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A centralised data envelopment analysis (DEA) approach optimises the resource usage for all the different units in an organization rather than for each unit separately (conventional DEA). This is particularly relevant for the Spanish airports controlled centrally by the Spanish airport authority rather than by individual airport managers. In this study, a non-oriented Slack-based inefficiency (SBI) DEA model is used in order to reallocate two transferrable inputs (namely, labour costs and operating costs) between the different airports. Firstly, we apply a conventional (i.e. non-centralised) non-oriented SBI model to identify the inefficient airports. Then, we apply the corresponding centralised DEA model to the inefficient units to maximise the potential improvements (slacks) obtained by reducing the total consumption of the inputs (allowing resource reallocation) and increasing total outputs. The results show how it is feasible to increase the total amount of passengers and cargo as well as the number of aircraft movements without increasing the total amount of inputs, just by reallocating them in an efficient way. Several progressively more relaxed scenarios have been considered, leading to larger total potential efficiency improvements. The model identifies airports that suffer from over-capacity and provide individual targets in each input and output to become more efficient. Sensitivity analysis to outliers or mavericks (i.e. airports with a strong specialisation) has been carried out. The size efficiency of individual airports as well as the overall company has also been studied. The potential efficiency gains and the optimal number of airports in a radical system restructuring have been computed and the optimal size operating point has been determined and compared with the actual inputs and outputs of the existing airports.

This work investigates life cycle costing analysis as a tool to estimate the cost of hydrogen to be used as fuel for Hydrogen Fuel Cell vehicles (HFCVs). The method of life cycle costing and economic data are considered to estimate the cost of hydrogen for centralised and decentralised production processes. In the current study, two major hydrogen production methods are considered, methane reforming and water electrolysis. The costing frameworks are defined for hydrogen production, transportation and final application. The results show that hydrogen production via centralised methane reforming is financially viable for future transport applications. The ownership cost of HFCVs shows the highest cost among other costs of life cycle analysis.

Unaffordable medical treatment and inflated drug prices have become a challenging issue for lawmakers worldwide. To reduce the financial burden and standardize the pharmaceutical market, the Chinese government has issued several detailed regulations, including the measures of drug recruitment and procurement in one and volume purchasing to not only ensure the high quality of approved drugs but also lower the cost of the production and sell procedure. In this work, to have a thorough overview of the enforcement of these regulations, we attempted to critically analyze the data of our hospital’s centralized procurement of drugs from 2019 to 2022. We identified some concerns, such as the difficulty in determining the “quantity” of drug procurement, out-of-stock of collectively procured drugs, difficulty in managing the preallocation of associated funds, incomplete centralized procurement systems, etc. Therefore, it is essential to promote a multidimensional strategy, including the combination of the medical insurance reform and drug centralized procurement policies, strict controlling of the forecast quantity of drugs to ensure stable drug supply, improvement of the relevant policies for retaining the surplus of centralized procurement drug medical insurance funds, secureness of the drug procurement system platform, and available reference and guidance for subsequent centralized quantity procurement of drugs.

ZigBee, a wireless technology standard for the Internet of Things (IoT) devices based on IEEE 802.15.4, faces significant security challenges that threaten the confidentiality, integrity, and availability of its networks. Despite using 128-bit Advanced Encryption Standard (AES) with symmetric keys for node authentication and data confidentiality, ZigBee’s design constraints, such as low cost and low power, have allowed security issues to persist. While ZigBee 3.0 introduces enhanced security features such as install codes and trust centre link key updates, there remains a lack of empirical research evaluating their effectiveness in real-world deployments. This research addresses the gap by conducting a comprehensive, hardware-based analysis of ZigBee 3.0 networks using XBee 3 radio modules and ZigBee-compatible devices. We investigate the following three core security issues: (a) the security of symmetric keys, focusing on vulnerabilities that could allow attackers to obtain these keys; (b) the impact of compromised symmetric keys on network confidentiality; and (c) susceptibility to Denial-of-Service (DoS) attacks due to insufficient protection mechanisms. Our experiments simulate realistic attack scenarios under both Centralised and Distributed Security Models to assess the protocol’s resilience. The findings reveal that while ZigBee 3.0 improves upon earlier versions, certain vulnerabilities remain exploitable. We also propose practical security controls and best practices to mitigate these attacks and enhance network security. This work contributes novel insights into the operational security of ZigBee 3.0, offering guidance for secure IoT deployments and advancing the understanding of protocol-level defences in constrained environments.

The replacement of conventional generation sources by DER creates the need to carefully manage the reactive power maintaining the power system safe operation. The principal trend is to increase the DER volume connected to the distribution network in the coming years. Therefore, the microgrid represents an alternative to offer reactive power management due to excellent controllability features embedded in the DER, which enable effective interaction between the microgrid and the distribution network. This paper proposes a microgrid–iterative reactive power management approach of power-electronic converter based renewable technologies for day-ahead operation. It is designed to be a centralised control based on local measurements, which provides the optimal reactive power dispatch and minimise the total energy losses inside the microgrid and maintain the voltage profile within operational limits. The proposed optimal-centralised control is contrasted against seven local reactive power controls using a techno-economic approach considering the steady–state voltage profile, the energy losses, and the reactive power costs as performance metrics. Three different reactive power pricing are proposed. The numerical results demonstrate the optimal microgrid–interactive reactive power management is the most suitable techno-economic reactive power control for the day–ahead operation.

(Series Information) European Papers - A Journal on Law and Integration, 2025 10(3), 709-719 | Article | (Abstract) This introduction aims to provide a concise bird-eye's view of the digitalisation of EU law enforcement from a fundamental rights perspective in view of the various legislative and case law developments in recent years. The introduction highlights the multiplicity of such avenues through the creation and consecutive reformation of highly sophisticated databases (Schengen Information System and Europol databases) and the proliferation of decentralised systems, such as the European Criminal Record Information System (ECRIS). It is noted that law enforcement heavily relies on the private sector not only for the processing of personal data in various contexts (telecommunication metadata, Passenger Name Records and money-laundering related data), but also for enforcing rules on online content moderation entrusting them with the task of ensuring a secure digital environment whilst safeguarding fundamental rights. The introduction notices also the progressive move to the use of algorithms in law enforcement, for instance, the processing of PNR data or online content moderation relies on such tools, amplifying the challenges for fundamental rights if such use is incompatible with fundamental rights.

The Internet of Things (IoT) has extended the internet connectivity to reach not just computers and humans, but most of our environment things. The IoT has the potential to connect billions of objects simultaneously which has the impact of improving information sharing needs that result in improving our life. Although the IoT benefits are unlimited, there are many challenges facing adopting the IoT in the real world due to its centralized server/client model. For instance, scalability and security issues that arise due to the excessive numbers of IoT objects in the network. The server/client model requires all devices to be connected and authenticated through the server, which creates a single point of failure. Therefore, moving the IoT system into the decentralized path may be the right decision. One of the popular decentralization systems is blockchain. The Blockchain is a powerful technology that decentralizes computation and management processes which can solve many of IoT issues, especially security. This paper provides an overview of the integration of the blockchain with the IoT with highlighting the integration benefits and challenges. The future research directions of blockchain with IoT are also discussed. We conclude that the combination of blockchain and IoT can provide a powerful approach which can significantly pave the way for new business models and distributed applications.

Energy poverty can be defined as the inability to pay the bills that are required for maintaining the comfort conditions (usually in winter) in dwellings. The use of energy efficient systems is one way forward to mitigate this problem, with one option being the electrically driven air source heat pump water heater. This paper assesses the performance of a centralised heat pump (200 kW of heating capacity) to meet the space heating demand of block dwellings in Madrid (tier four out of five in winter severity in Spain). Two models have been developed to obtain the following variables: the hourly thermal energy demand and the off-design heat pump performance. The proposed heat pump is driven by a motor with variable rotational speed to modulate the heating capacity in an efficient way. A back-up system is also considered to meet the peak demand. A levelised cost of heating of 92.22 €/MWh is obtained for a middle-level energy efficiency in housing (class E, close to D). Moreover, the following energy-environmental parameters have been achieved: more than 74% share of renewable energy in primary energy and 131.7 g CO2 avoided per kWh met. A reduction of 60% in the heating cost per dwelling is obtained if an energy retrofit is carried out, improving the energy performance class from E to C. These results prove that the proposed technology is among the most promising measures for addressing energy poverty in vulnerable households.

Target detection in satellite images is an essential topic in the field of remote sensing and computer vision. Despite extensive research efforts, accurate and efficient target detection in remote sensing images remains unsolved due to the large target scale span, dense distribution, and overhead imaging and complex backgrounds, which result in high target feature similarity and serious occlusion. In order to address the above issues in a comprehensive manner, within this paper, we first propose a Centralised Visual Processing Center (CVPC), this structure is a parallel visual processing center for Transformer encoder and CNN, employing a lightweight encoder to capture broad, long-range interdependencies. Pixel-level Learning Center (PLC) module is used to establish pixel-level correlations and improve the depiction of detailed features. CVPC effectively improves the detection efficiency of remote sensing targets with high feature similarity and severe occlusion. Secondly, we propose a centralised feature cross-layer fusion pyramid structure to fuse the results with the CVPC in a top-down manner to enhance the detailed feature representation capability at each layer. Ultimately, we present a Context Enhanced Adaptive Sparse Convolutional Network (CEASC), which improves the accuracy while ensuring the detection efficiency. Based on the above modules, we designed and conducted a series of experiments. These experiments are conducted on three challenging public datasets, DOTA-v1.0, DIOR, and RSDO, showing that our proposed 3CNet achieves a more advanced detection accuracy while balancing the detection speed (78.62% mAP for DOTA-v1.0, 79.12% mAP for DIOR, and 95.50% mAP for RSOD).

Biological invasions are responsible for substantial biodiversity declines as well as high economic losses to society and monetary expenditures associated with the management of these invasions 1 , 2 . The InvaCost database has enabled the generation of a reliable, comprehensive, standardized and easily updatable synthesis of the monetary costs of biological invasions worldwide 3 . Here we found that the total reported costs of invasions reached a minimum of US$1.288 trillion (2017 US dollars) over the past few decades (1970–2017), with an annual mean cost of US$26.8 billion. Moreover, we estimate that the annual mean cost could reach US$162.7 billion in 2017. These costs remain strongly underestimated and do not show any sign of slowing down, exhibiting a consistent threefold increase per decade. We show that the documented costs are widely distributed and have strong gaps at regional and taxonomic scales, with damage costs being an order of magnitude higher than management expenditures. Research approaches that document the costs of biological invasions need to be further improved. Nonetheless, our findings call for the implementation of consistent management actions and international policy agreements that aim to reduce the burden of invasive alien species. Analysis of the InvaCost database shows that the costs of biological invasions have markedly increased between 1970 and 2017 and show no sign of slowing down, highlighting the importance of evidence-based and cost-effective management actions.