Search Results (2,846)

Optimizing the parameters of the manufacturing process for products in terms of metalworking equipment is one of the key tasks in technological preparation for production. This process is structurally complex, characterized by an ordered set of actions of various types. The basis for improving the efficiency of the technological process is the comprehensive optimization of the parameters of individual elements that form its structure. To solve this problem, an integrated model for comprehensive multi-criteria optimization of a structurally complex process has been developed, establishing a clear hierarchical relationship between its elements. The model is based on the structural decomposition of two processes: the process of forming individual design elements and the technological process of manufacturing a product. Structural hierarchical models have been developed for each process. The structure of the integrated model contains six levels of control. For each level of control, a set of target indicators and control parameters has been formed. The article presents the results of testing the proposed model using the example of optimizing the technological process of mechanical processing for the “Housing” product. As part of the study, structural and parametric optimization of the manufacturing process for this part was carried out. During the study, the structure of the technological processing route was optimized, as well as individual technological operations and technological transitions. Over the course of the work, the technological equipment and processing methods used for shaping a number of surfaces were replaced. As a result of the optimization, the overall labor intensity of the technological process for manufacturing the “Housing” product was reduced by 19.8%, and the manufacturing accuracy of the most critical surfaces was increased by 16.4%. The results confirm the effectiveness of the proposed model for comprehensive optimization of the mechanical processing technological process. Full article

Decommissioning poses a challenge for decision-makers. As an aspect of decommissioning that is not explicitly outlined in regulations, waste management for decommissioned materials is a special challenge. In Brazil, a large amount of the decommissioned subsea infrastructure is composed of flexible pipelines, with interlocked structures that increase the recycling challenge. This study identified two technological routes to dismantle the pipes. These routes (A and B), consisting of processes centered on the shredding and the manual dismantling of the pipes, respectively, were analyzed through a comparative Life Cycle Assessment (LCA) study. This study offers valuable insight into the waste management of decommissioned subsea infrastructure by quantifying the potential environmental impacts associated to the two main pre-processing strategies for the recycling of decommissioned flexible pipes in Brazil. Each route presented different levels of mechanization, energy consumption, productivity, labor intensity, types and levels of occupational hazards and recycling options for the resulting polymeric materials. The results from this study indicate that Route B is more aligned with the principles of a circular economy, enabling the mechanical recycling of 98% of the polymeric material and presenting substantially lower potential environmental impacts. In particular, Route B represents approximately 9.6% of the global warming impact (kg CO₂ eq) associated with Route A. Overall, its impacts vary from 1.47% (marine eutrophication) to 12.18% (ozone formation) of those associated with Route A across the different impact categories. Full article

As a crucial pathway for optimizing land factor allocation, farmland transfer plays a pivotal role in implementing the “storing grain in land and technology” strategy and safeguarding national grain security. Based on panel data from 30 provinces in China spanning 2009 to 2023, this study employs a two-way fixed effects model and a Spatial Durbin Model (SDM) to systematically examine the mechanisms, heterogeneity, and spatial spillover effects of farmland transfer on grain production capacity. The results indicate that: (1) Farmland transfer significantly enhances grain production capacity, and this conclusion remains robust after multiple robustness and endogeneity tests. (2) Farmland transfer boosts grain production capacity by promoting cultivated land connectivity and facilitating the substitution of machinery for labor; however, the accompanying non-grain tendency and land governance disputes exert inhibitory effects on capacity release. (3) Transfers to farming households and professional cooperatives, as well as the adoption of leasing and informal exchange arrangements, exhibit the strongest positive effects on production capacity, and the scale-efficiency gains of farmland transfer are particularly pronounced in major grain-consuming areas. (4) Improvements in a region’s farmland transfer level drive the enhancement of grain production capacity in neighboring regions through the diffusion of management experience and the sharing of social services. This study provides empirical evidence and policy insights to optimize farmland transfer mechanisms and safeguard food security. Full article

Generative artificial intelligence in higher education is typically framed as either a student productivity tool or an institutional disruption. This agenda-setting essay advances a third position: mobile generative AI functions as relational infrastructure—a persistent communicative presence that mediates identity, meaning-making, and belonging during institutional transition. Focusing on international graduate student onboarding, we abductively “think through” two complementary theoretical lenses. Constitutive Artificial Intelligence Identity Theory (CAIIT) conceptualizes AI as a co-constitutive participant in identity formation through recursive communicative feedback loops. Language Convergence/Meaning Divergence (LC/MD) theory explains how shared institutional language masks interpretive gaps across intercultural and bureaucratic contexts. Reading narrative vignettes through these frameworks, we argue that generative AI is neither simple curricular tool nor personal aid, but both relational and organizational infrastructure, redistributing translational, emotional, and interpretive labor in higher education. We outline four design principles for AI-integrated onboarding: distinguish communicative scaffolding from cognitive replacement; design systems that assume meaning divergence; center equity in AI-mediated transitions; and anticipate ethical risk. Reframing AI as relational infrastructure shifts AI-in-education research toward relational accountability and institutional care. Full article

Production greenhouse complexes increasingly require automation and digitalization to address rising labor costs, improve productivity, and support sustainable resource use. However, most existing solutions target isolated tasks and lack a unified framework for continuous monitoring and production-oriented accounting at facility scale. This paper proposes a system-level architecture that integrates robotic monitoring platforms, AI-based perception, and cloud-based data management into a coherent operational framework. The robotic monitoring platforms operate on rails and concrete surfaces and are capable of elevating cameras and sensors up to 5 m to support plant-health assessment, environmental monitoring, and production accounting. Aggregated data are incorporated into a digital twin that supports spatial traceability, historical analysis, and decision support. The proposed approach enables continuous inspection, improves early detection of crop stress, reduces repetitive manual scouting, and supports targeted interventions. The framework provides a scalable foundation for sustainable, data-driven greenhouse management and practical deployment of robotic monitoring systems in industrial production environments. Full article

The way land is managed and utilized restricts agricultural development and food production. The fragmentation of arable land, characterized by “many plots and small areas,” is unfavorable for moderate-scale agricultural management and food production supply. Based on survey data of grain farmers in the Yellow River Basin, this study employs methods such as 2SLS, PSM, and IVQR to analyze the impact of average plot size on farmers’ grain production efficiency and its mechanisms. It also examines the differentiated effects of expanding plot size on different types of farmers, regions, and crops. The results show the following: (1) Expanding the arable land plot size (ALPS) helps improve farmers’ grain production efficiency, thereby enhancing the quality and benefits of agricultural development. (2) Expanding plot size can affect grain production efficiency through multiple pathways, including promoting machinery use and agricultural technology adoption, reducing material and labor input costs, and increasing grain yields. (3) Expanding plot size is more beneficial to farmers with higher production efficiency and smaller operation scales, as it both “supports the strong” and has a “pro-smallholders” characteristic, with more benefits for farmers in the western region and those growing wheat. Therefore, in order to promote high-quality agricultural development and ensure national food security, policies should focus on addressing land fragmentation and appropriately expanding the average plot size for farmers, especially smallholders. Full article

Large-scale infrastructure development disrupts not only the material foundations of agrarian livelihoods but also the social and ecological systems through which households manage uncertainty. This study argues that the livelihood shifts observed among households affected by the construction of the Bili-Bili Reservoir in Lanna Sub-district, Gowa Regency, Indonesia, are best understood as products of contextual rationality operating at the individual level and enacted through household-level strategies. Using a qualitative phenomenological approach with 15 purposively selected informants, each representing a distinct household directly affected by the reservoir’s construction functioned as a structural shock that exceeded the adaptive capacity of the existing agrarian system, triggering differentiated household responses—including reservoir fisheries, small-scale trade, home-based enterprise, and labor migration—whose variation reflects systematic differences in individual skills, asset endowments, and social capital access rather than arbitrary or purely compelled choice. Theoretically, this study advances the sustainable livelihoods framework by specifying the mechanism linking individual rationality to household adaptive outcomes, and by showing how social capital—in its bonding, bridging, and linking dimensions—shapes the option set within which rational calculations are made. These findings suggest that post-displacement livelihood recovery is more effectively supported by policies that strengthen social network structures alongside physical and financial provision. Full article

Parboiling enhances the nutritional, structural, and economic value of rice, yet its adoption in the United States remains limited despite rising domestic and export demand. This review summarizes key stages of the parboiling process and their effects on milling yield, grain integrity, nutrient retention, and glycemic response. It outlines major industry challenges, including high energy and water use, uneven heating and drying, handling of defective kernels, limited automation in smaller mills, labor shortages, and emerging climate-related risks. Advances such as vacuum soaking, infrared and microwave-assisted drying, smart sensors, and AI-driven control systems show strong potential to improve efficiency and product quality. Circular-economy strategies, including biomass energy recovery, water reuse, and by-product valorization, offer additional sustainability gains. Continued research, modernization, and policy support are critical to strengthen competitiveness and positioning of the U.S. parboiled rice sector for a more resilient and sustainable future. Full article

Background: Global supply chains operate in increasingly volatile and technology-intensive environments shaped by digital transformation and artificial intelligence integration. While prior research has emphasized structural and technological enablers of flexibility, the behavioral foundations of supply chain adaptability remain insufficiently explored. Methods: This study develops a conceptual integration of the Kano model and the Cobb–Douglas production function to position managerial attitude as a strategic “delighter” within supply chain systems. The proposed framework models supply chain flexibility as a function of capital, labor, artificial intelligence integration, and managerial attitude within an extended economic representation. Results: The model suggests that managerial attitude acts as a behavioral amplifier that strengthens the performance effects of technological and economic inputs, potentially generating nonlinear gains in responsiveness and adaptive capacity. By distinguishing human-driven, algorithmic, and hybrid attitudinal configurations, the framework clarifies how behavioral orientations influence artificial intelligence adoption and supply chain flexibility, particularly in small and medium-sized enterprise contexts. Conclusions: Although conceptual in nature, the framework provides a formal analytical foundation for future empirical testing and elasticity-based sensitivity analysis in supply chain research. Full article

Rapid digitalization and artificial intelligence are restructuring land systems by altering the functional relationship between built environments, socio-ecological processes, and territorial capital accumulation. This paper provides a conceptual and literature-based analysis of how hybrid physical–digital infrastructures are reshaping urban–rural interactions, land-use intensity, and long-term sustainability conditions. Rather than developing a fully operational measurement model, the study critically examines the limitations of aggregate productivity indicators and existing evaluation frameworks in capturing spatial reorganization processes, capital durability, and long-term dynamics. Building on insights from sustainability economics and socio-ecological systems research, the paper proposes a stock–flow interpretative perspective to better understand the interaction between physical, natural, and intangible capital within evolving land systems. The analysis focuses on three structural drivers of land system transformation: (i) the virtualization of services and the expansion of cyberspace-based infrastructures; (ii) demographic contraction and aging processes affecting land demand and settlement structures; and (iii) capital deepening in energy-intensive digital networks with implications for land–climate interactions. Within this context, particular attention is given to infrastructure life-cycle dynamics, entropy-related capital decay, and the role of artificial intelligence in reshaping labor–land relationships. The paper highlights the need for new evaluation approaches capable of distinguishing between value generated through material land transformation and value emerging from intangible and digital layers. In this sense, it aims to contribute to ongoing debates on land management and spatial planning by outlining a research agenda for the development of spatially grounded, stock–flow-based sustainability metrics. The findings suggest that future land governance and urban development strategies will need to explicitly account for hybrid spatial architectures and their long-term resource and climate implications in order to preserve territorial resilience and intergenerational equity. Full article

Background/Objectives: Robotic Process Automation (RPA) offers a potential solution for reducing the manual burden of clinical data abstraction, yet empirical evidence of its effectiveness in real-world electronic health record (EHR)-integrated cancer registries remains limited. This study aimed to evaluate the post-implementation effectiveness of RPA for cancer registry data abstraction in a tertiary hospital and to explore multidisciplinary stakeholder perceptions regarding its deployment. Methods: We implemented RPA for gastric and breast cancer registries within a production EHR system. Quantitative effectiveness was evaluated by comparing per-patient data extraction time using descriptive statistics. To ensure data integrity, all RPA-extracted outputs were entirely verified manually by researchers against source records. Qualitatively, semi-structured interviews were conducted with 14 participants and analyzed via thematic analysis based on the Promoting Action on Research Implementation in Health Services (PARiHS) framework (Evidence, Context, and Facilitation). Results: RPA was applied to 70 gastric cancer variables and 83 breast cancer variables. For the gastric cancer registry, the mean abstraction time per patient decreased by 74% (19.5 ± 3.0 to 5.1 ± 1.8 min). For the breast cancer registry, time decreased by 30% (25.4 ± 6.9 to 17.8 ± 5.5 min). Based on 2024 surgical volumes, this translates to an estimated saving of over 260 h of manual labor per year. Qualitative findings revealed that while participants recognized RPA as ideal for repetitive tasks, successful implementation was contingent on clinician cooperation and continuous output monitoring. Conclusions: RPA implementation significantly improved data abstraction efficiency in a real-world clinical research workflow. The disparity in time savings highlights that efficiency gains are contingent upon registry complexity. While formal quantitative assessments of data accuracy were not performed, RPA is a readily deployable tool for enhancing clinical data workflows when aligned with organizational readiness and robust monitoring. Full article

Lentinula edodes (shiitake) is a globally significant edible mushroom, with China being its largest producer. Efficient breeding is fundamental to sustaining its industry, yet it is often hindered by the labor-intensive and time-consuming nature of traditional mating type identification methods. To develop a rapid genotyping tool, we elucidated the polymorphism of key mating-type genes and established a practical molecular marker system. In this study, we focused on four major cultivated L. edodes varieties in China (0912, 9608, L808, and W1). Whole-genome sequencing, assembly, and annotation revealed the allelic diversity of HD1 of the A mating type and rcb1 and rcb5 of the B mating type in monokaryotic strains of these varieties. Sequence alignment indicated that HD1 could be classified into five types, rcb1 into four types, and rcb5 into four types. Based on SNPs and InDels, co-dominant primers capable of distinguishing all allelic types of HD1, rcb1, and rcb5 were designed, generating clear molecular fingerprints for the 0912, 9608, L808, and W1 varieties. Notably, this system also demonstrated robust discriminatory power when applied to different Chinese varieties and international L. edodes varieties from Japan, Korea, Thailand, and Canada, confirming its reliability across diverse genetic backgrounds. This highly accurate and efficient marker system offers robust theoretical and technical support for parental selection, germplasm identification, and new variety protection for L. edodes, presenting significant potential to improve horticultural mushroom production efficiency. Full article

Rainbow trout (Oncorhynchus mykiss) farming represents a significant opportunity for developing sustainable regional aquaculture and food systems. This study assesses its potential using the Vologda Region in Northwest Russia as a case study. The methodology involved analyzing the compatibility of the species’ ecological requirements with local hydrochemical conditions and evaluating production dynamics from 2016 to 2024 through trend analysis. The results confirm that key water bodies in the region provide suitable conditions for industrial-scale cage farming. Production exhibited exponential growth, increasing from 10 to 994 tonnes over the eight-year period, transitioning from a rapid expansion phase (2016–2020) to a phase of stable, sustainable growth (2021–2024) with annual increases of 100–150 tonnes. A SWOT analysis identified major strengths, including abundant water resources and government support, alongside critical challenges such as technological lag, dependence on imported inputs, and skilled labor shortages. The findings underscore the substantial potential of trout aquaculture to serve as a pillar of a localized food system in the region. Realizing this potential over the long term will require targeted investments in modern technology, value-added processing, and workforce development to mitigate existing constraints. Full article

We developed an automated folding device for soft plastic bags to replace manual folding. The device employs a flat folding plane, combined with feeding positioning and edge-guided pre-crease. After computing the required torque for every folding step, the actuators are selected. This device increases production output and reduces labor costs. Under typical operating conditions, the production of folded bags has increased to 90 bags per hour, three times that of manual folding, while controlling the crease position deviation within 2.0 mm. With one automated folding device, instead of one laborer, the yield rate was raised to 98%, the production was 187,200 bags per year, and the annual savings were estimated as NT$240,000. Full article

While return migrant workers (RMWs) are increasingly viewed as key to rural development, their specific impact on grain production remains ambiguous. Clarifying this role is critical to manage the dual nature of their reintegration—leveraging valuable resources and knowledge while addressing complex reintegration challenges—to ensure national food security and advance agricultural modernization. Drawing on data from the 2018 China Labor-force Dynamics Survey (CLDS), this study explicitly tests the hypothesis that migration experience significantly reduces the likelihood that RMW households engage in grain production. The empirical results from probit models support this hypothesis, and this finding is robust across multiple specifications. Further analysis shows that migration experience significantly reduces land cultivation scales—especially among larger producers—and increases land abandonment. Additionally, it inhibits technology adoption or invest in agricultural technology. These results suggest that migration experience may weaken, rather than enhance, RMWs’ commitment to grain production, challenging the policy expectation that they can lead agricultural transformation. The study calls for more nuanced policy interventions that account for the structural constraints facing RMW households and their limited contribution to large-scale, efficient grain farming. Full article