Unforeseen Events Research Articles

Drug-induced liver injury during valproic acid and cenobamate coadministration: a direct consequence or an unforeseen event?

Drug-induced liver injury during valproic acid and cenobamate coadministration: a direct consequence or an unforeseen event?

U-Space Contingency Management Based on Enhanced Mission Description

Loss of communication, low battery, or bad weather conditions (like high-speed wind) are currently managed by performing a return to launch (RTL) point maneuver. However, the execution of this procedure can pose a safety threat since it has not been considered within the mission planning process. This work proposes an advanced management of contingency events based on the integration of a new U-space service that enhances mission description. The proposed new service, deeply linked to demand capacity balance and strategic deconfliction services, assigns alternative safe landing spots by analyzing the planned mission. Two potential solutions are characterized (distinguished primarily by the number of contingency vertiports assigned): contingency management based on the assignment of a single alternative vertiport to each mission (static) or the allocation of a set of different contingency vertiports that are valid during certain time intervals. It is proven that this enhanced mission planning could ensure that U-space volumes operate in an ultra-safe system conditions while facing these unforeseen events, highlighting its importance in high-risk scenarios like urban air mobility deployments.

IDENTIFIKASI FAKTOR DAN TANTANGAN DI SEKTOR PERUNGGASAN UNTUK MENINGKATKAN KELINCAHAN BISNIS DI AGROINDUSTRI INDONESIA: TINJAUAN LITERATUR

The poultry industry in Indonesia, especially the poultry sector, plays a crucial role in ensuring national food security by providing essential animal protein sources. Therefore, business agility is highly necessary to address fluctuating demand issues that can change unpredictably. Many industries in this sector have faced setbacks due to unforeseen shifts in demand. However, in implementing business agility, numerous factors need consideration, such as traditional organizational structures, bureaucratic processes that impede change, and a corporate culture resistant to transformation. This research aims to identify various challenges faced by companies in achieving business agility through a literature review using Publish or Perish software and manual searches on Google Scholar, resulting in the selection and analysis of 23 relevant journals. The findings from the literature review indicate that effective supply chain management, innovative management leadership, technological automation, adaptability to unforeseen events, investment in employee development, and a deep understanding of customer needs are key factors influencing business agility in the poultry industry in Indonesia.

The covert and overt role of art in landscape partnership

Although in recent history the arts have received substantial attention as a conduit for memorable artworks to draw attention to issues that may be coincidental to the artists original intention, this does not acknowledge the arts as equal partner in a shared enterprise but more to facilitate the accessibility of difficult concepts. This essay explores the capability for the visual arts to increase understanding of issues as disparate as the loss of rural landscape to urban development and the incremental effects of sea level rise upon coastal communities. With increased specialisation of disciplinary practice there is an incapacity to address the multi-dimensional character of practical challenges, particularly in the matter of the societal impacts of environmental change. This demands greater flexibility in approach to policy and an understanding that the increasing frequency of unforeseen events beg the question of our cultural preparedness to evolve a new paradigm for knowledge sharing.

A stochastic hepatitis B model with media coverage and Lévy noise

Globally, it is evident that vaccination and social media significantly influence the spread of diseases. Research has demonstrated that the spread of diseases can be affected by unforeseen events. Therefore, a stochastic hepatitis B virus (HBV) dynamical model is constructed that incorporates media coverage, while also Lévy noise is included. Itô's formula and the Lyapunov function approach are employed to analyze the existence of a positive global solution. Furthermore, the necessary conditions for disease eradication as well as long-term survival are also established to facilitate the general understanding. The statistics indicate that the media's impact is not immediate and does not lead to disease eradication. To effectively manage the spread of diseases, it is essential to employ a combination of significant noise disruption and a low rate of decline in vaccine effectiveness. Numerical simulations are conducted to demonstrate the analytical findings.

Innovative ways of dealing with unforeseen events

Innovative ways of dealing with unforeseen events Dorothy Sutherland Olsen and Lisa Scordato from the Nordic Institute for Studies of innovation, research and education, explore innovative ways of dealing with unforeseen events. Increasing interest in the challenges experienced by public and private organisations when unforeseen events occur, has prompted a research project looking into potential ways of developing relevant competence to deal with such events. The project has been inspired by earlier studies on innovation where change is seen, not only as a challenge, but also as an opportunity. Unforeseen events have always been around, ready to disrupt everyday routines in organisations. These events are not always completely unforeseen, but the scale is often unknown, and we can rarely predict exactly when these events might occur. These events can be pandemics, terror incidents or natural catastrophes; they can also be new technologies, new green ways of working or perhaps more local events like an employee leaving confidential documents on the bus or a construction team dropping a six-tonne oil installation. All these events require a rapid response; speed is of the essence, and errors and delays must be avoided.

Refinement method of equivalent source power level determination for traffic noise in urban noise mapping

For traffic noise prediction, the predictive models of source power level determination commonly in use are the Technical Guidelines for Noise Impact Assessment in China or the Calculation of Road Traffic Noise model in the United Kingdom, which incorporate traffic flow and car speeds. However, the accuracy of these models is often compromised due to urban traffic's complexity, vehicle diversity, and unforeseen events. This study investigates a refinement method based on noise on-site measurement and aforementioned approaches for equivalent source power level determination for traffic noise in urban noise mapping. In the study, onsite measurements are conducted to collect noise and traffic data, and source power level calculated by refinement method is validated using measurement data. Different prediction methods are employed for measurement sites calculations. By comparisons between predictions with noise on-site measurement data, the refinement method proposed in the study demonstrates a significant accuracy enhancement in traffic noise prediction over previous models for determining equivalent source power level. This enhancement highlights the efficacy of adopting noise measurement-based methods for setting traffic noise source power levels, leading to more precise traffic noise predictions in complex urban settings, particularly in areas surrounding urban arterial roads.

Performance of agricultural extension agents in Indonesia: evidence from a nationally representative survey

ABSTRACT Purpose This study analyses the performance of field extension agents in Indonesia using a multi-dimensional performance indicator. Methodology The study uses data from an online survey of a nationally representative sample of 1,974 field extension agents. Binary and ordinal probit models are utilised to analyse the performance of extension agents and the factors influencing it based on a multi-dimensional measurement of performance. Findings and practical implications Improved performance is associated with increased career progression, availability of external funds, the opportunity to collaborate, involvement in government programs, implementation of disciplinary measures and a diversified use of advisory methods. To promote performance, the government should encourage and improve the institutional arrangements. Theoretical implications This study introduces a multidimensional measurement that covers timeliness, targeting and content dimensions while capturing both the institutional arrangement and demographic characteristics in explaining performance. Originality/value This study introduces an online survey for extension agents that encompasses a nationally representative sample, thereby demonstrating this cost effective approach designed for rapid data collection and facilitating the measurement of performance during unforeseen events, such as the Covid-19 pandemic. Its broad applicability allows for a thorough analysis of agricultural extension agents’ performance in a variety of contexts.

Model-based assembly process planning for flexible aircraft cabin architectures

The configuration and equipment of an aircraft cabin has a significant impact on the passenger’s flight experience. To meet the needs of passengers and improve the flight experience, airlines repeatedly demand customised adaptations to the cabin design. The implementation of these changes requires a high degree of flexibility in production and can lead to difficulties in setting up a fixed final assembly line. In addition, unforeseen events and changes in the OEMs’ supply chain require a rapid response in aircraft production to be able to deliver on time. Digitalisation in product development and production planning makes it possible to overcome these challenges and makes an important contribution to flexibility, time and cost efficiency. This paper presents a digital approach to modelling and flexible planning of assembly processes of the cabin. To this end, aircraft design data is automatically linked to the assembly system to react quickly to design changes in the assembly planning process. The integration is realised in a system architecture model depicted with the systems modelling language (SysML). The architecture model follows the formal process description defined in VDI3682. A planning algorithm then uses the production architecture parameters to optimise the assembly processes, e.g. in terms of time. The approach presented is demonstrated using the example of scheduling the pre-assembly processes of the "crown module". The latter includes all structural and functional components above the window panels, such as overhead bins, electrics and air conditioning. The results show how changes in aircraft and cabin design or in the production plant and resources can be flexibly evaluated. This allows conceptual changes to be evaluated and traded before the cabin design is frozen and transferred to real production. These advantages contribute to the time and cost optimisation of aircraft production. This work thus makes a valuable contribution to the further development of digital solutions in aircraft production.

DISTANCE LEARNING EXIT ECONOMIC MODEL

At the beginning of 2020, with the onset of the pandemic, the traditional learning environment for learners drastically changed globally. Since then, most students/teachers have started and practiced distance and virtual learning/teaching. Thus, a technological breakthrough in virtual learning has followed. In connection with this, many countries worldwide have commenced allocating additional financing and funds for educational institutions' technological improvement and development. The long-term stay in distance learning has revealed and highlighted new problems students face: their knowledge level has decreased, they lack socialization skills, and they face psychological and physical health problems. Due to this negative impact on students, a need to research and evaluate how much the EU countries allocated to solve the distance learning-caused problems and what programs or models they prepared has emerged and encouraged further studies. The research has found that many countries increased their allocations very minimally, e.g., 0.0.1%, but some increased their available budgets to 32%. Notably, most countries did not separate distance learning exit funding from distance learning preparation funding. Based on the problems the countries saw, only a few states identified withdrawal from distance learning as a problem. Considering this, we set ourselves the goal to evaluate exit models from distance learning and allocated funding amounts. To stabilize the impact of unforeseen events, such as epidemics, pandemics, military conflicts, etc., on learning processes, it is necessary to have sustainable solutions for managing learning processes in such situations. As revealed by the COVID-19 situation, the stability and continuity of the learning process remains very important even in emergencies. Stable and continuous learning can be ensured by practising sustainable distance learning, which must be based on sustainable tools. The results of this research are significant in terms of improving distance learning and providing qualitative and sustainable education. The current situation stimulates hybrid learning, which is increasingly becoming the foundation of sustainability in the education sector. Thus, to reverse the damage caused by distance learning and create a sustainable environment for blended learning, it is necessary to eliminate the negative effects of distance learning. This challenge will lead to the need for new sustainable blended learning programs. The following objectives were planned to achieve the goal: · to evaluate the global practice of exit from distance learning in the context of sustainability; · to determine the scope of funding for pandemic management; · to evaluate the amounts of funding allocated to manage pandemic-caused consequences and the GDP ratio. Research methods: mathematical-statistical analysis, empirical analysis, and analysis of scientific literature.

YOUTH OF KAZAKHSTAN: NAVIGATION INTO THE FUTURE (BASED ON THE RESULTS OF AN EMPIRICAL RESEARCH)

The crises of the last several decades highlight the fragility of many societies, emphasizing a complicated and uncertain future. These concepts focus researchers' attention on identifying and mitigating the risks and potential effects of unforeseen events on society. The article offers the findings of focus group discussions about the future among young Kazakhstani citizens, ages 18 to 29. The authors identify important trends and images of future through discourse analysis. In Kazakhstan-2044, political freedom and freedom of speech are considered to be essential political values. The primary issues facing society in the future might be corruption, emigration—particularly of educated youth—and people's disregard for their professional obligations. The significance of intelligence, knowledge, and advanced technology are recognized as the most societal factors in the development. The ideas of this paper can be used in various fields, including politics, economics, and social aspects.

Research on the Social Mobilization Mechanism for Improving Emergency Response Capability in Unforeseen Events

This paper investigates the social mobilization mechanism in emergency response through the integration of emergency management and social mobilization theories with various scientific analysis methods. The aim is to explore the importance and development prospects of a reasonable and scientific social mobilization mechanism for enhancing emergency response capabilities in sudden events and to seek practical and valuable improvement measures to enhance the effectiveness of emergency management in emergency response and rescue.

METHODOLOGICAL APPROACHES TO TAX AUDIT: THE IMPERATIVE OF ANALYSIS UNDER THE CONDITION OF UNCERTAINTY OF THE TERM

Introduction. A tax audit is a comprehensive examination of the financial activities of business entities with the aim of assessing compliance with tax legislation and identifying possible violations. In modern conditions, when economic instability and constant changes in tax legislation are becoming the norm, ensuring the effectiveness and accuracy of tax audits requires the use of complex methodological approaches. One of the key problems of the tax audit is the uncertainty of terms, which makes it difficult to plan and conduct audit procedures. Uncertainty can be caused by various factors, including changes in legislation, economic crises, force majeure and other unforeseen events. This uncertainty creates additional challenges for auditors who must adapt their methodological approaches to new conditions. The purpose of the article is considering methodological approaches to the interpretation of tax audits, identify their advantages and disadvantages. To justify the analysis as an imperative element of the tax audit method in the system of control over compliance with tax legislation. Methods. The following methods were used in the study of methodological approaches to tax audits in conditions of uncertainty of terms: analysis of literary sources. A systematic review of scientific publications, articles, monographs and legal acts related to tax audit was conducted. This made it possible to identify existing approaches and theoretical foundations; Comparative analysis: a comparison of different methodological approaches used in tax audits in different countries and conditions was made. This helped identify the most effective practices and adapt them to conditions of uncertainty. Results. A detailed substantiation of methodological approaches to the interpretation of tax audit from the standpoint of linguistic semantics strengthens the opinions of those scientists and practitioners who believe that in parallel with independent audit and audit services in the field of taxation, the concept of tax audit can be used for inspections carried out by tax authorities. In this case, both tax authorities and independent auditors have the right to use the concept of tax audit and have the right to conduct it. However, in our opinion, it is more appropriate to use two separate terms, in particular, such as "state tax audit" and "independent tax audit".

Multi-scale collaborative modeling and deep learning-based thermal prediction for air-cooled data centers: An innovative insight for thermal management

Investigating the data center (DC) thermal environment and temperature distribution is crucial to responding to unforeseen events such as equipment failure or environmental changes. However, building full-scale simulation models from DC room level to chip level faces significant challenges. In this paper, we propose a distinctive approach that combines multi-scale collaborative modeling with deep learning techniques for thermal prediction in air-cooled DCs. By taking the simulation results of the parent model as the boundary conditions of the child model, we constructed the DC multi-scale simulation model, which significantly reduces the model complexity and computational resources. Leveraging experimental data, the models at different scales were validated separately. The effects of different cooling strategies, air supply temperatures and air supply flow rates on multi-scale simulation models were investigated. Based on the parametric simulation approach, datasets for training data-driven models are constructed. Simultaneously, we propose the CNN-BiLSTM-Attention neural network model to predict the maximum CPU temperature and optimize the hyperparameters of the neural network through by Bayesian optimization. The prediction results of the coupled multi-scale model and the deep learning prediction model show that the absolute error is controlled within ±0.1 K, and the R2 value of the model evaluation metric is as high as 0.9899. Herein, the results provide valuable insights for enhancing thermal management in air-cooled DCs, paving the way for more efficient and resilient DC operations in the future.

Unravelling the effects of short-term starvation and pH disturbances in stable volatile fatty acids production

The successful upscaling of anaerobic fermentation (AF) still relies on ensuring the stable production of volatile fatty acids (VFAs) in high concentrations and yields. The unforeseen events taking place at industrial scale can compromise the AF stability, thereby decreasing the cost-effectiveness of the process. To assess process stability against disturbances and identify AF failure indicators, this investigation explored the effect of starvation and pH control failure in a continuous reactor. The starvation disturbance did not affect AF performance and methanogenesis was not restored, confirming the relevance of selecting proper conditions (25 °C and pH 6.5) to ensure methanogenesis suppression. By contrast, the uncontrolled pH provoked a pH drop to 4.5, limiting the acidogenesis metabolisms and modifying the metabolites profile due to microbiome reshape. Lactobacillus, and members of Lactobacillaceae, Lactobacillales, and Bifidobacteriaceae dominated the microbiome in the pH disturbance, revealing lactic, succinic and oxalic acids as warning indicators of the acidogenesis failure. Nevertheless, the AF was completely recovered after the disturbances evidencing the microbiome robustness against pH range between 4.5 and 5.

Multi-objective rescheduling of job shop scheduling problems in manufacturing using Quantum Annealing

Unforeseen events in manufacturing necessitate rescheduling to minimize lead times and maintain continuous production. Reducing rescheduling effort is also crucial otherwise additional setup times are incurred. This paper extends a dynamic rescheduling workflow, previously demonstrating success with Quantum Annealing through a multicriterial optimization. It introduces a second objective function considering rescheduling effort alongside makespan. The study addresses job arrivals and machine failures, employing a binary quadratic model for optimization. Results highlight the superiority of Quantum Annealing for larger problems compared to classical metaheuristics. Nevertheless, parameter selection complexities urge further exploration such as exploring deep learning techniques to tackle this challenge.

Navigating Natural Disaster Disruption in the Hospitality Sector: Insights From the September 8, 2023 Earthquake in Morocco

Purpose: This case study delves into the specific hurdles encountered by hotel managers in Marrakech during and after the September 8, 2023 earthquake, alongside the strategies deployed to tackle these challenges. Moreover, it aims to unravel the intricacies faced by risk claims professionals in processing claims and evaluating risks post-earthquake, aiming to formulate suggestions for enhancing disaster risk management within the hospitality domain. Design/Methodology/Approach: Semi-structured interviews were conducted with 27 hotel managers and five insurance professionals in Morocco, all intimately engaged in handling or alleviating the impacts of the earthquake on the hospitality sector. Thematic analysis was utilized to pinpoint key challenges, responses initiated by hotel managers, and insights provided by risk claims professionals. Findings: The study underscores that the earthquake caused significant operational disruptions and financial strains on hotels, resulting in cancellations, revenue loss, and infrastructure damage. Hotel managers responded with prompt evacuation, safety protocols, damage assessment, and customer communication strategies. Risk claims professionals underscored the significance of comprehensive insurance coverage, streamlined claims processes, and advanced risk modeling techniques to mitigate financial risks and bolster disaster resilience within the hospitality sector. Originality/Value: This study furnishes original insights into the challenges faced by hotel managers and risk claims professionals post-seismic event, illuminating the complexities of disaster risk management within the hospitality industry. The recommendations proposed contribute to the formulation of effective strategies and protocols for navigating similar unforeseen events in the future.

A multi-objective model for integrated supplier order allocation and supply chain network transportation planning decision-making

Effective supplier order allocation (SOA) and transportation planning (TP) are critical for the smooth operation of supply chains, especially in dynamic markets with evolving customer demands. While previous research has made significant strides in addressing these areas individually, studies that integrate both aspects while considering a comprehensive set of objectives are limited. This study introduces an innovative multi-objective model that concurrently addresses total operational costs, supplier defect rates, sustainability performance, and supply chain network disruption risks. The model applies an augmented max–min approach of fuzzy multiple objective linear programming (AMM-FMOLP), which enhances overall utility while ensuring balanced performance across all objectives. The inclusion of all five objectives in the model is essential for a holistic evaluation of supply chain performance. The model’s effectiveness and practicality are validated through a case study involving a computer numerical control (CNC) machine tool assembly company, under various scenarios. Additionally, sensitivity analysis reveals how adjustments in supply chain structure can further improve performance. Moreover, the execution process of this study does not require expert intervention, making it a unique data-driven decision model particularly suitable for intelligent supply chain management and decision-support systems. This approach enhances the flexibility and resilience of supply chains, enabling them to effectively respond to unforeseen events and minimize their impact on business operations, especially in volatile global markets.

Optimization of Scheduling in Reconfigurable Production Systems: An Approach Based on Intelligent Petri Nets

This article proposes an innovative approach to optimizing scheduling in reconfigurable production systems, with a focus on minimizing resource allocation in a dynamic environment while considering time constraints and resource availability. We present a methodology based on intelligent Petri nets to model and solve this complex problem. Our approach aims to maximize operational efficiency and flexibility of production systems while ensuring optimal performance in the face of unforeseen events and changing market demands. We illustrate the effectiveness of our approach through a case study in a real industrial context, demonstrating the tangible benefits it offers in terms of optimizing production processes and reducing costs.

Conceptualization of territorial resilience potential indicators to coastal hazards through the use of unmanned aerial vehicles

Major natural hazards in recent decades have led to a revisiting of the concept of resilience, particularly in order to analyze traditional models of response to an unforeseen event and post-crisis management mechanisms. For resilience to be an applicable/operational concept to guide management and inform decisions, it must ultimately be characterized for its assessment. This assessment can be done through the identification of indicators specifically contextualized to the study site and object of study. However, today, operationalizing of the concept of resilience tends to draw on annual censuses or aggregated data, providing a generalized large scale view of the territorial resilience potential. The objective of this study is to identify a table of Territorial Resilience Potential (TRP) indicators to coastal hazards applied to coastal island territories, supplied by data from Unmanned Aerial Vehicles (UAVs) to allow for rapid and site specific data acquisition for repetitive surveys. This acquisition method makes it possible to calculate a number of relevant indicators for assessing the resilience potential of coastal areas. In particular, it allows rapid updating of data following major meteorological events and identification of hot and cold spots of resilience potential of a specific study site. To demonstrate the applicability of this method to island territories, the island of Bora Bora in French Polynesia was used as a case study. Finally, these kinds of results can be fed through a spatial decision support system to help decision-makers choose an adaptation and protection strategy in order to move towards resilient territories, over a long period of time.