Low Production Efficiency Research Articles

Based on STM32 SCM Intelligent Greenhouse

With the continuous growth of the global population and the continuous development of agricultural production, there are many problems in the traditional agricultural production mode, such as resource waste, low production efficiency, environmental pollution, and the urgent need for innovative solutions to meet the growing food demand and sustainable development goals. This paper introduces an intelligent greenhouse system based on STM 32 single-chip microcomputer, using advanced technology and automation functions, in improving the efficiency, quality and sustainability of agricultural production. The hardware composition of the intelligent greenhouse system includes STM 32 MCU, various sensor actuators, ESP8266 module and user interface module.

The risk of increasing energy demand while pursuing decarbonisation: the case of the e-fuels in the EU aviation sector

The European Union target of a net-zero economy by mid-century requires an unprecedented effort in the reduction of carbon emissions. Aviation is among the most difficult sectors to decarbonize, and since direct electrification is unlikely to become a viable option in the short-term, other alternatives are considered, including biofuels and e-fuels. The blending mandates recently approved in the ReFuelEU Aviation package (35% of e-fuels at 2050) will require devoting an important amount of renewable electricity to produce e-fuels, increasing the relative weight of aviation with respect other sectors in terms of energy consumption. Aviation accounts today for 13% of the EU27 (2019) energy consumption for transport, while in 2050 this is expected to reach the 22%. This “magnifying effect” for the energy required by the sector, due to the low overall conversion efficiency of e-fuel production, will likely foster a competition for the access to renewable energy. This shift toward the aviation sector may occur to detriment of other applications potentially most effective in decreasing carbon emissions per unit of electricity. This apparent dichotomy between GHG reduction and energy efficiency could reduce the actual effectiveness of existing policies and the possibility of fostering similar initiatives in other countries.

Axial compression behavior of mechanized filament-wound GFRP-steel tubed concrete stub columns

Filament-wound is presently the prevailing and efficient process in the field of molding, known for its ability to achieve optimal molding effects. This technique offers numerous advantages, including high precision, a high fiber content. Traditional FRP-steel tubed concrete stub columns (FSTCSCs) are fabricated by longitudinally wrapping FRP sheet, which results in low production efficiency. This paper introduces a mechanized filament-wound FSTCSC, which can achieve overall molding and effectively improve production efficiency. This paper presents an examination of the axial compression performance of mechanically wound FSTCSC. Two variables were considered including FRP wrapping angle and concrete strength. The experimental results reveal that fiber fracture of mechanized filament-wound FSTCSC is a gradual process, with damage starting from the outermost layer. When GFRP undergoes fracture, a higher wrapping angle results in enhanced restraint stiffness but reduced ductility. Moreover, the validated finite element model is used to analyze the parameters such as the wrapping angle and the thickness of GFRP tube, and it is found that adjusting both upward and downward wrapping angles plays a role in boosting the peak load carrying capacity. Furthermore, five models for predicting ultimate strengths were evaluated using test results, followed by the provision of recommendations for practical design.

Simulation Study on Reservoir Stimulation of Multihorizontal Wells for Gas Hydrate Production in Low-Permeability Reservoirs.

The feasibility of hydrate exploitation technology has been verified by two rounds of trial productions in the South China Sea, but it is also faced with the problem of low gas production efficiency. Therefore, this paper proposed four different hydrate production cases with multihorizontal wells and established simulation models. Then, the influence patterns of reservoir stimulation and offset distances on hydrate dissociation, saturation change, and pressure distribution were studied. To understand hydrate dissociation behaviors and production performances, the coupling effects of multihorizontal wells were discussed. Through simulation, the following conclusions could be drawn: (1) hydrate reservoir stimulation could effectively increase gas production. In these four production models, the cumulative gas production in Case C (multihorizontal wells + reservoir stimulation) was 5.27 times that of Case A (only multihorizontal wells) in 330 days. However, in Case D with screen completions, the gas output was 15.58% less compared with Case C. (2) Different offset distances of horizontal wells had a relatively minor impact on the cumulative gas yield and daily gas capacity. In addition, the variation range of hydrate saturation changed with offset distances of horizontal wells, indicating that hydrate dissociation occurred mainly around horizontal wells and fractures. (3) Considering interwells coupling, the daily gas rate and cumulative gas production of inner wells were higher than outer wells, and the cumulative gas volume increased by 6.4% in 330 days. Temporally and spatially, the hydrate saturation variation between wells was significantly faster than the outward expansion from the horizontal wells. Moreover, nearer to the axis of the horizontal wells, the variation in the hydrate saturation was more pronounced. These results could provide theoretical data to optimize marine hydrate development with multihorizontal wells.

Hybrid grain production in wheat benefits from synchronized flowering and high female flower receptivity.

The performance of plant hybrids relative to line breeding types is generally associated with higher yields, better adaptation, and improved yield stability. In bread wheat (Triticum aestivum L.), however, a broad commercial success for hybrids has not been accomplished until now largely due to the low efficiency of hybrid grain production, which is highly attributable to its self-pollinating nature. To better understand how hybrid wheat grains can be produced more effectively, we investigated the influence of synchronized flowering between female, i.e. male-sterile, lines and their male cross-pollinator lines as well as of the duration of flowering on hybrid grain production. We found that synchronization of flowering in combination with the longest possible temporal overlap had the largest positive effect on hybrid grain production. However, despite sufficient spatial and temporal synchronization of flowering, we also found that some female lines had lower hybrid grain set than others, suggesting genetic differences in female floral receptivity. To better assess female receptivity, we established a new phenotyping scale of male-sterile wheat flowers that provides the floral basics for effective cross-pollination. Applying this scale in our field and greenhouse trials revealed that better performing female lines remained longer in the pollen-receptive phase.

Economic Efficiency Of Pineapple Farming Using The Stochastic Frontier Approach

Central Aceh Regency is the province's largest pineapple producer. However, pineapple farming is facing the problem of low pineapple productivity and input use efficiency. The research aims to analyze the factors that influence the level of technical efficiency and the allocative and economic efficiency of pineapple farming in Pegasing District, Central Aceh Regency. The sampling process employs the stratified random sampling method. The total sample consisted of 62 respondents. The stochastic frontier is used. The research revealed that the production factor of land area, with a variable coefficient value of 0.0312, seeds with a variable coefficient value of seeds of 1.0152, and pesticides with a coefficient value of 5.6239, significantly influenced pineapple farming production in Pegasing District. Conversely, the labor factor, with a coefficient value of 0.0408, and fertilizer, with a coefficient value of 0.1198, had an insignificant effect. The use of inputs in pineapple farming has reached technical efficiency values, but there are ​still opportunities to increase optimally. However, neither allocatively nor economically have we achieved efficiency. The technical efficiency value for pineapple farmers was 0.80, the allocative efficiency value reached 0.427, and the economic efficiency was 0.351. Farmers, as actors in farming activities, need to pay attention to the use of the right combination of inputs; economic efficiency will be obtained from the use of production factors so that pineapple farmers' income will increase.

Exploring aquaculture related traits of the grooved carpet shell (Ruditapes decussatus) in relation to other bivalve species using Dynamic Energy Budget theory

To assess the potential of the grooved carpet shell (Ruditapes decussatus) for aquaculture in Europe, we used Dynamic Energy Budget (DEB) theory to perform extensive parametrization on the species and compared its energy allocation strategy with those of commonly farmed bivalve species: mussels (Mytilus edulis and Mytilus galloprovincialis), oysters (Ostrea edulis and Magallana gigas), the common cockle (Cerastoderma edule), and great scallop (Pecten maximus). The comparison was based on DEB primary parameters relevant to aquaculture production, such as maximum assimilation rate and kappa, which represents the fraction of energy allocated to maintenance and growth, and compound parameters like the von Bertalanffy growth coefficient and maximum storage density. Furthermore, we evaluated the production efficiency at the population level, which represents the ratio of assimilated energy converted into biomass. Our results revealed notable differences in energy utilization strategies among species. However, uncertainties in parameter estimation and environmental factors challenge the direct translation of these parameters to real-world aquaculture, therefore our interpretation focuses on how these parameters might influence a species’ potential for aquaculture. The grooved carpet shell exhibits a balanced energy allocation strategy with a low growth coefficient and low maintenance costs, leading to high production efficiency. Similarly, the common mussel focuses on growth with significant biomass investment over reproduction, while the Pacific oyster and Mediterranean mussel prioritize reproductive development. The flat oyster and scallop demonstrate rapid growth at the cost of the low production efficiencies. The grooved carpet shell and mussels face constraints such as limited reserves, making them comparatively more susceptible to low food quality and quantity. In contrast, high storage densities in species like the common cockle, scallop, and Pacific oyster suggest resilience to fluctuating food conditions. These findings, along with both agreements and discrepancies with existing literature, highlight the need for further experimental research to refine DEB parameters and enhance their application in aquaculture. Overall, the DEB framework proves effective for exploring aquaculture traits across species and underscores the need for additional work on temperature-related processes, life-history events, and morphological variation.

3D-Printed Complete Dentures: A Review of Clinical and Patient-Based Outcomes.

There has recently been an increasing trend to shift the fabrication of complete dentures from conventional to digital workflows to shorten the treatment time and increase patient comfort and satisfaction. Digital fabrication of complete dentures can be achieved either by a subtractive process (milling)or by an additive technique (3D printing). The milling process offers numerous advantages; however, they require large-size production machines and are associated with low production efficiency, increased cost, limited block size, and a considerable waste of material. On the other hand, 3D printing technology can potentially offer the benefits of lower manufacturing and equipment costs, good surface details, and lower material waste.Hence, 3D printing is being considered lately by some researchers as a valid choice for manufacturing digital dentures. Therefore, the aim of the current review was to identify and highlight studies on 3D-printed dentures, mainly those investigating clinical and patient-centered outcomes. A search was conducted using thedatabasesPubMed/MEDLINE, Cochrane Library, Embase, and Google Scholar. After applying the inclusion and exclusion criteria, a total of 16 studies that investigated clinical outcomes (masticatory efficiency, biting force, retention and stability, computerized occlusal analysis, and post-insertion maintenance) as well as patient-based outcomes (patient satisfaction, oral health-related quality of life (OHRQoL), patient-related complications, patient preference, and willingness to pay) were included. After a thorough review and discussion of these articles, it could be concluded that 3D printing of complete dentures offers many advantages from both a clinical and patient-based perspective. Retention and comfort with 3D-printed dentures were found to be comparable or even superior to conventional dentures. Moreover, retention of 3D-printed dentures constructed from conventional impressions and digitized casts demonstrated improved retention when compared to a protocol adopting intraoral scanning (digital impressions). Masticatory efficiency, biting force, OHRQoL, and patient satisfaction with 3D-printed dentures varied and were inconsistent among the included studies. Most of the studies reported positive results in the different domains and assessed aspects, while others reported some concerns (especially in terms of aesthetics and phonetics). With regard to post-insertion maintenance, printed dentures showed comparable results to conventional dentures in the short term. The technique seems promising with numerous benefits; however, further clinical research with larger sample sizes and longer follow-up periods is still needed to confirm these conclusions and address the potential concerns.

Research on Multi-Parameter Optimization of Conical Roller Line Processing Technology Based on Satisfaction Function

In the process of conical roller line processing, there will be problems such as low precision of processing parameters, long processing time, low utilization rate of machine tools, high rejection rate, and high processing cost, which will lead to low production efficiency. In order to solve this problem, it is necessary to iteratively optimize the size parameters, including inner diameter, ovality, and taper. By obtaining the optimal parameter combination, the size parameters in the production process are kept consistent, that is, the accuracy and performance of the workpiece during the processing are guaranteed so as to avoid the problem of quality difference, improve the production efficiency and reduce the processing cost. In view of the fact that there are often some constraints on the accuracy and efficiency in the machining process of tapered roller lines, how to optimize the parameters affecting the accuracy and the parameters affecting the efficiency to achieve balance between accuracy and efficiency in order to better meet the needs of customers for multi-objective optimization of the machining process has become the focus of research. Based on the existing research, this paper explores the multi-parameter optimization modeling and application in the machining process of tapered roller lines by constructing a satisfaction function, and then uses a genetic algorithm to iteratively search for the optimal solution by simulating natural selection and the genetic mechanism. Based on Python software v3.12, the production process of tapered roller bearings is simulated. The AHP analytic hierarchy process and CRITIC weight method are used to redistribute the parameter weights respectively. After eight iterations, it is concluded that the weight value assigned by the AHP analytic hierarchy process makes the satisfaction function value reach the best value of 0.99795 and tend to converge stably. The optimized parameter configuration significantly improves the machining accuracy and production efficiency of the tapered roller line. The optimal parameter combination is obtained: inner diameter: 9.9982 mm, ovality: 0.7 mm, taper: 0.5 degrees, production efficiency: 101.0.97 piece/h. In order to verify the optimization effect, the single value (X) and moving extreme difference (Rs) control charts in the measurement value control chart are used to analyze and verify the tolerance values of important parameters in the processing technology of the tapered roller line. The results show that the data points are all within the control limit, indicating that the processing process is in a statistical control state.

Mass Production of Multishell Hollow SiO2 Spheres With Adjustable Void Ratios and Pore Structures.

SiO2 multishell hollow spheres (MHSs) as supports have multiple porous layers and internal voids, which present notable advantages in regulating mass transport and chemical reactions. However, practical applications of SiO2 MHSs are severely hindered because of their high costs and low production efficiency issues. Herein, it is overcome these obstacles by developing a precursor hydrolysis method and demonstrate a cost-effective production of void-ratio tunable SiO2 MHSs on a large scale, which has a much lower cavitation temperature (25°C) and one order of magnitude decrease in cost. In addition, the new method can also be applied to fabricate TiO2 and SnO2 hollow spheres (HSs). In particular, an NH4Cl precipitation-pyrolysis strategy is developed to tune the pore diameters and pore distributions of SiO2 MHSs with different void ratios. SiO2 MHSs with varying void ratios and pore distributions have the broadest controlling release time ranges (30-430h). The precursor hydrolysis method and NH4Cl precipitation-pyrolysis strategy offer adequate stimulus to push forward SiO2 MHSs from laboratory-scale to industry-scale applications.

Improved Nitrate-to-Ammonia Electrocatalysis through Hydrogen Poisoning Effects.

Electrochemical conversion from nitrate to ammonia is a key step in sustainable ammonia production. However, it suffers from low productive efficiency or high energy consumption due to a lack of desired electrocatalysts. Here we report nickel cobalt phosphide (NiCoP) catalysts for nitrate-to-ammonia electrocatalysis that display a record-high catalytic current density of -702±7 mA cm-2, ammonia production rate of 5415±26 mmol gcat-1 h-1 and Faraday efficiency of 99.7±0.2 % at -0.3 V vs. RHE, affording the estimated energy consumption as low as 22.7 kWh kgammonia-1. Theoretical and experimental results reveal that these catalysts benefit from hydrogen poisoning effects under low overpotentials, which leave behind catalytically inert adsorbed hydrogen species (HI*) at Co-hollow sites and thereupon enable ideally reactive HII* at secondary Co-P sites. The dimerization between HI* and HII* for H2 evolution is blocked due to the catalytic inertia of HI* thereby the HII* drives nitrate hydrogenation timely. With these catalysts, the continuous ammonia production is further shown in an electrolyser with a real energy consumption of 18.9 kWh kgammonia-1.

Monocular Visual Pig Weight Estimation Method Based on the EfficientVit-C Model

The meat industry is closely related to people’s daily lives and health, and with the growing global population and increasing demand for meat, the development of efficient pig farming technology is particularly important. However, China’s pig industry still faces multiple challenges, such as high labor costs, high biosecurity risks, and low production efficiency. Therefore, there is an urgent need to develop a fast, accurate, and non-invasive method to estimate pig body data to increase production efficiency, enhance biosecurity measures, and improve pig health. This study proposes EfficientVit-C model for image segmentation and cascade several models to estimate the weight of pigs. The EfficientVit-C network uses a cascading group attention module and improves computational efficiency through parameter redistribution and structured pruning. This method uses only one camera for weight estimation, reducing equipment costs and maintenance expenses. The results show that the improved EfficientVit-C model can segment pigs accurately and efficiently the mAP50 curve convergence is 98.2%, the recall is 92.6%, and the precision is 96.5%. The accuracy of pig weight estimation is 100 kg +/− 3.11 kg. On the Jetson Orin NX platform, the average time to complete image segmentation for each 640*480 resolution image was 4.1 ms, and the average time required to complete pig weight estimation was 31 ms. The results show that this method can quickly and accurately estimate the weight of pigs and provide guidance for the subsequent weight evaluation procedures of pigs.

A method for accurate extraction of three-dimensional point cloud feature data in loading test of container ships

The accuracy of container slot dimensions directly affects the efficiency and safety of container loading and unloading. However, traditional methods of container loading tests need to be improved for their long cycles, high costs, and low production efficiency. With the application of three-dimensional laser scanning devices in ship manufacturing, the use of simulated container loading test methods based on point cloud becomes a breakthrough in key technology for container ship construction. This paper presents a multi-objective segmentation method of cargo hold feature point cloud for container ship simulated loading tests. Data preprocessing algorithms are applied to remove noise and pseudo-image, and then a Random Sample Consensus algorithm is used to remove bulkhead and cargo bottom point clouds. Based on the density-based spatial clustering of applications with noise algorithm and the region growing algorithm, an algorithm for multiple segmentation of guide rail and bottom cone point clouds is devised, and a four-plane segmentation of guide rail point clouds is realized. Finally, a method for three-dimensional point cloud data flatness assessment and a Hausdorff distance based method for calculating the guide rail lateral and longitudinal spacing are proposed. These methods are validated through the loading test of a 16,000 TEU container ship.

Medium optimization to improve growth and iron uptake by Bacillus tequilensis ASFS1 using fractional factorial designs

Many notable applications have been described for magnetic nanoparticles in delivery of diverse drugs and bioactive compounds into cells, magnetofection for the treatment of cancer, photodynamic therapy, photothermal therapy, and magnetic particle imaging (MPI). In response to the growing demand for magnetic nanoparticles for drug delivery or biomedical imaging applications, more effective and eco-friendly methodologies are required for large-scale biosynthesis of this nanoparticles. The major challenge in the large-scale biomedical application of magnetic nanoparticles lies in its low efficiency and optimization of nanoparticle production can address this issue. In the current study, a prediction model is suggested by the fractional factorial designs. The present study aims to optimize culture media components for improved growth and iron uptake of this strain. The result of optimization for iron uptake by the strain ASFS1 is to increase the production of magnetic nanoparticles by this strain for biomedical applications in the future. In the present study, design of experiment method was used to probe the effects of some key medium components (yeast extract, tryptone, FeSO4, Na2-EDTA, and FeCl3) on Fe content in biomass and dried biomass of strain ASFS1. A 25−1 fractional factorial design showed that Na2-EDTA, FeCl3, yeast extract-tryptone interaction, and FeSO4-Na2-EDTA interaction were the most parameters on Fe content in biomass within the experimented levels (p < 0.05), while yeast extract, FeCl3, and yeast extract-tryptone interaction were the most significant factors within the experimented levels (p < 0.05) to effect on dried biomass of strain ASFS1. The optimum culture media components for the magnetic nanoparticles production by strain ASFS1 was reported to be 7.95 g L−1 of yeast extract, 5 g L−1 of tryptone, 75 μg mL−1 of FeSO4, 192.3 μg mL−1 of Na2-EDTA and 150 μg mL−1 of FeCl3 which was theoretically able to produce Fe content in biomass (158 μg mL−1) and dried biomass (2.59 mg mL−1) based on the obtained for medium optimization. Using these culture media components an experimental maximum Fe content in biomass (139 ± 13 μg mL−1) and dried biomass (2.2 ± 0.2 mg mL−1) was obtained, confirming the efficiency of the used method.

Optimizing production efficiency in semiconductor enterprises by an improve and optimized biogeographical optimization algorithm based on three-layer coding

Aiming at the problem of low production efficiency and inability to fully unleash production capacity in current semiconductor enterprises, a production efficiency optimization model for semiconductor enterprises has been studied and constructed. This model transforms the problem of low production efficiency into a problem of locating and solving the decoupling point of enterprise customer orders, and comprehensively considers the situation of sudden changes in enterprise production orders when locating and solving the decoupling point of customer orders. Propose to use a three-layer coding (TLC) mechanism to improve and optimize the biogeographical optimization algorithm, and use the improved biogeographical optimization (IOBO) algorithm to solve the production efficiency optimization problem of semiconductor enterprises. The results show that the proposed IBBO-TCL algorithm has a fast convergence speed and the minimum root mean square error after convergence. And this method can accurately solve the decoupling point of customer orders for semiconductor enterprises. The method proposed in the study has effectively improved the production efficiency of semiconductor enterprises and has guiding significance for optimizing enterprise structure.

Acid Hydrolysis of Quinoa Starch to Stabilize High Internal Phase Emulsion Gels.

Starch nanocrystals (SNCs) to stabilize high internal phase emulsions (HIPEs) always suffer low production efficiency from acid hydrolysis. Due to its small granule size, Quinoa starch (QS) was selected to produce SNCs as a function of acid hydrolysis time (0-4 days), and their structural changes and potential application as HIPEs' stabilizers were further explored. With increasing the acid hydrolysis time from 1 day to 4 days, the yield of QS nanocrystals decreased from 30.4% to 10.8%, with the corresponding degree of hydrolysis increasing from 51.2% to 87.8%. The occurrence of QS nanocrystals was evidenced from the Tyndall effect and scanning electron microscopy with particle size distribution. The relative crystallinity of QS subjected to different hydrolysis times (0-4 days) increased from 22.27% to 26.18%. When the acid hydrolysis time of QS was 3 and 4 days, their HIPEs showed self-standing after inversion, known as high internal phase emulsion gels (HIPE gels), closely related to their densely packed interfacial architecture around oil droplets, seen on an optical microscope, and relatively high apparent viscosity. This study could provide a theoretical guidance for the efficient production and novel emulsification of SNCs from QS to HIPE gels.

An innovative walnut cracker: Self-grading and multi-station extrusion mechanism with high efficiency.

The walnut cracking process is the most critical and delicate step for achieving high-quality kernels. The traditional method for cracking (manually) is labor-intensive, time-consuming, and tedious. The existing cracking approaches are low production efficiency and serious walnut kernel breakage. Increasing cracking efficiency with minimum kernel breakage has been a challenging issue in the preliminary processing of walnuts. Therefore, this study develops an innovative walnut cracker with self-grading and multi-station extrusion, combined with theoretical investigation and experiment verification. First, a statistical analysis of walnut physical properties was conducted, including dimensions, shell thickness as well as shape characteristics. The mechanical properties of walnut cracking were examined by a series of experiments. Based on mechanical theory, a grading mechanism was designed for preliminary processing before walnut cracking. Then a shaftless screw conveying mechanism and an extrusion cracking mechanism were developed. To evaluate the cracker's performance, a comprehensive examination was carried out. The experiments yielded impressive results, with a grading rate of 87.3%, a shell-breaking rate of 91.50%, and a kernel-exposed rate of 84.72%. These outcomes signify a substantial improvement in production efficiency while minimizing kernel breakage. The developed walnut cracker plays a crucial role in walnut processing and kernel extraction, thereby elevating economic value. PRACTICAL APPLICATION: A self-grading multi-station extrusion walnut cracker is developed, which includes a grading mechanism with a shaftless screw conveyor and a grid-type trommel screen for conveying and classifying walnuts. This cracker can adapt to different walnut varieties by changing the gap-adjusting guide to control the breaking gap. Compared to similar extrusion-type walnut crackers, the developed cracker not only incorporates preliminary classification but also exhibits superior performance. HIGHLIGHTS: A novel multi-station extrusion mechanism for walnuts cracking is developed. The cracker can accommodate various walnut sizes for self-grading and screening. The design with semi-arc plates converts extrusion force into alternating stress. The shell-breaking rate and kernel-exposed rate achieves 91.50% and 84.72%.

Research on AGV Path Planning Integrating an Improved A* Algorithm and DWA Algorithm

With the rapid development of the economy and the continuous improvement of people’s living standards, the printing and packaging industry plays an increasingly important role in people’s lives. The traditional printing industry is a discrete manufacturing industry, relying on a large amount of manpower and manual operation, low production efficiency, higher labor costs, wasting of resources, and other issues, so the realization of printing factory intelligence to improve the competitiveness of the industry is an important initiative. Automatic guided vehicles (AGVs) are an important part of an intelligent factory, serving the function of automatic transportation of materials and products. To optimize the movement paths of AGVs, enhance safety, and improve transportation efficiency and productivity, this paper proposes an alternative implementation of the A* algorithm. The proposed algorithm improves search efficiency and path smoothness by incorporating the grid obstacle rate and enhancing the heuristic function within the A* algorithm’s evaluation function. This introduces the evaluation subfunction of the nearest distance between the AGV, the known obstacle, and the unknown obstacle in the global path in the dynamic window approach (DWA algorithm), and reduces the interference of obstacles with the AGV in global path planning. Finally, the two improved algorithms are combined into a new fusion algorithm. The experimental results show that the search efficiency of the fusion algorithm significantly improved and the transportation time shortened. The path smoothness significantly improved, and the closest distance to obstacles increased, reducing the risk of collision. It can thus effectively improve the productivity of an intelligent printing factory and enhance its flexibility.

Metabolic engineering of Klebsiella pneumoniae for 1, 3-propanediol production

1, 3-propanediol is an important monomer for the production of polytrimethylene terephthalate (PTT). Currently, it is mainly produced by microbial fermentation, which, however, has low production efficiency. To address this problem, this study employed atmospheric room temperature plasma (ARTP) mutagenesis technology and high-throughput screening to obtain a strain with high tolerance to osmotic pressure, which achieved a 1, 3-propanediol titer of 87 g/L. Furthermore, the gene expression elements suitable for Klebsiella pneumoniae were screened, and metabolic engineering was employed to block redundant metabolic pathways (deletion of ldhA, budA, and aldA) and enhance the synthesis pathway (overexpression of dhaB and yqhD). The titer of 1, 3-propanediol produced by the engineered strain increased to 107 g/L. Finally, in a 5 L fermenter, the optimal strain KP-FMME-6 achieved a 1, 3-propanediol titer of 118 g/L, with a glycerol conversion rate of 42% and productivity of 2.46 g/(h·L), after optimization of the fermentation parameters. This study provides a reference for the industrial production of 1, 3-propanediol.

Transient characteristics of ultra-high frequency adjustable multi-pulse gas tungsten welding arc

In response to the shortcomings of traditional Gas Tungsten Arc Welding (GTAW), such as low penetration, slow welding speed, and low production efficiency, an Ultra-High-Frequency Adjustable Multi-Pulse Gas Tungsten Arc Welding (UFMP-GTAW) process is proposed. This process more effectively concentrates the temperature distribution of the welding arc. To characterize the arc morphology and its dynamic changes, high-speed photography captured ten images of the UFMP-GTAW welding arc within one cycle. The arc image processing algorithm proposed in the paper was used to study the arc's variation characteristics over one cycle. This algorithm includes binarization, arc segmentation, and edge detection to obtain arc morphology parameters. The arc symmetry algorithm is used to symmetrize the arc images for Abel inversion, resulting in the emission coefficient distribution. Further calculations provide the temperature distribution, electrical conductivity distribution, and current density distribution of the arc. Analysis reveals that changes in arc temperature, electrical conductivity, and current density lag behind changes in current. The temperature of the arc spreads from the central axis to the surrounding arc space. When high-frequency current variations occur, the heat input generated by the current increase takes time to transfer to the entire arc space. Conversely, if the current suddenly decreases, the heat input rapidly diminishes. However, because heat transfer takes time, the arc space remains relatively stable for a short period, making the ultra-high-frequency arc form more stable.