Search Results (12,706)

Malus ‘Baiyun’ (registration no. 20210210), a new crabapple cultivar, was registered in 2021 by the Nanjing Forestry Unversity. However, the difficult rooting has greatly limited the production of high-quality M. ‘Baiyun’ in industrialization development. There is thus a pressing need to develop an organogenesis protocol for the in vitro propagation of M. ‘Baiyun’ to alleviate a shortage of high-quality M. ‘Baiyun’ seedlings. The results showed that choosing the apical bud in mid-March was an excellent explant material. To promote proliferation, the highest proliferation (6.27) of apical shoots was cultured on Murashige and Skoog (MS) medium supplemented with 0.5 mg·L⁻¹ 6-benzylaminopurine(6-BA) + 0.05 mg·L⁻¹ indole-3-butyric acid (IBA). Subsequently, a 100% rooting rate, average number of roots per shoot of 6.2 and maximum length of roots of 4.96 cm were obtained on half-strength Murashige and Skoog (1/2 MS) medium with the application of 0.5 mg·L⁻¹ naphthaleneacetic acid (NAA) or 0.6 mg·L⁻¹ NAA + 0.7 mg·L⁻¹ IBA. Additionally, thick and lateral roots were obtained with 0.6 mg·L⁻¹ NAA + 0.7 mg·L⁻¹ IBA. Our study is the first to establish an effective organogenesis protocol for new crabapple cultivars using stem segments. Full article

This study addresses the critical issue of cardiovascular diseases (CVDs) as the leading cause of death globally, emphasizing the importance of stent delivery catheter manufacturing. Traditional manufacturing processes, reliant on destructive end-of-batch sampling, present significant financial and quality challenges. This research addresses this challenge by proposing a novel approach: a closed-loop cyber-physical production system (CPPS) employing non-destructive process analytical technology (PAT). Through a mixed-method approach combining a comprehensive literature review and the development of a CPPS prototype, the study demonstrates the potential for real-time quality control, reduced production costs, and increased manufacturing efficiency. Initial findings showcase the system’s effectiveness in streamlining production, enhancing stability, and minimizing defects, translating to substantial financial savings and improved product quality. This work extends the author’s previous research by comparing the validated system’s performance to that of pre-implementation manual workflows and inspections, highlighting tangible and intangible improvements brought by the new system. This paves the way for advanced control strategies to revolutionize medical device manufacturing. Furthermore, the study proposes a generalized CPPS framework applicable across diverse regulated environments, ensuring optimal processing conditions and adherence to stringent regulatory standards. The research concludes with the successful demonstration of innovative approaches and technologies, leading to improved product quality, patient safety, and operational efficiency in the medical device industry. Full article

In this study, we construct heterogeneous agent general equilibrium models to investigate the relative importance of labor endowment in driving structural transformation. We aim to explore the following question: beyond the demand-side and supply-side structural transformation driving forces extensively studied in the existing literature, does labor, as a crucial endowment, play a pivotal role in facilitating structural transformation and the energy economy? In contrast to the prevalent partial equilibrium analyses, our study employs a general equilibrium framework to conduct a policy evaluation of college expansion, a significant policy that has altered the labor endowment structure in China. Our approach begins with developing a multi-sector model that integrates a nested CES production function and incorporates workers with different skill levels to assess the macroeconomic impact of college expansion on structural transformation. We calibrate the base model to reflect labor allocations across sectors and skill levels using the simulated method of moments (SMM), ensuring that the model-generated data align closely with actual labor allocation data. Utilizing this calibrated model, we perform counterfactual experiments to assess the impact and relative importance of the college expansion policy. Our counterfactual analysis demonstrates that the policy has resulted in an average decrease of 7.7% in labor allocation in the agricultural sector, alongside an average increase of 8.9% in the industry sector and 28.7% in the services sector. These results highlight the significant, yet often overlooked, contribution of labor in endowment-driven structural transformation. Furthermore, we extend the base model by constructing an industry-level heterogeneous agent general equilibrium model, enabling us to pinpoint which industries have developed as a result of the college expansion policy and recalibrate it at the industry level. This approach allows us to analyze the impact of changes in labor endowment on the energy economy. Counterfactual experiments conducted show that the college expansion policy has prompted a labor shift from industries with low energy efficiency and high pollution to high-end services. This macroeconomic pattern of structural transformation suggests that the college expansion policy has facilitated a transition toward a low-carbon economy by reducing dependency on high energy-consuming industries and promoting high-end services. Full article

The research related to subsea inspection, and the prediction of corrosion is a challenging task, and the progress in this area is continuously generating exciting new developments that may be used in subsea inspection. Wall thickness monitoring is an important tool to control and predict corrosion, such as on platforms for the infrastructure of floating offshore wind power production. This study shows the results obtained in marine environments. For this experiment, a steel plate equipped with ultrasound transducers was placed in seawater to corrode naturally. The sensor test setup consisted of 15 ultrasound transducers and 1 temperature sensor, which were installed in the cassette. The data acquisition system was based on a standard industrial computer with software written in Python and MATLAB. The ultrasound signals were collected at regular intervals and processed to calculate the instantaneous wall thickness. The progress of corrosion was evaluated by trend plots of wall thickness versus time, and the change in shape of the ultrasonic back wall reflection waveform measured by each sensor. Full article

Environmental-economic analysis is an evolving field that seeks to situate the human economy within environmental systems through its consumption of environmental resources and cycling of resources and waste products back into the environment. Environmental accounting has seen increased focus in recent years as national and regional governments look to better track environmental flows to aid in policy development and evaluation. This study outlines a conceptual environmental-economic framework founded on network science principles. An empirical study operationalizes portions of the framework and highlights the need for further research in this area to develop new data sources and analytic methods. We demonstrate a spatial mismatch between the location of water-intensive industries and the natural location of water resources (i.e., lakes, rivers, and precipitation), which climate change is likely to exacerbate. We use eigenvector centrality to measure differences in the US economy according to economic trade flow and five associated environmental flow accounts (land use, water consumption, energy use, mineral metal use, and greenhouse gas production). Population normalization helps to identify low-population counties that play a central role in the environmental-economic system as a function of their natural resources. Full article

The realization of a harmonious relationship between the natural environment and economic development has always been the unremitting pursuit of traditional mineral resource-based cities. With rich reserves of iron and coal ore resources, Laiwu has become an important steel production base in Shandong Province in China, after several decades of industrial development. However, some serious environmental problems have occurred with the quick development of local steel industries, with ground subsidence and consequent secondary disasters as the most representative ones. To better evaluate possible ground collapse risk, comprehensive approaches incorporating the common deformation monitoring with small-baseline subset (SBAS)-synthetic aperture radar interferometry (InSAR) technique, environmental factors analysis, and risk evaluation are designed here with ALOS PALSAR and Sentinel-1 SAR observations. A retrospect on the ground deformation process indicates that ground deformation has largely decreased by around 51.57% in area but increased on average by around −5.4 mm/year in magnitude over the observation period of Sentinel-1 (30 July 2015 to 22 August 2022), compared to that of ALOS PALSAR (17 January 2007 to 28 October 2010). To better reveal the potential triggering mechanism, environmental factors are also utilized and conjointly analyzed with the ground deformation time series. These analysis results indicate that the ground deformation signals are highly correlated with human industrial activities, such underground mining, and the operation of manual infrastructures (landfill, tailing pond, and so on). In addition, the evaluation demonstrates that the area with potential collapse risk (levels of medium, high, and extremely high) occupies around 8.19 km², approximately 0.86% of the whole study region. This study sheds a bright light on the safety guarantee for the industrial operation and the ecologically friendly urban development of traditional steel production industrial cities in China. Full article

Isoreticular metal-organic framework-3 (IRMOF-3), a porous coordination polymer, is an MOF material with the characteristics of a large specific surface area and adjustable pore size. Due to the existence of the active amino group (-NH₂) on the organic ligand, IRMOF-3 has more extensive research and application potential. Herein, the main preparation methods of IRMOF-3 in existing research were compared and discussed first. Second, we classified and summarized the functionalization modification of IRMOF-3 based on different reaction mechanisms. In addition, the expanded research and progress of IRMOF-3 and their derivatives in catalysis, hydrogen storage, material adsorption and separation, carrier materials, and fluorescence detection were discussed from an application perspective. Moreover, the industrialization prospect of IRMOF-3 and the pressing problems in its practical application were analyzed and prospected. This review is expected to provide a reference for the design and application of more new nanomaterials based on IRMOF-3 to develop more advanced functional materials in industrial production and engineering applications. Full article

The quality of coking coal is vital in steelmaking, impacting final product quality and process efficiency. Conventional forecasting methods often rely on empirical models and expert judgment, which may lack accuracy and scalability. Previous research has explored various methods for forecasting coking coal quality parameters, yet these conventional methods frequently fall short in terms of accuracy and adaptability to different mining conditions. Existing forecasting techniques for coking coal quality are limited in their precision and scalability, necessitating the development of more accurate and efficient methods. This study aims to enhance the accuracy and efficiency of forecasting coking coal quality parameters by employing neural networks and artificial intelligence algorithms, specifically in the context of Knurow and Szczyglowice mines. The research involves gathering historical data on various coking coal quality parameters, including a proximate and ultimate analysis, to train and test neural network models using the Group Method of Data Handling (GMDH). Real-world data from Knurow and Szczyglowice mines’ coal production facilities form the basis of this case study. The integration of neural networks and artificial intelligence techniques significantly improves the accuracy of predicting key quality parameters such as ash content, sulfur content, volatile matter, and calorific value. This study also examines the impact of these quality indicators on operational costs and highlights the importance of final indicators like the Coke Reactivity Index (CRI) and Coke Strength after Reaction (CSR) in expanding industrial reserve concepts. Model performance is evaluated using metrics such as mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). The findings demonstrate the effectiveness of these advanced techniques in enhancing predictive modeling in the mining industry, optimizing production processes, and improving overall operational efficiency. Additionally, this research offers insights into the practical implementation of advanced analytics tools for predictive maintenance and decision-making support within the mining sector. Full article

Seawater electrolysis for hydrogen production represents a substantial opportunity to curtail production expenditures and exhibits considerable potential for various industrial applications. Platinum-based precious metals exhibit excellent activity for water electrolysis. However, their limited reserves and high costs impede their widespread use on a large scale. Single-atom catalysts, characterized by low loading and high utilization efficiency, represent a viable alternative, and the development of simple synthesis methods can facilitate their practical application. In this work, we report the facile synthesis of a single-atom Pt-loaded NiCoFeS_x (Pt@NiCoFeS_x) bifunctional catalytic electrode using a simple impregnation method on a nickel foam substrate. The resulting electrode exhibits low overpotentials for both HER (60 mV@10 mA cm⁻²) and OER (201 mV@10 mA cm⁻²) in alkaline seawater electrolytes. When incorporated into a seawater electrolyzer, this electrode achieves a direct current energy consumption of only 4.18 kWh/Nm³H₂ over a 100 h test period with negligible decay. These findings demonstrate the potential of our approach for industrial-scale seawater electrolysis. Full article

Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle. Full article

In this research, an analysis of the socio-environmental vulnerability in the urban area of the border municipality of Tijuana, Baja California (BC), in Mexico is carried out with data from the year 2020. Currently, this municipality is the most populated in the country, housing a population of just over 1.9 million inhabitants, characterized by being a city in constant urban growth due to its geographical location and various social, cross-border and productive dynamics directed by industrial development. However, Tijuana presents territorial problems related to lack of urban planning, overpopulation, urban marginalization, topographic conditions, urban waste management, air quality and lack of infrastructure and basic services. The proposed methodology develops a socio-environmental vulnerability index (SEVI), based on the evaluation of critical or extreme demographic and urban aspects, including social, economic, environmental and physical variables of the territory with the support of the Geographic Information System (GIS). This index is composed of a total of 19 indicators related to education, health, employment, housing conditions, infrastructure, population settlement, industrial concentration and some factors regarding environmental quality, especially focused on the disposal of urban solid waste (USW) in clandestine sites, garbage collection service coverage and flood risk. This analysis allowed us to determine the groups most vulnerable to socio-environmental risks in 692 Basic Geostatistical Areas (AGEB, the acronym in Spanish) of nine city delegations. The results of the research highlight that 14.78% of the population is between a situation of high and very high socio-environmental vulnerability, representing just over 284,000 inhabitants. It is concluded that the use of GIS in spatial planning allows us to identify risk areas and thereby promote more sustainable measures to ensure the well-being of the population. Full article

High-temporal resolution and timely emission estimates are essential for developing refined air quality management policies. Considering the advantages of extensive coverage, high reliability, and near real-time capabilities, in this work, electric power big data (EPBD) was first employed to obtain accurate hourly resolved facility-level air pollutant emissions information from the cement industries in Tangshan City, China. Then, the simulation optimization was elucidated by coupling the data with the weather research and forecasting (WRF)-community multiscale air quality (CMAQ) model. Simulation results based on estimated emissions effectively captured the hourly variation, with the NMB within ±50% for NO₂ and PM_2.5 and R greater than 0.6 for SO₂. Hourly PM_2.5 emissions from clinker production enterprises exhibited a relatively smooth pattern, whereas those from separate cement grinding stations displayed a distinct diurnal variation. Despite the remaining underestimation and/or overestimation of the simulation concentration, the emission inventory based on EPBD demonstrates an enhancement in simulation results, with RMSE, NMB, and NME decreasing by 9.6%, 15.8%, and 11.2%, respectively. Thus, the exploitation of the vast application potential of EPBD in the field of environmental protection could help to support the precise prevention and control of air pollution, with the possibility of the early achievement of carbon peaking and carbon neutrality targets in China and other developing countries. Full article

There is an increased demand for healthy foods by the consumer nowadays, while at the same time, circular bio-economy and sustainability in food production represent top priority issues for the food industry. In this context, purslane, a highly nutritious annual plant that grows abundant during the hottest months of the year but is considered a by-product of the agricultural process, was utilized for the development of an innovative, ready-to-eat food product suitable for a vegetarian diet in the form of a bread spread. Following an initial small-scale experimentation for the stabilization of apparent quality attributes, the product’s recipe was finalized on an industrial scale, and the hazard analysis and critical control point (HACCP) for the manufacturing process, the physicochemical (pH, water activity) and sensorial analysis of the end product, together with its nutritional value, shelf-life, and antioxidant capacity, were determined. The results suggested that the acidic (pH 4.3) product had a shelf-life of a minimum of six months to one year and, according to EU legislation, it comprised a source of (dietary) fibers and protein, while being high in poly-unsaturated (e.g., omega-3, omega-6), and mono-unsaturated (e.g., oleic acid) fatty acids. Total phenolic content (TPC) with the Folin–Ciocalteau assay and total antioxidant capacity (TAC) using the Ferric-Reducing Antioxidant Power assay of the product, presented concentrations of 0.95 mg of gallic acid equivalent/g and 0.016 mmol of Fe²⁺/g of dry weight of sample, respectively. However, the predicted bioavailability for TPC and TAC was 28% and 31%, respectively. The product was evaluated positively by a panel of potential consumers without significant differences compared to conventional familiar products. The potential of using agro-food chain by-products, such as purslane, for the development of novel foods representing a healthy and tasty food choice at any time of the day is a promising opportunity for the food industry to meet growing consumer demands for more sustainable, nutritious, and healthy food products with a reduced environmental footprint compared to the traditional plant-originated products of intensive agriculture. Full article

The application of geopolymers has recently been given significant attention to address climate change and the growing scarcity of construction materials in the 21st century. Researchers have utilized industrial waste or supplementary cementitious materials containing high levels of silica and alumina as precursors along with different alkaline activators. Furthermore, the technical challenges associated with waste brick management or recycling include both land use changes and financial implications. The existence of amorphous aluminosilicates in waste clay bricks, which can be used as geopolymer binders, has drawn attention recently. This paper reviews the recent advancements of the integration of clay brick wastes in geopolymer applications, individually as well as its use with other alternative materials. Prior studies suggest that waste clay bricks can effectively serve as the primary source material in geopolymer applications. This review covers various aspects, including the assessment of fresh, mechanical, microstructure, and durability-related properties. It specifically focused on enhancing these properties of waste clay bricks through mechanical and thermal treatments, through varying curing conditions, utilizing different types of alkaline activators, and considering their properties and corresponding ratios in the development of geopolymer products using waste brick powder. Furthermore, this paper portrays a critical review of the sustainability implications of the utilization of clay brick waste in geopolymer applications. Conclusively, this review provided the lessons learnt, research gaps, and the future direction for investigation into the feasibility of geopolymers derived from waste clay brick powder. Full article

The relevance of assessing the applicability of intelligent wells using autonomous inflow control devices lies in the active development of the relevant sector of the oil and gas industry and the limited understanding of the economic efficiency of intelligent wells. The use of autonomous inflow control devices allows for a change in the composition of flow to the well, thus contributing to delaying the breakthrough of undesirable formation fluids, but at the same time, such an effect affects the dynamics of formation fluid production, which undoubtedly has a huge impact on the economic effect of the project. The analysis of scientific publications on the topic of “intelligent well completion” as a downhole production monitoring and remote production control system has shown that the vast majority of researchers pay attention to the evaluation of technological efficiency, ignoring the economic aspects of the proposed solutions. This study considered the dependence of the economic effect on the geological reservoir and technological well characteristics for variant 1—intelligent horizontal well (HW) completion using autonomous inflow control devices and variant 2—conventional horizontal well completion using the open hole. Calculations of production levels and dynamics in the two variants were performed on a created sector hydrodynamic model of a horizontal well operating in the depletion mode. The analysis of the obtained results allowed us to determine the applicability criteria of the proposed configuration of formation and well characteristics at the object of study, as well as to establish general dependencies of the net discounted income of an intelligent well. As a result of this study, it was determined that the economic efficiency of intelligent well completion with the use of autonomous inflow control devices relative to conventional well completion increases with decreasing permeability and drawdown pressure on the reservoir and reaches maximum values at the object of study at the thickness of the oil-saturated part of the reservoir about 5–6 m and the location of the wellbore in it at 35–40% of the thickness of the oil-saturated part below the gas–oil contact (GOC). This article covers the research gap in evaluating the economic efficiency of intelligent HW completion using AICD relative to conventional HW completion in oil rims. Full article