Backup Strategy Research Articles

To Act or Wait: The Impact of Disruption Duration Estimates on Manufacturer’s Response Strategies

In the event of a disruption at a primary supplier, the manufacturer’s sourcing and production operations are inevitably affected, necessitating a response strategy based on the estimated disruption duration. This paper derives the optimal production policy for each response strategy, aiming to minimize total costs over a planning horizon within a dynamic programming framework. We characterize these production policies across various model parameters, particularly focusing on the estimated disruption duration and initial inventory level. Our analysis identifies when the passive acceptance strategy and the backup strategy each hold an advantage, and how the cost benefits of each strategy vary with different model parameters. Additionally, we examine the consequences of overestimating or underestimating the disruption duration, providing insights into how the chosen response strategy and production policy, based on the estimated duration, diverge from the true optimal ones as the actual duration unfolds. We also highlight the cost implications of these discrepancies. Finally, in scenarios where the true duration follows a probabilistic distribution, our numerical experiments demonstrate how strategy selection and the cost of misestimation are influenced by the mean of the true disruption duration and the initial inventory level. These analyses offer decision-makers valuable guidance on when to act or wait in the face of disruptions.

An Economical Multilevel Backup Strategy for Electro-Hydraulic Braking System by Integrating Driving and Electronic Parking Brake Systems

An Economical Multilevel Backup Strategy for Electro-Hydraulic Braking System by Integrating Driving and Electronic Parking Brake Systems

Software Error Incident Categorizations in Aerospace

Since the first use of computers in spacecraft and aircraft, software errors have occurred. These errors can manifest as loss of life or less catastrophically. As the demand for automation increases, software in mission- or safety-critical systems should be designed to be tolerant to the most likely software faults. This paper categorizes historic aerospace software errors to determine trends of how and where automation is most likely to fail. A distinction between software producing wrong (erroneous) output versus no output (fail-silent) is introduced. Of the historical incidents analyzed, 85% were from software producing erroneous output rather than stopping. Rebooting was found to be ineffective in clearing erroneous behavior and not reliable to recover from silent software. Errors originated from within the code/logic itself in 58% of cases, 16% from configurable data, and 25% introduced through input sources, command or sensor. Forty percent of unexpected software behavior was caused by the absence of software, and 16% was subjectively due to “unknown-unknowns.” These findings indicate that to achieve software fault tolerance, backup strategies must be employed to detect and respond to erroneous software behavior beyond only fail-silent cases, and robust off-nominal testing should be performed to uncover unanticipated situations.

A phage satellite manipulates the viral DNA packaging motor to inhibit phage and promote satellite spread.

ICP1, a lytic bacteriophage of Vibrio cholerae, is parasitized by phage satellites, PLEs, which hijack ICP1 proteins for their own horizontal spread. PLEs' dependence on ICP1's DNA replication machineryand virion components results in inhibition of ICP1's lifecycle. PLEsare expected to depend on ICP1 factors for genome packaging, but the mechanism(s) PLEs use to inhibit ICP1 genome packaging is currently unknown. Here, we identify and characterize Gpi, PLE's indiscriminate genome packaging inhibitor. Gpi binds to ICP1's large terminase (TerL), the packaging motor, and blocks genome packaging. To overcome Gpi's negative effect on TerL, a component PLE also requires, PLE uses two genome packaging specifiers, GpsA and GpsB, that specifically allow packaging of PLE genomes. Surprisingly, PLE also uses mimicry of ICP1's pac site as a backup strategy to ensure genome packaging. PLE's pac site mimicry, however, is only sufficient if PLE can inhibit ICP1 at other stages of its lifecycle, suggesting an advantage to maintaining Gpi, GpsAand GpsB. Collectively, these results provide mechanistic insights into another stage of ICP1's lifecycle that is inhibited by PLE, which is currently the most inhibitory of the documented phage satellites. More broadly, Gpi represents the first satellite-encoded inhibitor of a phage TerL.

A Higher Performance Data Backup Scheme Based on Multi-Factor Authentication.

Remote data backup technology avoids the risk of data loss and tampering, and has higher security compared to local data backup solutions. However, the data transmission channel for remote data backup is not secure, and the backup server cannot be fully trusted, so users usually encrypt the data before uploading it to the remote server. As a result, how to protect this encryption key is crucial. We design a User-Centric Design (UCD) data backup scheme based on multi-factor authentication to protect this encryption key. Our scheme utilizes a secret sharing scheme to divide the encryption key into three parts, which are stored in the laptop, the smart card, and the server. The encryption key can be easily reconstructed from any two parts with user's private information password, identity and biometrics. As long as the biometrics has enough entropy, our scheme can resist replay attacks, impersonation user attacks, impersonation server attacks, malicious servers and offline password guessing attacks.

Manual Microcatheter-tip Modification: A bailout option for difficult "tip-in" technique during chronic total occlusion percutaneous coronary intervention.

The retrograde approach in chronic total occlusion (CTO) interventions often encounters significant challenges, particularly, when aligning the retrograde microcatheter (MC) with the antegrade system is difficult, complicating or even preventing standard externalization. To address these issues, techniques like the "tip-in" have proven to be effective backup strategies. We introduce the "Manual Microcatheter-tip Modification" (MMM) technique as an alternative when the "tip-in" method faces complications. We present a case of a left anterior descending CTO where MMM was successfully employed for the first time, enabling successful revascularization by manually modifying the MC tip to engage the retrograde guidewire. We explore the technical details within the framework of contemporary CTO PCI. This new technique could enhance the management of CTO interventions, offering innovative solutions when traditional externalization methods are problematic.

Selecting Resilient Strategies for Cost Optimization in Prefabricated Building Supply Chains Based on the Non-Dominated Sorting Genetic Algorithm-Ⅱ: Facing Diverse Disruption Scenarios

As a new sustainable building production mode, prefabricated building supply chains can realize energy saving, environmental protection and full cycle value maximization of building products. Prefabricated building supply chains often experience disruptions due to supply instability, transportation delay and force majeure, resulting in project delays and cost escalations and posing challenges to the sustainable development objectives of enterprises. Therefore, it is important and essential to study the strategy of enhancing the resiliency of prefabricated building supply chains, which has not been comprehensively explored in previous papers. This paper constructs decision-making models for supply chain cost resilience strategies under varying scenarios of supply disruptions, incorporating both redundant inventory and back-up supplier strategy. It considers the total cost and resilience of the supply chain as dual objective functions. Parameter-tuned non-dominated sorting genetic algorithm-П (NSGA-П) algorithms were used innovatively to solve the project case, and the impacts of the redundant inventory coefficient and back-up supplier supply price coefficient on the model result were analyzed. The results indicate that the supply chain with resilience construction has a superior capability to cope with disruption. The results show that when there is a mild supply disruption, the general contractor uses the capacity within the supply chain and chooses a redundant inventory strategy to restore resilience. In the event of moderate disruption, both the easy inventory strategy and back-up supplier strategy are selected to maintain supply chain stability. In the event of a severe disruption, only the back-up supplier strategy is selected to cover the losses and maintain the project schedule. In addition, the choice of resilience strategy is impacted by the inventory levels and component prices of back-up suppliers. It further verifies the effectiveness of the model and the impacts of uncertain parameters in the model on the results. This study contributes to enhancing the resilience management of the prefabricated building supply chain by the general contractor, thereby elevating the overall efficiency and competitiveness of the supply chain and furthering the sustainable development of prefabricated buildings.

Efficient SFC Protection Method against Network Attack Risks in Air Traffic Information Networks

With the continuous development of the civil aviation industry toward digitalization and intelligence, the closed architecture of traditional air traffic information networks struggles to meet the rapidly growing demands for air traffic services. Network function virtualization (NFV) is one of the key technologies that can address the rigidity of traditional air traffic information networks. NFV technology has facilitated the flexible deployment of air traffic services, but it has also expanded the attack surface of the network. In addressing the network attack risks faced by service function chains (SFCs) in NFV environments, a SFC protection method based on honeypots and backup technology (PBHB) is proposed to reduce the resource cost of protecting air traffic information networks while enhancing network security. Initially, PBHB utilizes the TAPD algorithm to deploy the primary VNFs as closely as possible to the shortest path between the source and destination endpoints, thus aiming to reduce SFC latency and save bandwidth resource costs. Subsequently, the RAHDR algorithm is employed to install honeypot VNFs in each physical platform that is at risk of side-channel attacks, thus updating the deployment status of honeypot VNFs in real time based on the VNF lifecycle in order to offer primary protection for SFCs. Lastly, the BDMPE algorithm was used to calculate the backup scheme with the highest protection efficiency to implement secondary protection for the SFCs that still do not meet the security requirements. Through experiments, the maximum backup limit for SFCs in PBHB was determined, confirming its satisfactory performance across various SFC arrival rates. Furthermore, performance comparisons with other SFC protection methods revealed that PBHB achieves optimizations in resources cost while ensuring SFC security and latency.

Research on reliability mapping of 5G low orbit constellation network slice based on deep reinforcement learning

Reliability mapping of 5G low orbit constellation network slice is an important means to ensure link network communication. The problem of state space explosion is a typical problem. The deep reinforcement learning method is introduced. Under the 5G low orbit constellation integrated network architecture based on software definition network (SDN) and network function virtualization (NFV), the resource requirements and resource constraints of the virtual network function (VNF) are comprehensively considered to build the 5G low orbit constellation network slice reliability mapping model, and the reliability mapping model parameters are trained and learned by using deep reinforcement learning, solve the problem of state space explosion in the reliability mapping process of 5G low orbit constellation network slices. In addition, node backup and link backup strategies based on importance are adopted to solve the problem that VNF/link reliability is difficult to meet in the reliability mapping process of 5G low orbit constellation network slice. The experimental results show that this method improves the network throughput, packet loss rate and intra slice traffic of 5G low orbit constellation, and can completely repair network faults within 0.3 s; For different number of 5G low orbit constellation network slicing requests, the reliability of this method remains above 98%; For SFC with different lengths, the average network delay of this method is less than 0.15 s.

2218: Surface-guided SBRT of ultracentral lung tumors: a possible backup strategy for MR-guided SBRT

2218: Surface-guided SBRT of ultracentral lung tumors: a possible backup strategy for MR-guided SBRT

Data Resilience: Secure Emergency Backup on Cloud

In the dynamic landscape of cloud computing, ensuring the resilience and availability of data is paramount, particularly in emergency situations such as cyberattacks, system failures, or natural disasters. This abstract presents a comprehensive examination of emergency backup strategies tailored specifically for cloud environments. It delves into the challenges associated with data loss and downtime, emphasizing the critical need for proactive measures to mitigate risks and safeguard valuable data assets. By exploring various backup methodologies including incremental backups, differential backups, and snapshot-based backups, this abstract provides insights into the diverse approaches available for creating robust data redundancy in the cloud. Furthermore, it discusses the importance of geographical redundancy, data encryption, and access controls in enhancing the security and integrity of backup data. Additionally, emerging technologies such as blockchain-based backup solutions and AI-driven anomaly detection systems are explored as potential avenues for further enhancing data resilience in the cloud. By adopting a proactive approach to emergency data backup, organizations can fortify their cloud infrastructures against unforeseen disruptions and ensure the continuous availability and integrity of their critical data assets

Redact4Trace: A solution for auditing the data and tracing the users in the redactable blockchain

With the introduction of the General Data Protection Regulation and the advent of the Blockchain 3.0 era, redactable blockchain have become a popular area of research. However, auditing harmful data on redactable blockchain has become an urgent problem to be solved to promote redactable blockchain. Moreover, tracing the identity of users who submit harmful data is a concerning problem that urgently needs to be solved. To address these issues, we propose Redact4Trace, a solution for tracing and auditing data in redactable blockchains. In Redact4Trace, transactions are the unit for minor data editing and redaction, ensuring fine-grained data editing and access. We have designed a data auditing scheme based on the unique characteristics of redactable blockchains. This scheme, which uses a chameleon hash, depends only on the transaction’s hash and effectively protects user privacy. We have also designed an identity tracing scheme based on bilinear maps. Users must use the bilinear mapping to compute address information and store it in the transaction for identity tracing. If the identity information in the transaction is altered, our backup scheme based on the discrete logarithm problem can still trace the user’s identity effectively. Security analyses and experimental results confirm that Redact4Trace is both secure and efficient.

The contribution of mRNA targeting to spatial protein localization in bacteria.

About 30% of all bacterial proteins execute their function outside of the cytosol and must be inserted into or translocated across the cytoplasmic membrane. This requires efficient targeting systems that recognize N-terminal signal sequences in client proteins and deliver them to protein transport complexes in the membrane. While the importance of these protein transport machineries for the spatial organization of the bacterial cell is well documented in multiple studies, the contribution of mRNA targeting and localized translation to protein transport is only beginning to emerge. mRNAs can exhibit diverse subcellular localizations in the bacterial cell and can accumulate at sites where new protein is required. This is frequently observed for mRNAs encoding membrane proteins, but the physiological importance of membrane enrichment of mRNAs and the consequences it has for the insertion of the encoded protein have not been explored in detail. Here, we briefly highlight some basic concepts of signal sequence-based protein targeting and describe in more detail strategies that enable the monitoring of mRNA localization in bacterial cells and potential mechanisms that route mRNAs to particular positions within the cell. Finally, we summarize some recent developments that demonstrate that mRNA targeting and localized translation can sustain membrane protein insertion under stress conditions when the protein-targeting machinery is compromised. Thus, mRNA targeting likely acts as a back-up strategy and complements the canonical signal sequence-based protein targeting.

Hemodynamics in pig-to-baboon heterotopic thoracic cardiac xenotransplantation: Recovery from perioperative cardiac xenograft dysfunction and impairment by cardiac overgrowth.

Orthotopic cardiac xenotransplantation has seen notable improvement, leading to the first compassionate use in 2022. However, it remains challenging to define the clinical application of cardiac xenotransplantation, including the back-up strategy in case of xenograft failure. In this regard, the heterotopic thoracic technique could be an alternative to the orthotopic procedure. We present hemodynamic data of heterotopic thoracic pig-to-baboon transplantation experiments, focusing on perioperative xenograft dysfunction and xenograft overgrowth. We used 17 genetically modified piglets as donors for heterotopic thoracic xenogeneic cardiac transplantation into captive-bred baboons. In all animals, pressure probes were implanted in the graft's left ventricle and the recipient's ascending aorta and hemodynamic data (graft pressure, aortic pressure and recipient's heart rate) were recorded continuously. Aortic pressures and heart rates of the recipients' hearts were postoperatively stable in all experiments. After reperfusion, three grafts presented with low left ventricular pressure indicating perioperative cardiac dysfunction (PCXD). These animals recovered from PCXD within 48h under support of the recipient's heart and there was no difference in survival compared to the other 14 ones. After 48h, graft pressure increased up to 200mmHg in all 17 animals with two different time-patterns. This led to a progressive gradient between graft and aortic pressure. With increasing gradient, the grafts stopped contributing to cardiac output. Grafts showed a marked weight increase from implantation to explantation. The heterotopic thoracic cardiac xenotransplantation technique is a possible method to overcome PCXD in early clinical trials and an experimental tool to get a better understanding of PCXD. The peculiar hemodynamic situation of increasing graft pressure but missing graft's output indicates outflow tract obstruction due to cardiac overgrowth. The heterotopic thoracic technique should be successful when using current strategies of immunosuppression, organ preservation and donor pigs with smaller body and organ size.

A review on MOFs synthesis and effect of their structural characteristics for hydrogen adsorption.

Climate change is causing a rise in the need to transition from fossil fuels to renewable and clean energy such as hydrogen as a sustainable energy source. The issue with hydrogen's practical storage, however, prevents it from being widely used as an energy source. Current solutions, such as liquefied and compressed hydrogen storage, are insufficient to meet the U.S. Department of Energy's (US DOE) extensive on-board application requirements. Thus, a backup strategy involving material-based storage is required. Metal organic frameworks (MOFs) belong to the category of crystalline porous materials that have seen rapid interest in the field of energy storage due to their large surface area, high pore volume, and modifiable structure. Therefore, advanced technologies employed in the construction of MOFs, such as solvothermal, mechanochemical, microwave assisted, and sonochemical methods are reviewed. Finally, this review discussed the selected factors and structural characteristics of MOFs, which affect the hydrogen capacity.

Design and Development of an Automated Product Categorization Software: AI-Driven Solutions for E-Commerce Platforms

This article outlines the design and development process of an automatic product categorization software intended for use in e-commerce and online marketplace platforms. The project aims to tackle the urgent issue of effectively classifying a wide range of products within digital markets. By utilizing artificial intelligence (AI) and machine learning methodologies, the software effectively analyzes product descriptions, enabling users to seamlessly incorporate products through automated categorization. The significance of the project is rooted in its ability to guarantee the accuracy and consistency of category hierarchies, automate the process of categorizing, and improve the overall user experience. The main goals involve the process of project planning, data collecting, and preparation. Machine learning models have been built and subsequently incorporated to facilitate the study of product descriptions. Through strict evaluation and optimization processes, a high level of accuracy and efficiency is achieved, resulting in several anticipated benefits. These benefits cover automated product categorization, enhanced user experience, and the potential for online platforms to gain a competitive edge. The key elements of innovation involve AI-driven textual analysis, learning methodologies grounded in data, and the ability to adapt to diverse industry contexts. Precautions and backup strategies are implemented to tackle technical issues, including the selection of machine learning libraries and algorithms, ensuring data quality, and integrating with various platforms. The success criteria encompass the objective of achieving a minimum prediction accuracy rate of 90%, optimizing business efficiency, enhancing user pleasure, and ensuring smooth system functioning. This project is a significant contribution to the field of product categorization inside the digital marketplace, as it provides automation, accuracy, and efficiency, ultimately resulting in an enhanced user experience.

A Study on Data Protection in Cloud Environment

Data protection in the online environment pertains to the safeguarding of sensitive or important data kept, analyzed, or sent in cloud-based systems. It entails assuring data confidentiality, integrity, and availability, as well as adhering to appropriate data protection requirements. In a nutshell, cloud data protection seeks to protect data against unauthorized access, deletion, or breaches while retaining its accuracy and accessible to authorized users. This is accomplished in the cloud environment using various security measures, encryption approaches, access controls, disaster recovery and backup processes, and constant monitoring and threat detection. The research significance of data protection in the cloud environment can be summarized as follows: Security and Privacy: Research in data protection in the cloud helps address the security and privacy concerns associated with storing and processing sensitive data in cloud-based systems. It explores and develops advanced security mechanisms, encryption techniques, and access controls to protect data from unauthorized access, data breaches, and privacy violations. Trust and Confidence: Research in data protection contributes to building trust and confidence in cloud computing. By developing robust security solutions and demonstrating their effectiveness, research helps alleviate concerns about data security and privacy, fostering greater adoption of cloud services by organizations and individuals. Compliance and Regulations: Cloud computing often involves compliance with data protection regulations and industry standards. Research in this area explores the legal and regulatory aspects of data protection in the cloud and helps organizations understand and comply with relevant requirements. Data Resilience and Recovery: Research in data protection focuses on ensuring data resilience and developing efficient data recovery mechanisms in the cloud. It explores backup and disaster recovery strategies, data replication techniques, and data loss prevention methods to minimize downtime, recover data promptly, and maintain business continuity in the event of system failures or disasters. By addressing these research areas, studies on data protection in the cloud environment contribute to enhancing security, privacy, compliance, and resilience in cloud computing. They provide valuable insights, practical solutions, and guidelines for organizations and service providers to protect data effectively and maintain the trust of users in cloud-based services. The weighted product method approach is commonly used to choose the best data protection in cloud environment. CCSS1, CCSS2, CCSS3, CCSS4, CCSS5 data visibility, data integrity, Maintains compliance, Data security, Data storage. From the result it is seen that CCSS2 got highest rank whereas CCSS5 got lowest rank According to the results, CCSS2 was ranked first.

Exploring the feasibility of introducing triple artemisinin-based combination therapy in the malaria treatment policy in Vietnam

BackgroundThis study investigates the processes regarding changing malaria treatment policies in Vietnam. Moreover, it explores the feasibility of introducing triple artemisinin-based combination therapy (TACT) in Vietnam to support the national malaria control and elimination plan.MethodsData were collected via 12 in-depth interviews with key stakeholders, combined with a review of policy documents.ResultsTACT is considered as a useful backup strategy in case future treatment failures with current artemisinin-based combination therapy (ACT) would occur. Moreover, TACT is also considered as a promising strategy to prevent the re-establishment of malaria. However, regulatory procedures and implementation timelines for TACT were expected to be lengthy. Therefore, strategies to engage national decision-makers, regulators, and suppliers should be initiated soon, stipulating the benefits of TACT deployment. In Vietnam, a procedure to apply for an import permit without registration that has previously been applied to the introduction of artesunate-pyronaridine was proposed to accelerate the introduction of TACT. Global-level support through the World Health Organization recommendations and prequalification were considered critical for supporting the introduction of TACT in Vietnam.ConclusionsAppropriate approach strategies and early stakeholder engagement will be needed to accelerate the introduction of TACT in Vietnam.

Optimization model for low-carbon supply chain considering multi-level backup strategy under hybrid uncertainty

When constructing a supply chain, the profit, environmental impact, and hybrid uncertainties the supply chain faces should be considered. This research investigates the problem of low-carbon supply chain design under hybrid uncertainty, where demand is regarded as a stochastic variable, supply and transportation disruptions are regarded as uncertain events, and the coefficient of emission reduction capacity of suppliers is regarded as an uncertain variable. Based on the probability theory and uncertainty theory, a mixed-integer optimization model is constructed to handle the disruption risk by utilizing a multi-level backup strategy and to reduce carbon emissions by investing in suppliers. This model guarantees that manufacturers’ demand is satisfied to a given confidence level, manufacturers prefer to construct a supply chain within the acceptable supply chain risk, the emission reduction investment scheme and the supply decision to manufacturers are determined to maximize the profit of the supply chain. To facilitate the solution, we perform deterministic equivalent transformation of stochastic and uncertainty constraints, linearize the nonlinear constraints, and analyze the mathematical properties of the model. Finally, the validity of the proposed model is verified by case studies. The results show that although the larger the supply levels, that is, the more priority levels of suppliers, the more beneficial it is to improve the reliability, too large supply levels will reduce profits. The reasonable setting of the supply levels can optimize the emission reduction investment scheme. In addition, the confidence level of carbon emission should be set within a certain range to avoid the disparity between profit growth and emission reduction. Finally, the greater the belief degree of disruption or the lower the emission reduction capacity of suppliers, the more significant the effect of a multi-level backup strategy.

Deep Brain Stimulation for Focal or Segmental Craniocervical Dystonia in Patients Who Have Failed Botulinum Neurotoxin Therapy-A Narrative Review of the Literature.

(1) Background: The first-line treatment for patients with focal or segmental dystonia with a craniocervical distribution is still the intramuscular injection of botulinum neurotoxin (BoNT). However, some patients experience primary or secondary treatment failure from this potential immunogenic therapy. Deep brain stimulation (DBS) may then be used as a backup strategy in this situation. (2) Methods: Here, we reviewed the current study literature to answer a specific question regarding the efficacy and safety of the use of DBS, particularly for cervical dystonia (CD) and Meige syndrome (MS) in patients with documented treatment failure under BoNT. (3) Results: There are only two studies with the highest level of evidence in this area. Despite this clear limitation, in the context of the narrowly defined research question of this paper, it is possible to report 161 patients with CD or MS who were included in studies that were able to show a statistically significant reduction in dystonic symptoms using DBS. Safety and tolerability data appeared adequate. However, much of the information is based on retrospective observations. (4) Conclusions: The evidence base in this area is in need of further scientific investigation. Most importantly, more randomized, controlled and double-blind trials are needed, possibly including a head-to-head comparison of DBS and BoNT.