Search Results (623)

Plant economics is based on carbon and nutrients rather than money. While leaf strategies aboveground are well characterized along an economic spectrum from “fast-growing and short-lived” to “slow and conservative,” economic models defined by aboveground shoot strategies remain unclear. Here, we offer a comprehensive view of aboveground economics and show that collaboration between shoots and stem cortical chlorenchyma can break out of the one-dimensional economic spectrum, offering a full range of economic possibilities. Trait data from 1551 current-year shoots of a single species confirm the classical fast–slow “conservation” gradient but reveal that most variation is explained by an orthogonal “cooperation” gradient, ranging from self-reliant resource acquisition to outsourced nutrient synthesis via the stem cortical chlorenchyma. This expanded “shoot economics space” provides a solid foundation for predicting aboveground responses to environmental change. Full article

This paper develops a bilevel game-theoretic model to analyze the strategic effects of tariffs and subsidies in a global supply chain involving a manufacturer and a third-party logistics (3PL) provider. The government, acting as a Stackelberg leader, sets fiscal instruments to maximize national welfare, while downstream supply chain participants respond by optimizing production, pricing, and logistics outsourcing decisions. The model is evaluated under three coordination structures—centralized, decentralized, and alliance-based—to examine how decision alignment influences policy effectiveness. Simulation results show that while tariffs negatively impact supply chain efficiency and profitability, well-designed subsidies can partially or fully offset these effects, particularly under centralized coordination. The model further reveals that policy outcomes are highly sensitive to the strategic power structure within the supply chain. This study advances the literature by integrating endogenous government behavior with logistics coordination and supply chain decision-making within a unified bilevel optimization framework. The findings offer actionable insights for both policymakers and global supply chain managers in designing robust fiscal and coordination strategies. Full article

Undergraduate design education faces a structural contradiction characterized by high cognitive load (CL) and relatively low innovation output. Meanwhile, existing generative AI tools predominantly emphasize the generation of visual outcomes, often overlooking the logical guidance mechanisms inherent in design thinking. This study proposes a Dual-Path teaching model integrating critical reconstruction behaviors to examine how AI enhances design thinking. It adopts structured interactions with the DeepSeek large language model, CL theory, and Structural Equation Modeling for analysis. Quantitative results indicate that AI-assisted paths significantly enhance design quality (72.43 vs. 65.60 in traditional paths). This improvement is attributed to a “direct effect + multiple mediators” model: specifically, AI reduced the mediating role of Extraneous Cognitive Load from 0.907 to 0.017, while simultaneously enhancing its investment in Germane Cognitive Load to support deep, innovative thinking. Theoretically, this study is among the first to integrate AI-driven critical reconstruction behaviors (e.g., iteration count, cross-domain terms) into CL theory, validating the “logical chain externalization → load optimization” mechanism in design education contexts. Practically, it provides actionable strategies for the digital transformation of design education, fostering interdisciplinary thinking and advancing a teaching paradigm where low-order cognition is outsourced to reinforce high-order creative thinking. Full article

Background/Objectives: In many parts of the world, pharmacists hold the primary responsibility for providing safe and effective pharmacotherapy. A key aspect is the availability of appropriate medicines for each individual patient. When industrially manufactured medicines are unsuitable or unavailable, pharmacists can prepare tailor-made medicines. While this principle applies globally, practices vary between countries. In the Netherlands, the preparation of medicines in pharmacies is well-established and integrated into routine healthcare. This narrative review explores the role and significance of extemporaneous compounding, pharmacy preparations and related product care in the Netherlands. Methods: Pharmacists involved in pharmacy preparations across various professional sectors, including community and hospital pharmacies, central compounding facilities, academia, and the professional pharmacists’ organisation, provided detailed and expert insights based on the literature and policy documents while also sharing their critical perspectives. Results: We present arguments supporting the need for pharmacy preparations and examine their position and role in community and hospital pharmacies in the Netherlands. Additional topics are discussed, including the regulatory and legal framework, outsourcing, quality assurance, standardisation, education, and international context. Specific pharmacy preparation topics, often with a research component and a strong focus on product care, are highlighted, including paediatric dosage forms, swallowing difficulties and feeding tubes, hospital-at-home care, reconstitution of oncolytic drugs and biologicals, total parenteral nutrition (TPN), advanced therapy medicinal products (ATMPs), radiopharmaceuticals and optical tracers, clinical trial medication, robotisation in reconstitution, and patient-centric solid oral dosage forms. Conclusions: The widespread acceptance of pharmacy preparations in the Netherlands is the result of a unique combination of strict adherence to tailored regulations that ensure quality and safety, and patient-oriented flexibility in design, formulation, and production. This approach is further reinforced by the standardisation of a broad range of formulations and procedures across primary, secondary and tertiary care, as well as by continuous research-driven innovation to develop new medicines, formulations, and production methods. Full article

Carbon cap-and-trade is a practical policy in guiding manufacturers to produce economic and environmental production plans. However, previous studies on carbon cap-and-trade are from a macro level to guide manufacturers to make production plans, rather than from a perspective of specific production scheduling, which leads to a lack of theoretical guidance for manufacturers to develop reasonable production scheduling schemes for specific production orders. This article investigates a specific scheduling problem in a flexible job-shop environment that considers the carbon cap-and-trade policy, aiming to provide guidance for specific production scheduling (i.e., resource allocation). In the proposed problem, carbon emissions have an upper limit. A penalty will be generated if the emissions overpass the predetermined cap. To satisfy the carbon emission cap, the manufacturer can trade carbon credits or adopt outsourcing strategy, that is, outsourcing partial orders to partners at the expense of outsourcing costs. To solve the proposed model, a novel and efficient memetic algorithm (NEMA) is proposed. An initialization method and four local search operators are developed to enhance the search ability. Numerous experiments are conducted and the results validate that NEMA is a superior algorithm in both solution quality and efficiency. Full article

In the deep integration process between digital infrastructure and new economic forms, structural imbalance between the evolution rate of cloud storage technology and the growth rate of data-sharing demands has caused systemic security vulnerabilities such as blurred data sovereignty boundaries and nonlinear surges in privacy leakage risks. Existing academic research indicates current proxy re-encryption schemes remain insufficient for cloud access control scenarios characterized by diversified user requirements and personalized permission management, thus failing to fulfill the security needs of emerging computing paradigms. To resolve these issues, a revocable attribute-based proxy re-encryption scheme supporting policy-hiding is proposed. Data owners encrypt data and upload it to the blockchain while concealing attribute values within attribute-based encryption access policies, effectively preventing sensitive information leaks and achieving fine-grained secure data sharing. Simultaneously, proxy re-encryption technology enables verifiable outsourcing of complex computations. Furthermore, the SM3 (SM3 Cryptographic Hash Algorithm) hash function is embedded in user private key generation, and key updates are executed using fresh random factors to revoke malicious users. Ultimately, the scheme proves indistinguishability under chosen-plaintext attacks for specific access structures in the standard model. Experimental simulations confirm that compared with existing schemes, this solution delivers higher execution efficiency in both encryption/decryption and revocation phases. Full article

Global building energy consumption is significantly increasing. Utilizing renewable energy sources may be an effective approach to achieving low-carbon and energy-efficient buildings. A combined system incorporating solar photovoltaic–thermal (PV/T) components with an air-source heat pump (ASHP) was studied for simultaneous heating and power generation in a real residential building. The back panel of the PV/T component featured a novel polygonal Freon circulation channel design. A prototype of the combined heating and power supply system was constructed and tested in Fuzhou City, China. The results indicate that the average coefficient of performance (COP) of the system is 4.66 when the ASHP operates independently. When the PV/T component is integrated with the ASHP, the average COP increases to 5.37. On sunny days, the daily average thermal output of 32 PV/T components reaches 24 kW, while the daily average electricity generation is 64 kW·h. On cloudy days, the average daily power generation is 15.6 kW·h; however, the residual power stored in the battery from the previous day could be utilized to ensure the energy demand in the system. Compared to conventional photovoltaic (PV) systems, the overall energy utilization efficiency improves from 5.68% to 17.76%. The hot water temperature stored in the tank can reach 46.8 °C, satisfying typical household hot water requirements. In comparison to standard PV modules, the system achieves an average cooling efficiency of 45.02%. The variation rate of the system’s thermal loss coefficient is relatively low at 5.07%. The optimal water tank capacity for the system is determined to be 450 L. This system demonstrates significant potential for providing efficient combined heat and power supply for buildings, offering considerable economic and environmental benefits, thereby serving as a reference for the future development of low-carbon and energy-saving building technologies. Full article

Background: The growth of parcel volumes in urban areas, largely driven by e-commerce, has increased the complexity of pickup and delivery operations. To meet demands for cost efficiency, flexibility, and sustainability, CEP (Courier, Express, and Parcel) operators increasingly outsource segments of their last-mile networks. Methods: This study proposes a novel multidimensional cost model for outsourcing, integrating five key variables: transport unit type (parcel/pallet), service phase (pickup/delivery), vehicle category, powertrain type, and delivery point type. The model applies correction coefficients based on internal operational costs, further adjusted for location and service quality using a bonus/malus mechanism. Results: Each cost component is calculated independently, enabling full transparency and route-level cost tracking. A real-world case study was conducted using operational data from a CEP operator in Bosnia and Herzegovina. The model demonstrated improved accuracy and fairness in cost allocation, with measurable savings of up to 7% compared to existing fixed-price models. Conclusions: The proposed model supports data-driven outsourcing decisions, allows tailored cost structuring based on operational realities, and aligns with sustainable last-mile delivery strategies. It offers a scalable and adaptable tool for CEP operators seeking to enhance cost control and service efficiency in complex urban environments. Full article

Platform support for mobile collaboration among multiple smart devices has been an active research issues in the computing community. Using platform-level collaboration functionalities, a mobile device can share its resources, I/O events, and even apps easily with other devices, which enables developing a new kind of application that runs across multiple devices. In this work, we further extend the collaboration functionalities in mobile platforms by developing a novel platform service, remote intent service (RIS),which enables a running application in a device to outsource the execution of a specific task to another application in a remote device. Using the remote intent service, for example, we can view an attached document to an email, using a document viewer application in a remote device that has a larger screen, or conveniently browse an audio file that exists on another mobile device and play it locally. We implemented the remote intent service to the Android platform and measured the latency for executing such tasks in a remote device. The experimental results confirm that the remote intent service, for sending the intent plus retrieving the result, incurs an additional delay of less than 250 ms in total, and thus, it is practical. Full article

Remanufacturing in reverse logistics can not only support sustainable development but also provide a tractable way to achieve carbon neutrality. This study evaluates whether an original equipment manufacturer (OEM) should remanufacture outsource or authorize this reverse channel activity in the presence of government subsidies. Additionally, the model considers the equilibrium acquisition quantities, collection rates, prices, and effects of government subsidy under three reverse channel options: centralizing remanufacturing, outsourcing remanufacturing, and authorization remanufacturing. The analysis indicates that (i) a centralized approach with manufacturing and remanufacturing operations under a fixed government subsidy is always in the interest of the supply chain; (ii) that for the profit-maximizing third-party remanufacturer (3PR), the differentials in variable collection costs drive the strategy choice, and that a higher fixed scaling parameter of the collection cost favors outsourcing; and (iii) when the government aspires to reduce environmental effects and subsidy payments, the OEM and government have different reverse channel choice preferences. Surprisingly, profitability and environmental goals align under a high consumer acceptance of the remanufactured product. This paper extends the understanding of the remanufacturing strategy of an OEM and provides new insights on which reverse channel is optimal. Full article

Provable data possession (PDP) is a technique that enables the verification of data integrity in cloud storage without the need to download the data. PDP schemes are generally categorized into public and private verification. Public verification allows third parties to assess the integrity of outsourced data, offering good openness and flexibility, but it may lead to privacy leakage and security risks. In contrast, private verification restricts the auditing capability to the data owner, providing better privacy protection but often resulting in higher verification costs and operational complexity due to limited local resources. Moreover, most existing PDP schemes are based on classical number-theoretic assumptions, making them vulnerable to quantum attacks. To address these challenges, this paper proposes an identity-based PDP with a designated verifier over lattices, utilizing a specially leveled identity-based fully homomorphic signature (IB-FHS) scheme. We provide a formal security proof of the proposed scheme under the small-integer solution (SIS) and learning with errors (LWE) within the random oracle model. Theoretical analysis confirms that the scheme achieves security guarantees while maintaining practical feasibility. Furthermore, simulation-based experiments show that for a 1 MB file and lattice dimension of n = 128, the computation times for core algorithms such as TagGen, GenProof, and CheckProof are approximately 20.76 s, 13.75 s, and 3.33 s, respectively. Compared to existing lattice-based PDP schemes, the proposed scheme introduces additional overhead due to the designated verifier mechanism; however, it achieves a well-balanced optimization among functionality, security, and efficiency. Full article

The rapid expansion of blockchain-based digital asset trading raises new challenges in security, privacy, and efficiency. Although traditional attribute-based encryption (ABE) provides fine-grained access control, it imposes considerable computational overhead and introduces additional vulnerabilities when decryption is outsourced. To address these limitations, we present EBODS, an efficient outsourced decryption framework that combines an optimized ABE scheme with a decentralized blockchain layer. By applying policy matrix optimization and leveraging edge decryption servers, EBODS reduces the public key size by 8% and markedly accelerates computation. Security analysis confirms the strong resistance of EBODS to collusion attacks, making it suitable for resource-constrained digital asset platforms. Full article

The study aims to increase productivity in the cold room door manufacturing industry by addressing non-value-adding operations, identifying bottlenecks, and reducing processing time through digital twin (DT)-based simulation. The goal is to eliminate the need for supply chain outsourcing and increase overall efficiency. The research involves developing a DT of the existing production process for five distinct categories of cold room doors: flush door, single door, double door, face-mounted door, and sliding door. Simulation was used to uncover problems at multiple stations, encompassing curing, welding, and packing. Lean principles were used to identify the causes of inefficiency, and the process was improved using TRIZ principles. These changes produced a 42.90% improvement in productivity, a 20% dependence reduction on outsourcing and an increase of 10.5% added inventory to the shortage demand level. The approach presented is provided for a particular manufacturer of cold room doors, but the methods and techniques used are generally applicable to other manufacturing companies to support systematic innovation. Combining DT simulation, lean techniques and TRIZ principles, this study presents a strong approach to addressing the productivity challenges in manufacturing. The incorporation of these methods has brought considerable operational efficiency and has minimised dependency on external outsourcing. Full article

Wallboard outsourcing is a critical task in cloud-based manufacturing, where demand enterprises seek suitable suppliers for machining services through online platforms. However, the recommendation process faces significant challenges, including sparse rating data, unstructured textual descriptions from suppliers, and complex, non-linear user preferences. To address these issues, this paper proposes AttVAE-PMF, a novel recommendation method based on dual-channel neural networks and probabilistic matrix factorization. Specifically, an attention-enhanced long short-term memory (LSTM) is employed to extract semantic features from free-text supplier descriptions, while a variational autoencoder (VAE) is used to model latent preferences from sparse demand-side ratings. These two types of latent representations are then fused via probabilistic matrix factorization (PMF) to complete the rating matrix and infer enterprise preferences. Experiments conducted on both the wallboard dataset and the MovieLens-100K dataset demonstrate that AttVAE-PMF outperforms baseline methods—including PMF, DLCRS, and SSAERec—in terms of convergence speed and robustness to data sparsity, validating its effectiveness in handling sparse and heterogeneous information in wallboard outsourcing recommendation scenarios. Full article

Background: Developing countries face significant challenges in accessing high-quality pharmaceutical products due to resource constraints, limited regulatory capacity, and market dynamics that often prioritize cost over quality. This review addresses the critical gap in regulatory frameworks that fail to ensure pharmaceutical quality equity between developed and developing nations. Objective: This comprehensive review examines a novel dual-pathway regulatory framework that leverages stringent regulatory authority (SRA) approvals, artificial intelligence-based evaluation systems, and harmonized pricing mechanisms to ensure pharmaceutical quality equity across global markets. Methods: A comprehensive systematic analysis of current regulatory challenges, proposed solutions, and implementation strategies was conducted through an extensive literature review (202 sources, 2019–2025), expert consultation on regulatory science, AI implementation in healthcare, and pharmaceutical policy development. The methodology included an analysis of regulatory precedents, an economic impact assessment, and a feasibility evaluation based on existing technological implementations. Results: The proposed framework addresses key regulatory capacity gaps through two complementary pathways: Pathway 1 enables same-batch distribution from SRA-approved products with pricing parity mechanisms. At the same time, Pathway 2 provides independent evaluation using AI-enhanced systems for differentiated products. Key components include indigenous AI development, which requires systematic implementation over 4–6 years across three distinct stages, outsourced auditing frameworks that reduce costs by 40–50%, and quality-first principles that categorically reject cost-based quality compromises. Implementation analysis demonstrates a potential for achieving a 90–95% quality standardization, accompanied by a 200–300% increase in regulatory evaluation capability. Conclusions: This framework has the potential to significantly improve pharmaceutical quality and access in developing countries while maintaining rigorous safety and efficacy standards through innovative regulatory approaches. The evidence demonstrates substantial public health benefits with projected improvements in population access (85–95% coverage), treatment success rates (90–95% efficacy), and economic benefits (USD 15–30 billion in system efficiencies), providing a compelling case for implementation that aligns with global scientific consensus and Sustainable Development Goal 3.8. Full article