Search Results (15,620)

In the stage of high-quality development, the functional coordination between transportation systems and territorial space is a key issue for improving urban spatial efficiency. This paper breaks through the traditional volume-to-capacity ratio analysis paradigm and innovatively integrates the “production-living-ecological space” theory. By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. Empirical research indicates that the improved accessibility indicators can precisely identify the transportation location value of regional functional cores, while the composite coordination indicators can deconstruct the spatiotemporal matching characteristics of “transportation facilities—spatial functions,” providing a dual decision-making basis for the redevelopment of existing space. This measurement system innovatively realizes the integration of planning transmission mechanisms with multi-scale application scenarios, guiding both overall spatial planning and urban renewal area re-optimization. The methodology, applied to the urban villages of Guangzhou, can significantly increase land utilization intensity and value. The research results offer a technical tool for cross-scale collaboration in land space planning reforms and provide theoretical innovations and practical guidance for the value reconstruction of existing spaces under the context of new urbanization. Full article

The mushroom Stropharia rugoso-annulata is one of the most popular varieties in the international market because it is highly nutritious and has a delicious flavor. However, grading is still performed manually, leading to inconsistent grading standards and low efficiency. In this study, deep learning and computer vision techniques were used to develop an automated air-blown grading system for classifying this mushroom into three quality grades. The system consisted of a classification module and a grading module. In the classification module, the cap and stalk regions were extracted using the YOLOv8-seg algorithm, then post-processed using OpenCV based on quantitative grading indexes, forming the proposed SegGrade algorithm. In the grading module, an air-blown grading system with an automatic feeding unit was developed in combination with the SegGrade algorithm. The experimental results show that for 150 randomly selected mushrooms, the trained YOLOv8-seg algorithm achieved an accuracy of 99.5% in segmenting the cap and stalk regions, while the SegGrade algorithm achieved an accuracy of 94.67%. Furthermore, the system ultimately achieved an average grading accuracy of 80.66% and maintained the integrity of the mushrooms. This system can be further expanded according to production needs, improving sorting efficiency and meeting market demands. Full article

In the process of high-speed wire rod production, flying steel accidents may occur due to various reasons. Current detection methods relying on sensors like hardware make debugging complex as well as limit real-time and accuracy. These methods are complicated to debug, and the real-time and accuracy of detection are poor. Therefore, this paper proposes a flying steel detection method based on improved You Only Look Once v8 (YOLOv8), which can realize high-precision flying steel detection based on machine vision through the monitoring video of the production site. Firstly, the Omni-dimensional Dynamic Convolution (ODConv) is added to the backbone network to improve the feature extraction ability of the input image. Then, a lightweight C2f-PCCA_RVB module is proposed to be integrated into the neck network, so as to carry out the lightweight design of the neck network. Finally, the Efficient Multi-Scale Attention (EMA) module is added to the neck network to fuse the context information of different scales and improve the feature extraction ability. The experimental results show that the average accuracy (mAP@0.5) of the flying steel detection method based on the improved YOLOv8 is 99.1%, and the latency is reduced to 2.5 ms, which can realize the real-time accurate detection of the flying steel. Full article

Reducing setup costs and improving product quality are critical objectives in a sustainable production processes. The significance of these goals lies in their direct impact on efficiency. It affects competitiveness and customer satisfaction. Businesses can reduce setup costs to maximize resource usage. It can reduce downtime between production runs and improve overall operational agility. Sustained performance and expansion in contemporary manufacturing environments focus on setup cost reduction and product quality improvement. The present paper discusses a production inventory model for the product, which produces by-products as secondary products from the same manufacturing process. Setup cost is reduced for the setup of production and refining processes. A production process may change from being under control to an uncontrolled one. As a result of this, imperfect products are formed. This paper considers product quality improvement for both produced and processed items. The outcome shows that dealing with by-products helps make the system more profitable. Sensitivity analysis is performed for various costs and parameters. Mathematica 11 software was used for calculation and graphical work. Full article

The United States leads in corn production and consumption in the world with an estimated USD 50 billion per year. There is a pressing need for the development of novel and efficient techniques aimed at enhancing the identification and eradication of weeds in a manner that is both environmentally sustainable and economically advantageous. Weed classification for autonomous agricultural robots is a challenging task for a single-camera-based system due to noise, vibration, and occlusion. To address this issue, we present a multi-camera-based system with decision-level sensor fusion to improve the limitations of a single-camera-based system in this paper. This study involves the utilization of a convolutional neural network (CNN) that was pre-trained on the ImageNet dataset. The CNN subsequently underwent re-training using a limited weed dataset to facilitate the classification of three distinct weed species: Xanthium strumarium (Common Cocklebur), Amaranthus retroflexus (Redroot Pigweed), and Ambrosia trifida (Giant Ragweed). These weed species are frequently encountered within corn fields. The test results showed that the re-trained VGG16 with a transfer-learning-based classifier exhibited acceptable accuracy (99% training, 97% validation, 94% testing accuracy) and inference time for weed classification from the video feed was suitable for real-time implementation. But the accuracy of CNN-based classification from video feed from a single camera was found to deteriorate due to noise, vibration, and partial occlusion of weeds. Test results from a single-camera video feed show that weed classification accuracy is not always accurate for the spray system of an agricultural robot (AgBot). To improve the accuracy of the weed classification system and to overcome the shortcomings of single-sensor-based classification from CNN, an improved Dempster–Shafer (DS)-based decision-level multi-sensor fusion algorithm was developed and implemented. The proposed algorithm offers improvement on the CNN-based weed classification when the weed is partially occluded. This algorithm can also detect if a sensor is faulty within an array of sensors and improves the overall classification accuracy by penalizing the evidence from a faulty sensor. Overall, the proposed fusion algorithm showed robust results in challenging scenarios, overcoming the limitations of a single-sensor-based system. Full article

This study evaluated the effects of different doses of limonene essential oil (LEO) and a blend of cinnamaldehyde and carvacrol (BCC) on the fermentative quality and chemical–bromatological composition of total mixed ration (TMR) silages. Two independent trials were conducted, each focused on one additive, using a completely randomized design with four treatments (0, 200, 400, and 600 mg/kg of dry matter), replicated across two seasons (summer and autumn), with five replicates per treatment per season. The silages were assessed for their chemical composition, fermentation profile, aerobic stability (AS), and storage losses. In the LEO trial, the dry matter (DM) content increased significantly by 0.047% for each mg/kg added. Dry matter recovery (DMR) peaked at 97.9% at 473 mg/kg (p < 0.01), while lactic acid (LA) production reached 5.87% DM at 456 mg/kg. Ethanol concentrations decreased to 0.13% DM at 392 mg/kg (p = 0.04). The highest AS value (114 h) was observed at 203.7 mg/kg, but AS declined slightly at the highest LEO dose (600 mg/kg). No significant effects were observed for the pH, neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP), or non-fiber carbohydrates (NFCs). In the BCC trial, DMR reached 98.2% at 548 mg/kg (p < 0.001), and effluent losses decreased by approximately 20 kg/ton DM. LA production peaked at 6.41% DM at 412 mg/kg (p < 0.001), and AS reached 131 h at 359 mg/kg. BCC increased NDF (from 23.27% to 27.73%) and ADF (from 35.13% to 41.20%) linearly, while NFCs and the total digestible nutrients (TDN) decreased by 0.0007% and 0.039% per mg of BCC, respectively. In conclusion, both additives improved the fermentation efficiency by increasing LA and reducing losses. LEO was more effective for DM retention and ethanol reduction, while BCC improved DMR and AS, with distinct effects on fiber and energy fractions. Full article

Digitization and green low-carbon are the main directions of China’s economic development in the future. This paper aims to explore the relationship between improvements in the digital level of manufacturing industry segments and carbon emissions. It is found that the digitization level of China’s manufacturing industry segments is still at a low level, which needs to be further improved, and the digitization level of technology-intensive industries is higher than that of capital-intensive and labor-intensive industries. There is a serious misallocation of production factors and R&D factors among manufacturing industries, which is mainly caused by capital factors. Improvement in the digital level of manufacturing industry segmentation can significantly improve the double-layer factor allocation efficiency of the manufacturing industry, and can synchronously realize carbon emissions reduction through improvements in the double-layer factor allocation efficiency of the manufacturing industry; in other words, the improvement in the digital level of China’s manufacturing industry has the dual effects of improving factor allocation efficiency and carbon emissions reduction. Further analysis shows that this effect has significant heterogeneity of ownership. Therefore, China should focus on accelerating the digital transformation of the manufacturing industry, improve the allocation efficiency of traditional and R&D factors in the manufacturing industry through this digital transformation, and accelerate the realization of green and low-carbon development. Full article

Naturally fractured reservoirs (NFRs) account for a significant portion of the world’s oil and gas reserves. Among them, corridor-type NFRs, characterized by discrete fracture corridors, exhibit complex flow behavior that challenges conventional development strategies and reduces recovery efficiency. A review of previous studies indicates that failing to identify these corridors often leads to suboptimal recovery, whereas correctly detecting and utilizing them can significantly enhance production. This study introduces a well-testing technique designed to identify fracture corridors and to evaluate well placement for improved recovery prediction. A simplified modeling framework is developed, combining a local model for matrix/fracture wells with a global continuous-media model representing the corridor network. Diagnostic pressure and derivative plots are used to estimate corridor properties—such as spacing and conductivity—and to determine a well’s location relative to fracture corridors. The theoretical analysis is supported by numerical simulations in CMG, which confirm the key diagnostic features and flow regime sequences predicted by the model. The results show that diagnostic patterns can be used to infer fracture corridor characteristics and to approximate well positions. The proposed method enables early-stage structural interpretation and supports practical decision-making for well placement and reservoir management in corridor-type NFRs. Full article

The demand for biomass has been growing in recent years for several reasons, related to environmental, economic, and social trends. In the context of global climate changes and the depletion of natural resources, the recycling of plant biomass waste is a promising strategy for sustainable development that contributes to minimizing waste, improving resource efficiency, and achieving the goal of creating a circular economy. One of the highly demanded products of agricultural waste recycling is glucose. Glucose is an important organic substrate that allows a number of value-added products to be obtained. In this review, we focused on the commercially significant products of glucose oxidation: gluconic and glucaric acids. This review summarized the latest available data on the scope of the application of each product as well as the methods of their production. The capabilities and limitations of currently used methods of synthesis were highlighted. Full article

Due to the health-driven demand for fat replacers in meat products, Lycopene (Lyc)-loaded yeast protein (YP) high internal phase Pickering emulsions (HIPPEs) were explored as fat replacers for 3D-printed meat products. HIPPEs with varying Lyc concentrations were formulated, and their encapsulation efficiency and antioxidant activity (DPPH and ABTS assays) were evaluated. The encapsulation efficiency of Lyc exceeded 90% for all samples. Microscopic analysis revealed significant droplet enlargement in emulsions containing Lyc concentrations of 1.25 mg/mL and 1.50 mg/mL. Antioxidant activity peaked at a Lyc concentration of 1.00 mg/mL. Three-dimensional-printed meat products with different fat replacement ratios (0%, 25%, 50%, 75% and 100%) were prepared using both Lyc-loaded and non-loaded emulsions, and their printing precision, cooking loss, color, pH, texture, and lipid oxidation were assessed. The replacement ratio had no significant impact on printing precision, while cooking yield improved with higher fat replacement levels. Lyc emulsions notably influenced meat color, resulting in lower lightness and higher redness and yellowness. pH values remained stable across formulations. Lipid oxidation decreased with increasing fat replacement levels. The results indicate that Lyc-loaded YP Pickering emulsions have great potential as effective fat replacers for 3D-printed meat products, enhancing antioxidant performance while preserving product quality. Full article

This study evaluates the agronomic and environmental performance of pelletized compost derived from olive mill waste as a sustainable alternative to mineral fertilizers for cultivating wheat (Triticum turgidum L.) under conventional tillage methods. A field experiment was conducted in semi-arid Spain, employing three fertilization strategies: inorganic (MAP + Urea), sewage sludge (SS), and organic compost pellets (OCP), each providing 150 kg N ha⁻¹. The parameters analyzed included wheat yield, grain quality, soil properties, and greenhouse gas (GHG) emissions. Inorganic fertilization yielded the highest productivity and nutrient uptake. However, the OCP treatment reduced grain yield by only 15%, while improving soil microbial activity and enzymatic responses. The SS and OCP treatments showed increased CO₂ and N₂O emissions compared to the control and inorganic plots. However, the OCP treatment also acted as a CH₄ sink. Nutrient use efficiency was greatest under mineral fertilization, though the OCP treatment outperformed the SS treatment. These results highlight the potential of OCP as a circular bio-based fertilizer that can enhance soil function and partially replace mineral inputs. Optimizing application timing is critical to aligning nutrient release with crop demand. Further long-term trials are necessary to evaluate their impact on the soil and improve environmental outcomes. Full article

Accurate, energy-efficient climate regulation is crucial for scaling smart greenhouse production. While nonlinear model predictive control (NMPC) can co-optimize yield and resource use, its efficacy hinges on short-range weather information and real-time solver feasibility. This paper investigates the performance of advanced NMPC strategies for smart greenhouse climate control, with particular emphasis on the roles of AI-driven disturbance prediction and warm-start initialization for real-time optimization. Six controller configurations, including feedback-only, LSTM-based forecast, and ideal disturbance models, each with and without warm-start, were tested in a 40-day simulation of a lettuce smart greenhouse. Performance metrics included final biomass, constraint violations, resource costs, profit, and solver time. Results show that feedback-only controllers maximize yield and profit, incurring higher CO₂ costs but lower heating costs, alongside greater constraint violations compared to the predictive strategies. Predictive and ideal disturbance-aware controllers effectively reduce resource consumption and improve constraint compliance at the expense of lower yields. Importantly, warm-start initialization significantly accelerates computation without affecting control quality. The study also demonstrates that penalty parameters, rather than economic weight settings, predominantly determine aggregate constraint violation. The findings provide actionable insights for designing and deploying NMPC-based greenhouse controllers, highlighting the importance of warm-start techniques and the trade-offs between productivity, resource efficiency, and environmental compliance. Full article

Beef production in Greece is a sector that has been characterized by a decline in both the output and the number of beef-producing animals over the last decades. The major challenge is low beef self-sufficiency; only 19.1% of demand is met by domestic production. The latter leads to a growing reliance on imports of both live animals and carcasses. Hence, the fattening of young bulls from dairy breeds could be an option to address this challenge subject to improving the quality of produced meat. The objective of the present study was to investigate the effects of extruded linseed in the diet of young bulls on their performance and meat quality. Sixty-eight young Holstein bulls were equally assigned in two experimental groups: the control group (CON, n = 34) and Linseed Group (LS, n = 34). Bulls in the CON group received a basal total mixed ration while LS young bulls were offered the same basal ration supplemented with linseed (5% on dry matter basis) during the final fattening stage. All bulls were subjected to three individual weightings at the beginning, the middle and the end of the trial. The feed offered was recorded daily and feed refusals were weighed for each pen to calculate feed intake. After slaughter, the Longissimus dorsi muscle from each carcass was collected to evaluate meat pH, color, chemical composition, tenderness and fatty acid profile. Analysis of variance was used to evaluate the effect of dietary intervention on performance and examined meat parameters, with significance set at p < 0.05, using SPSS software (version 29.0). Average daily gain, dry matter intake and feed conversion ratio were not affected by the dietary intervention (p > 0.05). Similarly, carcass yield and dressing percentage remained unaffected (p > 0.05). Adding extruded linseed did not result in differences in meat quality traits (p > 0.05), except for meat pH, which was significantly decreased in the LS group (p < 0.05), indicating more efficient post-mortem glycolysis. Finally, the inclusion of extruded linseed resulted in higher levels of α-linolenic acid in the meat (p < 0.05). These results suggest that including 5% extruded linseed (on a DM basis) in the diet of young Holstein bulls increased meat n-3 content, improved beef pH and maintained production performance. Full article

Soybean production in Thailand faces significant challenges from malignant weed competition, potentially reducing yields by up to 37% and incurring annual economic losses of approximately USD 3.8 billion. Pre-emergence herbicides are critical for integrated weed management, but their efficacy varies depending on local conditions and soybean varieties. This study evaluates the performance of three pre-emergence herbicides, pendimethalin (1875 g a.i. ha⁻¹), s-metolachlor (900 g a.i. ha⁻¹), and flumioxazin (125 g a.i. ha⁻¹), on weed control efficiency (WCE), soybean growth, phytotoxicity, and yield in Northeast Thailand using a randomised complete block design with two varieties (CM60 and Morkhor60) across rainy (2023) and dry (2024/2025) seasons. Herbicide performance varied seasonally: s-metolachlor showed optimal rainy season results (61.54% weed control efficiency at 63 days after herbicide application (DAA), with a yield of 1036 kg ha⁻¹), while flumioxazin excelled in dry conditions (64.32% WCE, <4% phytotoxicity, and 1243 kg ha⁻¹ yield). Pendimethalin performed poorly under wet conditions but improved in drier weather. Among five dominant weed species, Cyperus rotundus proved the most resilient. CM60 demonstrated superior herbicide tolerance and yield stability, particularly under rainy conditions. These results emphasise that season-specific herbicide selection and variety matching are crucial for herbicide resistance management and effective weed control in Thailand’s rainfed soybean systems. Full article

Phosphorous slag is an industrial by-product generated in the process of producing yellow phosphorus by electric furnace, which occupies a substantial number of land resources and causes serious environmental pollution. The comprehensive utilization of phosphorous slag is a major topic relevant to the sustainability of the yellow phosphorus industry. In this paper, we attempted to utilize phosphorous slag as a supplementary cementing material to prepare silica-aluminum based cementitious material (SAC-PHS). To determine how phosphorus influences the early-age hydration reaction process of silica-aluminum based cementitious material, three groups of samples, PHS₂₀, PHS₂₅, and PHS₃₀, with better mechanical properties were selected to deeply investigate their one-week hydration characteristics. Characterization results showed that the main hydration products of SAC-PHS were C-A-S-H gels and ettringite. PHS₂₅ specimen produced more C-A-S-H gels and ettringite than the other two samples after one-week hydration. Interestingly, the P/Si atomic ratio indicated that chemical bonds were formed between Si and P during the formation of C-A-S-H gels, which improved the strength of SAC-PHS. Our findings offer valuable insights for the application of phosphorous slag in construction and building materials and promote the efficient resource utilization of phosphorous residue. Full article