Search Results (935)

Loop-Mediated Isothermal Amplification (LAMP) technology is emerging as a rapid pathogen testing method, potentially challenging the RT-PCR “gold standard”. Despite recent advancements, LAMP’s widespread adoption remains limited. This study provides a comprehensive market overview and assesses future growth prospects to aid stakeholders in strategic decision-making and policy formulation. Using a dataset of 1134 LAMP patent documents, we analyzed lifecycle and geographic distribution, applicant profiles, CPC code classifications, and patent claims. Additionally, we examined clinical developments from 21 curated clinical trials, focusing on trends, geographic engagement, sponsor types, and the conditions and pathogens investigated. Our analysis highlights LAMP’s potential as a promising rapid pathogen testing alternative, especially in resource-limited areas. It also reveals a gap between clinical research, which targets bacterial and parasitic diseases like malaria, leishmaniasis, and tuberculosis, and basic research and commercial efforts that prioritize viral diseases such as SARS-CoV-2 and influenza. European stakeholders emphasize the societal impact of addressing unmet needs in resource-limited areas, while American and Asian organizations focus more on research, innovation, and commercialization. Full article

The vehicle-road collaborative intelligence approach has become an industry consensus. It can efficiently tackle the technical hurdles and reduce the performance requirements and costs of on-board perception and computing devices. There is a need for in-depth quantitative studies to optimize the allocation of vehicle-road intelligent capabilities for collaborative intelligence. However, current research tends to focus more on qualitative analysis, and there is little research on the redistribution of vehicle and roadside intelligent capabilities. In this paper, we present a model for distributing perception and computing capabilities between vehicle-side and roadside, ensuring to meet the needs of various autonomous driving levels. Meanwhile, the collaborative intelligence approach will also introduce the costs of intelligent infrastructure deployment, energy, and maintenance. Different roads have varying scene characteristics and usage intensities. It is necessary to conduct a cost-effectiveness analysis of the intelligent deployment of different road types. A vehicle-road cost allocation model is developed based on the lifecycle traveled distance of vehicles and the lifecycle traffic flow of various roads to evaluate the function-cost effectiveness. Our study presents several vehicle-road intelligent schemes that meet the needs of various autonomous driving levels and selects Beijing for case analysis. The results indicate that primary intelligent infrastructure can reduce the lifecycle cost of the vehicle-side intelligent scheme for intermediate autonomous driving from ¥65,301 to ¥37,703, and advanced intelligent infrastructure can reduce the lifecycle cost for advanced autonomous driving from ¥126,938 to ¥42,180. Considering the distributed cost of vehicle-side and roadside, urban roads in Beijing have higher function-cost effectiveness compared to highways, especially urban expressways, which are expected to generate 43.3 times the vehicle-function-cost benefits after the advanced intelligent upgrades. The corresponding research findings can serve as a reference for city managers to make decisions on intelligent road deployment. Full article

This comprehensive systematic review explores the multifaceted impacts of electric vehicle (EV) adoption across technological, environmental, organizational, and policy dimensions. Drawing from 88 peer-reviewed articles, the study addresses a critical gap in the existing literature, which often isolates the impact of EV adoption without considering holistic effects. Technological advancements include innovations in the battery technology and energy storage systems, enhancing EV performance and mitigating range anxiety. The environmental analysis reveals substantial reductions in greenhouse gas emissions, with lifecycle assessments showing significant reductions for EVs compared to internal combustion engine vehicles, particularly when charged with renewable energy sources. Key comparisons include lifecycle emissions between mid-size battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), and global average lifecycle emissions by powertrain under various policy scenarios. The organizational implications are evident, as businesses adopt new models for fleet management and logistics, leveraging EVs for operational efficiency and sustainability. Policy analysis underscores the crucial role of government incentives, regulatory measures, and infrastructure investments in accelerating EV adoption. The review identifies future research areas such as efficient battery recycling methods, the potential impact of EVs on grid stability, and long-term economic implications. This study offers insights for stakeholders aiming to foster sustainable transportation and achieve global climate goals. Full article

The Industrial Internet of Things has enabled the integration and analysis of vast volumes of data across various industries, with the maritime sector being no exception. Advances in cloud computing and deep learning (DL) are continuously reshaping the industry, particularly in optimizing maritime operations such as Predictive Maintenance (PdM). In this study, we propose a novel DL-based framework focusing on the fault detection task of PdM in marine operations, leveraging time-series data from sensors installed on shipboard machinery. The framework is designed as a scalable and cost-efficient software solution, encompassing all stages from data collection and pre-processing at the edge to the deployment and lifecycle management of DL models. The proposed DL architecture utilizes Graph Attention Networks (GATs) to extract spatio-temporal information from the time-series data and provides explainable predictions through a feature-wise scoring mechanism. Additionally, a custom evaluation metric with real-world applicability is employed, prioritizing both prediction accuracy and the timeliness of fault identification. To demonstrate the effectiveness of our framework, we conduct experiments on three types of open-source datasets relevant to PdM: electrical data, bearing datasets, and data from water circulation experiments. Full article

This study proposes a model for the quantitative evaluation of the life-cycle carbon footprints of large sporting events and the uncertainties related to them. The model was used to analyze the case of a mega sporting event in Beijing, China. First, the quantitative model for the evaluation of the carbon footprints of mega sporting events includes a preparation stage, a holding stage, and an end stage. These stages consider the energy and resources used for construction, operation, transportation, catering, and accommodation. Second, this study proposes a prediction model using model-based and simulation-based methods to address the difficulty of obtaining traffic activity. Third, a semi-quantitative method that combines a data quality indicator and stochastic simulation is adopted for the uncertainty analysis of mega sporting events. Finally, a case study is used to indicate that the preparation stage of a mega sporting event accounts for the highest CO₂ emissions at 92.1%, followed by 7.5% in the holding stage and 0.4% in the end stage. The total life-cycle CO₂ emissions of a sustainable scenario of a mega sporting event in Beijing amount to 205,080.3 t CO_2e, and the per capita CO₂ emissions during the event’s holding stage amount to 0.26 t CO_2e/person. The uncertainty in the input parameters is 0.0617, indicating that the uncertainty of the model is low, and the reliability of the results is high. Full article

Biodegradable biobased polymers derived from biomass (such as plant, animal, marine, or forestry material) show promise in replacing conventional petrochemical polymers. Research and development have been conducted for decades on potential biodegradable biobased polymers such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs), and succinate polymers. These materials have been evaluated for practicality, cost, and production capabilities as limiting factors in commercialization; however, challenges, such as the environmental limitations on the biodegradation rates for biodegradable biobased polymer, need to be addressed. This review provides a history and overview of the current development in the synthesis process and properties of biodegradable biobased polymers, along with a techno-commercial analysis and discussion on the environmental impacts of biodegradable biobased polymers. Specifically, the techno-commercial analysis focuses on the commercial potential, financial assessment, and life-cycle assessment of these materials, as well as government initiatives to facilitate the transition towards biodegradable biobased polymers. Lastly, the environmental assessment focuses on the current challenges with biodegradation and methods of improving the recycling process and reusability of biodegradable biobased polymers. Full article

The conversion from building information modeling (BIM) to building energy modeling (BEM) based on the industry foundation classes (IFC) data standard is a crucial step for efficient building energy design and energy performance analysis. The scope encompasses analyzing limitations in existing BIM-to-BEM workflows and proposing an optimized strategy that addresses data loss and modeling inconsistencies. The research question revolves around enhancing conversion efficiency and precision, with the hypothesis validated through literature review, development of a conversion tool, and case study verification. The data collection and evaluation methods involve streamlining the conversion process by incorporating BIM model optimization, automatic repair of damaged geometric information, and automatic thermal zone division. The main findings reveal that the optimized strategy and tool significantly reduce information duplication, improve the precision of energy simulations, and validate the hypothesis, thereby contributing to more efficient and accurate building energy design and analysis. Full article

The North China Plain (NCP) serves as a critical grain-producing region in China, playing a pivotal role in ensuring the nation’s food security. A comprehensive analysis of the carbon footprint (CF) related to the cultivation of major grain crops within this region and the proposal of strategies to reduce emissions through low-carbon production methods are crucial for advancing sustainable agricultural practices in China. This study employed the lifecycle assessment (LCA) method to estimate the CF of wheat, maize, and rice crops over a period from 2013 to 2022, based on statistical data collected from five key provinces and cities in the NCP: Beijing, Tianjin, Hebei, Shandong, and Henan. Additionally, the Logarithmic Mean Divisia Index (LMDI) model was utilized to analyze the influencing factors. The results indicated that the carbon footprints per unit area (CF_A) of maize, wheat, and rice increased between 2013 and 2022. Rice had the highest carbon footprint per unit yield (CF_Y), averaging 1.1 kg CO₂-eq kg⁻¹, with significant fluctuations over time. In contrast, the CF_Y of wheat and maize remained relatively stable from 2013 to 2022. Fertilizers contributed the most to CF composition, accounting for 48.8%, 48.0%, and 25.9% of the total carbon inputs for wheat, maize, and rice, respectively. The electricity used for irrigation in rice production was 31.8%, which was much higher than that of wheat (6.8%) and maize (7.1%). The LMDI model showed that the labor effect was a common suppressing factor for the carbon emissions of maize, wheat, and rice in the NCP, while the agricultural structure effect and the economic development effect were common driving factors. By improving the efficiency of fertilizer and pesticide utilization, cultivating new varieties, increasing the mechanical operation efficiency, the irrigation efficiency, and policy support, the CF of grain crop production in the NCP can be effectively reduced. These efforts will contribute to the sustainable development of agricultural practices in the NCP and support China’s efforts to achieve its “double carbon” target. Full article

The U.S. dairy sector is a significant emitter of methane and nitrous oxide, with the US EPA estimating it produced around 90 Tg CO₂ eq. in 2021. This paper reviews the literature on and evaluates various mitigation actions for reducing GHG emissions in the U.S. dairy sector, focusing on both direct and indirect emission sources. We conducted a narrative literature review based on the cradle to gate life-cycle assessment method, covering the entire dairy supply chain up until milk enters retail establishments, including dairy and feed producing farm practices, processing, transportation, and their associated emissions/costs. The papers included were selected over a three year process depending on discussions with experts and issues mentioned in the emerging literature. We review significant opportunities for the U.S. dairy sector to reduce emissions, particularly through improved enteric fermentation and manure management practices. Additionally, we cover the potential for mitigating indirect emissions from feed production, processing, and transportation, areas less frequently covered in existing studies. This review also covers a gap in the literature by integrating economic findings including cost analysis and incentives to mitigate based on the social value of emissions reductions. Full article

This study begins by examining phenotypic variations in field growth among four parental Vietnamese rice lines, consisting of two Indica (PD211/GL37) and two Japonica (J23/SRA2-1) cultivars, which differ in life-cycle durations. Their phenotypic observations revealed both similarities and differences in growth patterns and field responses, setting the stage for further genomic investigation. We then focused on the sequencing and de novo genome assembly of these lines using high-coverage Illumina sequencing and achieving pseudochromosome assemblies ranging between 379 Mbp and 384 Mbp. The assemblies were further enhanced by annotation processes, designating between 44,427 and 48,704 gene models/genome. A comparative genomic analysis revealed that the Japonica varieties (J23/SRA2-1) exhibited more genetic similarity than the Indica varieties (PD211/GL37). From this, a phylogenetic analysis on the phytochrome C (phyC) gene distinctly positions the Indica and Japonica lines within their respective clades, affirming their genetic diversity and lineage accuracy. These genomic resources will pave the way for identifying quantitative trait loci (QTLs) critical for developing rice cultivars with shorter life cycles, thus enhancing resilience to adverse climatic impacts in Vietnam. This study provides a foundational step towards leveraging genomic data for rice breeding programs aimed at ensuring food security in the face of climate change. Full article

This article investigates heating options for poultry houses (or sheds) in order to meet their specific indoor air temperature requirements, with case studies conducted across Australia under conditions similar to those encountered worldwide. Hybrid geothermal–solar (PV)–gas heating systems with various configurations are proposed to minimise the lifecycle costs and GHG emissions of poultry shed heating, which involves six seven-week cycles per year. The baseload heating demand is satisfied using ground-source heat pumps (GSHPs), with solar photovoltaic panels generating the electricity needed. LPG burners satisfy the remaining heating demand. Integrating these systems with GSHPs aims to minimise the overall installation costs of the heating system. The primary focus is to curtail the costs and GHG emissions of poultry shed heating with these hybrid systems, considering three different electricity offsetting scenarios. It is found that a considerable reduction in the lifecycle cost (up to 55%) and GHG emissions (up to 50%) can be achieved when hybrid systems are used for heating. The Pareto front solutions for the systems are also determined. By comparing the Pareto front solutions for various scenarios, it is found that the shave factor, a measure of the GSHP proportion of the overall system, significantly influences the lifecycle cost, while the size and utilisation of the solar PV panels significantly affect the lifecycle GHG emissions. Full article

Vietnam’s seaport system currently includes 298 ports with 588 wharves (a total length of approximately 92,275 m), which is vital in developing Vietnam’s marine economy. The piled pier, a type of wharf structure, is widely used and accounts for up to 90%, while the remaining 10% is made up of other types of wharf structures, such as gravity and sheet pile quay walls. Most wharves have been operating for over 10 years and some for even more than 50 years. Noticeably, wharves are highly vulnerable and degrade rapidly due to many factors, especially heavy load impacts and severe environmental conditions. Additionally, wharves have a higher risk of deterioration than other inland infrastructure, such as buildings and bridges. Consequently, determining a wharf’s health is an important task in maintaining normal working conditions, extending its lifecycle, and avoiding other severe damage that could lead to dangers to the safety of vehicles, facilities, and humans. Moreover, regulated quality inspections usually include only simple inspections, e.g., displacement, settlement, geometric height, and tilt; the visual inspection and determination of dimensions by simple length-measuring equipment; concrete strength testing by ultrasonic and rebound hammers; and the experimental identification of the chloride ion concentration, chloride diffusion coefficient, corrosion activity of rebar in concrete, and steel thickness. These testing methods often give local results depending on the number of test samples. Therefore, advanced diagnostic techniques for assessing the technical condition of piled piers need to be studied. The impact vibration test (IVT) is a powerful non-destructive evaluation method that indicates the overall health of structures, e.g., underground and foundation structures, according to official standards. Hence, the IVT is expected to help engineers detect the potential deterioration of overall structures. It is fundamental that, if a structure is degraded, its natural frequency will be affected. A structure’s health index and technical condition are determined based on this change. However, the IVT does not seem to be widely applied to piled piers, with no published standard; hence, controversial issues related to accuracy and reliability still remain. This motivates the present study to recommend an adjusted factor (equal to 1.16) for the health index (classified in official standards for other structures) through numerical and experimental approaches before officially applying the IVT method to piled piers. The current work focuses on the health index using the design natural frequency, which is more practical in common cases where previous historical data and the standard natural frequency are unavailable. This study also examines a huge number of influencing factors and situations through theoretical analysis, experience, and field experiments to propose an adjusted indicator. The results are achieved with several assumptions of damages, such as the degradation of materials and local damages to structural components. With the proposed adjusted indicator, the overall health of piled piers can be assessed quickly and accurately by IVT inspections in cases of incidents, accidents due to collisions, cargo falls during loading and unloading, or subsidence and erosion due to natural disasters, storms, and floods. Full article

Wireless communication has revolutionized the evolution of humankind. The rapid growth and development of mobile communication has created an ecosystem better than what has been before. However, issues such as ample energy consumption and resulting carbon emissions, a lack of proper disposal mechanisms for large amounts of electronic waste, and the recycling of electronic materials interrupt growth. When the world is waiting for the implementation of 6G mobile communication technology, it is mandatory to resolve these issues for the sustainability of 6G technology. In this review, we present the superiority of 6G over previous generations accompanied by issues that cause extensive damage to the environment. To mitigate this adverse effect, we present a lifecycle analysis of 6G wireless communication technology from production to disposal, focusing on issues surrounding electronic waste, energy consumption, and environmental impact. This study explains the intricacies of electronic parts, toxic compounds, and the dangers of incorrect disposal techniques. It also investigates energy consumption issues specific to 6G technology, such as manufacturing processes and network infrastructures that require considerable energy. We also present a quantitative evaluation of the 6G lifecycle in detail. In addition, we present a comprehensive strategy and insights to make 6G sustainable. Furthermore, we suggest an ecological policy for all stakeholders for the sustainability of 6G. We also present political and commercial implications for 6G. As the process of 6G development continues, we show the impact of network fragmentation on standardization, which helps improve sustainability. Finally, we conclude that while the existing research has made significant advances in 6G, there is a need for correct disposal techniques to refine the key government policies for managing e-waste. New cooling technologies and renewable energy sources must be adopted to reduce the current greenhouse emission of 200 g of CO₂ and energy consumption of 2.5 kWh per GB for 6G networks. Full article

Automated industrial Visual Inspection Systems (VIS) are predominantly designed for specific use cases, resulting in constrained adaptability, high setup requirements, substantial capital investments, and significant knowledge barriers. This paper explores the business potential of recent alternative architectures proposed in the literature for the visual inspection of individual products or complex assemblies within highly variable production environments, utilizing next-generation VIS. These advanced VIS exhibit significant technical (hardware and software) enhancements, such as increased flexibility, reconfigurability, Computer Aided Design (CAD)-based integration, self-X capabilities, and autonomy, as well as economic improvements, including cost-effectiveness, non-invasiveness, and plug-and-produce capabilities. The new trends in VIS have the potential to revolutionize business models by enabling as-a-service approaches and facilitating a paradigm shift towards more sustainable manufacturing and human-centric practices. We extend the discussion to examine how these technological innovations, which reduce the need for extensive coding skills and lengthy reconfiguration activities for operators, can be implemented as a shared resource within a circular lifecycle. This analysis includes detailing the underlying business model that supports shared utilization among different stakeholders, promoting a circular economy in manufacturing by leveraging the capabilities of next-generation VIS. Such an approach not only enhances the sustainability of manufacturing processes but also democratizes access to state-of-the-art inspection technologies, thereby expanding the possibilities for autonomous manufacturing ecosystems. Full article

A hybrid electric vehicle (HEV) is a relatively practical technology that has emerged as electric vehicle technology has gradually matured. The analysis of the HEV patent lifecycle is crucial for understanding its impact on the development of this technology. This lifecycle tracks the progress of HEV technologies from their inception and patenting, through their market adoption, and to the expiration of their patent protection. In this study, we aimed to evaluate the technology lifecycle of the HEV industry using the growth S-curve method. The purpose of this study is to describe the technological lifecycle trajectory and current stage of the HEV industry, as well as the technical stages of each sub-technology, to facilitate better decision making. As part of this study, we used patent family data collected from the Derwent Innovation Index database from 1975 to 2022 and established an S-curve model for HEVs and their sub-technologies using logistic regression. In 2022, the technological maturity of HEVs reached 44%. The sub-technologies with the most substantial diffusion capabilities are energy management, propulsion systems, and cooling circuits. According to predictions, the saturation period for the patent family quantity related to HEVs is estimated to be around 53 years. Full article