revealed that upregulation of CALD1 increased the expression of PI3K,p-AKT,and p-mTOR,members of the PI3K-Akt pathway,while decreasing the expression of PTEN;PI3K-Akt inhibitor treatment decreased the expression of PI3K,p-AKT,and p-mTOR in cells overexpressing CALD1(still higher than that in the normal group),but increased the expression of PTEN(still lower than that in the normal group).CCK-8 results revealed that the effect of CALD1 on tumor cell activity was decreased by the addition of the inhibitor.Scratch and Transwell experiments showed that the effect of CALD1 on tumor cell migration and invasion was weakened by the addition of the PI3K-Akt inhibitor.The mRNA and protein levels of EMT-related genes in AGS and MKN45 cells were greatly altered by the overexpression of CALD1,whereas the effect of overex-pression of CALD1 was significantly weakened by the addition of the PI3K-Akt inhibitor.Animal experiments showed that tumour growth was slow after inhibition of CALD1,and the expression of some PI3K-Akt and EMT pathway proteins was altered.CONCLUSION Increased expression of CALD1 is a key factor in the progression,invasion,and metastasis of GC,which may be associated with regulating the PI3K-Akt pathway to promote EMT.