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Foot-and-mouth disease (FMD) is a highly contagious disease of livestock caused by the FMD virus (FMDV). It is not dangerous to humans but can cause severe disruption to the farming sector and hampers trade in animals and animal products. Given the characteristic of transmissibility of the virus, the legislation in force in the European Union requires that some control activities be initiated in peacetime: the so-called “emergency preparedness”. As part of a research project on FMD, a dynamic transmission model was developed to test the effectiveness of the main control strategies in different livestock settings in Italy. This manuscript focuses on the control of the disease in densely populated livestock areas (DPLAs). Reduction in farm density was simulated to identify a threshold density compatible with disease control in the study area and to understand whether this was acceptable in terms of the sustainability of the livestock production system. Considering that in some municipalities the density of animals greatly exceeded the identified threshold, we adopted an original risk-based approach aimed at identifying farms which were most likely to play a central role in FMDV transmission. This approach has proven to be the most effective in controlling the spread of FMDV and can be proposed for practical applications where limited information on contacts between farms is available.

China frequently experiences natural disasters, making emergency language services a key link in information transmission, cross-lingual communication, and resource coordination during disaster relief. Traditional contingency plans rely on manual experience, which results in low efficiency, limited coverage, and insufficient dynamic adaptability. Large language models (LLMs), with their advantages in semantic understanding, multilingual adaptation, and scalability, provide new technical approaches for emergency language services. Our study establishes the country’s first generative evaluation index system for emergency language service contingency plans, covering eight major dimensions. Through an evaluation of 11 mainstream large language models, including Deepseek, we find that these models perform excellently in precise service stratification and resource network stereoscopic coordination but show significant shortcomings in legal/regulatory frameworks and mechanisms for dynamic evolution. It is recommended to construct a more comprehensive emergency language service system by means of targeted data augmentation, multi-model collaboration, and human–machine integration so as to improve cross-linguistic communication efficiency in emergencies and reduce secondary risks caused by information transmission barriers.

The increase in arrivals of new forest pests highlights the need for effective phytosanitary legislation and measures. This paper introduces legislation targeted at prevention and management of potential introductions of forest pests and pathogens. An overview is given on plant health regulations on global and regional level with detailed information on the situation in the European Union (EU). The current and new European legislation is discussed, and a particular focus is given on eradication and contingency plans for Fusarium circinatum. We identified key aspects relevant for the improvement of the efficacy of measures aimed to prevent alien pests.

One of the key issues in supply chain sustainability is the efficient usage of the available resources. At the same time, proactive supply chain design with disruption risk considerations frequently leads to a network redundancy which implies some resource reservations in anticipation of possible disruptions. Even if resilient supply chain design has received much attention in literature, there is a research gap in designing both resilient and sustainable supply chains. This study contributes to closing the given gap by proposing a novel methodological approach to modelling network redundancy optimization. This allows for simultaneous computation of both optimal network redundancy and proactive contingency plans, considering both supply dynamics and structural disruption risks. The novelties of this study are the integration of sustainable resource utilization and SC resilience based on coordination of structure- and flow-oriented optimization. The model uncovers a practical approach to analyze and optimize supply chain redundancy by varying processing intensities of resource consumption in the network according to supply and structural dynamics. This makes it possible to explicitly include the dynamics of resource consumption for contingency plan realization in disruption scenarios.

The risk of extreme climatic conditions leading to unusually low global agricultural production is exacerbated if more than one global ‘breadbasket’ is exposed at the same time. Such shocks can pose a risk to the global food system, amplifying threats to food security, and could potentially trigger other systemic risks1,2. While the possibility of climatic extremes hitting more than one breadbasket has been postulated3,4, little is known about the actual risk. Here we combine region-specific data on agricultural production with spatial statistics of climatic extremes to quantify the changing risk of low production for the major food-producing regions (breadbaskets) over time. We show an increasing risk of simultaneous failure of wheat, maize and soybean crops across the breadbaskets analysed. For rice, risks of simultaneous adverse climate conditions have decreased in the recent past, mostly owing to solar radiation changes favouring rice growth. Depending on the correlation structure between the breadbaskets, spatial dependence between climatic extremes globally can mitigate or aggravate the risks for the global food production. Our analysis can provide the basis for more efficient allocation of resources to contingency plans and/or strategic crop reserves that would enhance the resilience of the global food system.

A major threat for marine and coastal environment comes from oil spill accidents. Such events have a great impact on both the ecosystem and on the economy, and the risk increases over time due to increasing ship traffic in many sensitive areas. In recent years, numerical simulation of oil spills has become an affordable tool for the analysis of the risk and for the preparation of contingency plans. However, in coastal areas, the complexity of the bathymetry and of the orography requires an adequate resolution of sea and wind flows. For this reason, we present, to the best of the author’s knowledge, the first study on the subject adopting Large Eddy Simulations for both the low-atmosphere and sea dynamics in order to provide highly-resolved marine surface current and wind stress to the oil slick model, within a one-way coupling procedure. Such approach is applied to the relevant case of Kotor Bay (UNESCO heritage since 1979), in Montenegro, which is a semi-closed basin surrounded by mountains that is subject to an intense ship traffic for touristic purposes. Oil spill spots are tracked along ship paths, in two wind scenarios.

Since the beginning of the COVID-19 pandemic Universities around the world are taking rapid actions to ensure students learning continuity and secure the well-being of their students. This study aims at exploring the student’s e-learning experience in Jordanian Universities as well as e-learning readiness during the pandemic. While each university is unique, we hope our assessment can provide some insights into how well the student’s e-learning experience was during the pandemic. A structural online questionnaire was distributed, followed by descriptive analysis. Students from remote and disadvantaged areas primarily faced enormous challenges such as technological accessibility, poor internet connectivity, and harsh study environments. This study also highlights the role of electronic commerce in transforming distance learning. Further investments and contingency plans are needed to develop a resilient education system that supports electronic and distance learning throughout Jordan.

Purpose The COVID-19 pandemic showed that preestablished contingency plans and resilience practices were insufficient to cope with long-term and global disruptions. Companies thus struggled to develop capabilities that ensure their survivability during similar crises. Building on the adaptation-based view (ABV) of supply chain resilience, this study aims to offer an in-depth perspective on survivability in supply chains (SCs). Design/methodology/approach The paper empirically tests related relationships between adaptation capabilities and practices that ensure operational continuity. Responses from 252 organisations were collected and analysed using partial least squares structural equation modelling. Findings The results empirically support the ABV’s theoretical propositions and assess the possibilities of intertwining, digitalisation, a circular economy and maturity for the survivability of SCs. Research limitations/implications The derived insights are attractive for managers and researchers to foster supply chain survivability and contribute to the increasing efforts of middle-range theorising in logistics and supply chain management research. Originality/value To the best of the authors’ knowledge, this study is one of the first studies to define factors enhancing the survivability of SCs through the lens of the ABV.

At its core, preparation is about foresight. It involves understanding potential obstacles and addressing them before they arise. Whether it's thoroughly studying for an exam, drafting contingency plans for a business project, or simply packing an umbrella on a cloudy day, thinking ahead reduces the risk of failure and increases the likelihood of achieving our goals. Preparation also fosters confidence. When we know we've done everything possible to ready ourselves, we can approach challenges with a calm and focused mind. This confidence is crucial in high-pressure situations, where the ability to remain composed can lead to better decision-making and outcomes. Moreover, being prepared allows for adaptability.