Short Time Research Articles

Quality assessment standards and production technology of artificial sand based on hydraulic concrete construction specifications

Natural sand and gravel resources are a local resource. Natural sand and gravel are non-renewable in a short time and are not suitable for long-distance transportation. After decades of mining, sand and gravel resources in some areas have been exhausted. The transportation distance of natural sand and gravel is getting farther and farther, and accordingly, the price of natural sand and gravel continues to rise. At the same time, continuous and disorderly mining has caused serious damage to the environment and resources. During the construction of large and medium-sized water conservancy and hydropower projects in China, due to the lack of surrounding natural aggregates, most projects use artificial aggregates. In the current national standards for water conservancy projects, the content of artificial sand and gravel powder is clearly defined. Based on the “Hydraulic Concrete Construction Specifications” (SL677-2014), this article summarizes the particle shape, gradation and surface structure of artificial sand, and also calculates the theoretical gradation of artificial sand. To find out the impact of stone powder content on the performance of artificial sand, different levels of stone powder content need to be selected for research and analysis to clarify the impact of artificial sand powder content on concrete properties. Research shows that for concrete made from artificial sand, increasing the aggregate content with a particle size less than 0.075 mm can significantly increase the compressive strength of the concrete. In artificial sand, the content of stone powder will affect the workability, polishability, durability, permeability and water release of concrete. In the artificial sand and gravel production process system, crushing and sand making equipment are the most important sand and gravel production equipment. The research results provide theoretical reference for the application of artificial sand in concrete and the update of artificial sand production technology and equipment.

Query-Oriented Micro-Video Summarization.

Query-oriented micro-video summarization task aims to generate a concise sentence with two properties: (a) summarizing the main semantic of the micro-video and (b) being expressed in the form of search queries to facilitate retrieval. Despite its enormous application value in the retrieval area, this direction has barely been explored. Previous studies of summarization mostly focus on the content summarization for traditional long videos. Directly applying these studies is prone to gain unsatisfactory results because of the unique features of micro-videos and queries: diverse entities and complex scenes within a short time, semantic gaps between modalities, and various queries in distinct expressions. To specifically adapt to these characteristics, we propose a query-oriented micro-video summarization model, dubbed QMS. It employs an encoder-decoder-based transformer architecture as the skeleton. The multi-modal (visual and textual) signals are passed through two modal-specific encoders to obtain their representations, followed by an entity-aware representation learning module to identify and highlight critical entity information. As to the optimization, regarding the large semantic gaps between modalities, we assign different confidence scores according to their semantic relevance in the optimization process. Additionally, we develop a novel strategy to sample the effective target query among the diverse query set with various expressions. Extensive experiments demonstrate the superiority of the QMS scheme, on both the summarization and retrieval tasks, over several state-of-the-art methods.

Patient trust, quality communication, and medication adherence in rheumatoid arthritis patients highly affected by social determinants of health.

Because medication adherence is essential to the management of rheumatoid arthritis (RA), identifying (1) subgroups at high risk for low medication adherence and (2) modifiable factors potentially contributing to low adherence can impact patient outcomes. This study aims to describe the relationships between anxiety, trust in the provider, quality patient-provider communication, fatigue, RA knowledge, adverse medication effects, disease activity, RA medications, disease duration, patient satisfaction, and medication intolerance and cluster factors to differentiate RA-patient subgroups. This observational study used correlation analysis, linear regression, and cluster analysis with determination decisions based on Schwarz's Bayesian Criterion. Medication adherence was higher in non-Hispanic, White participants, inversely correlated with disease activity and pain intensity, and positively correlated with trust in the provider. Patient satisfaction was higher among those with a shorter time since diagnosis, and was negatively associated with disease activity, pain intensity and interference, fatigue, and anxiety. It was positively associated with RA knowledge, trust in provider and quality of patient-provider communication. Medication intolerance differed by disease duration and was positively correlated with disease activity, pain interference, and fatigue. Of the two clusters, Cluster 1 participants had greater medication adherence and patient satisfaction, and lower medication intolerance. They were of higher income, employed, and non-Hispanic, White persons with a shorter disease duration and lower perceived pain intensity/interference, fatigue, and anxiety. They were more knowledgeable about RA with higher trust in their provider and perceived quality of patient-provider communication. A low medication adherence RA-patient subgroup-highly affected by social determinants of health and with unique relational and clinical characteristics was identified.

Influential Signs of Dry Eye-Related Ocular Symptoms in Participants With Unstable Tear Film.

The aim of this study was to investigate the factors influencing dry eye disease (DED)-related ocular symptoms in participants with short fluorescein tear break-up time (FTBUT). This cross-sectional study included 82 participants with short FTBUT (<10 seconds). Examinations included Ocular Surface Disease Index (OSDI), FTBUT, average noninvasive tear break-up time (NIBUTave), lid wiper epitheliopathy, lipid layer thickness, blink rate, partial blink, tear meniscus height, and meibomian gland (MG) evaluation which included ratio of residual MG area (RMGA) and MG grade in tarsal plates. One-way analysis of variance was used to detect differences between symptomatic tear film instability group (FTBUT <5 s, OSDI ≥13), asymptomatic tear film instability group (FTBUT <5 s, OSDI <13), and control group (FTBUT ≥5 s, OSDI <13). A bivariate correlation, partial correlation, and multiple linear regression analyses were used to identify major factors. Only the right eye was included. Among the participants with FTBUT <5 seconds, symptomatic group showed less upper RMGA ( P < 0.001) and NIBUTave ( P = 0.010). OSDI was negatively associated with upper RMGA ( r = -0.450, P < 0.001) and NIBUTave ( r = -0.414, P = 0.001), and positively associated with upper MG grade ( r = 0.277, P = 0.027). Linear regression analysis showed that the upper RMGA significantly affected OSDI (B = -41.895, P = 0.001), while not significantly correlated with age, upper MG grade, and NIBUTave. The upper RMGA might be the main factor affecting DED-related discomfort in participants with unstable tear film, indicating an early ocular change in DED.

Silica-based pyrrolidinium ionic liquid immobilised on copper-citric acid metal-organic framework, ([PyrrSi][Cl]@Cu-Cit-MOF): Heterogeneous catalysis to the multicomponent reaction for the synthesis of imidazoles

A novel, silica-based pyrrolidinium ionic liquid immobilised on copper-citric acid metal-organic framework ([PyrrSi][Cl]@Cu-Cit-MOF), has been synthesised through an easy-to-handle procedure and is characterised by several techniques such as Fourier transform infrared (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), powder X-ray diffraction (PXRD), thermal gravimetric (TG), and Brunauer-Emmett-Teller (BET) analyses. The present protocol is scalable and compatible with a wide range of aldehydes, producing imidazole derivatives in excellent yields (82-96 %) in very short reaction times (10–18 min). Moreover, the catalyst could be recovered and recycled simply by filtration and is reusable for up to six consecutive runs without any significant changes in its catalytic activity.

Ultrasound-Assisted Catalyst-free Synthesis of α,β -Unsaturated Amino Acid Esters and Unsaturated Amino Ketones

Introduction: Sonication has been introduced as a green and effective activation method for the selective monoamination of β-dicarbonyl compounds. The simple one-pot process resulted in different substituted β-amino-ɑ,β-unsaturated esters and ketones at room temperature with quantitative yields. Aqueous NH4OH was used as a safe and economical nitrogen source for pressurized NH3 gas. The process is considered green, accounting for not using any solvents and catalysts, besides some aqueous NH4OH-involved reactions using nontoxic water. A broad variety of useful synthetic intermediates, β- amino-ɑ,β-unsaturated esters and ketones have been prepared in short reaction time. Methods: Using this developed protocol, we were able to synthesize a series of structurally diverse β- amino-ɑ,β-unsaturated esters and unsaturated amino ketones. Results: The synthesis of target compounds was achieved in a truly green process with high atom economy and excellent yields in a catalyst-free one-pot system in an aqueous medium using simple, commercially available, inexpensive ammonium hydroxide as the source of the nitrogen. The high atom economy has been accompanied by the formation of a small amount of nontoxic waste, water. Conclusion: In conclusion, a simple, convenient, and high-yielding catalyst-free environmentally benign method was developed for the synthesis of unsaturated amino acid esters and unsaturated amino ketones.

Synthesis, Characterization, and Optimization of Novel Furan-ring Fused Chalcones via Radical Cyclization of α,β-Unsaturated Ketones and Cyclic Ketone

Abstract: Novel Furan-ring Fused Chalcones (FFC) were synthesized using a radical cyclization reaction of α,β-unsaturated ketones with cyclic ketone as the model reaction to attain this goal. In this study, traditional and microwave-assisted methods for the efficient and cost-effective synthesis of furan-ring fused chalcones in mild reaction conditions are compared and optimized. The goal is to develop a reliable and adaptable synthetic technique that may be used to produce these useful chalcone derivatives quickly and effectively. The optimal experimental conditions for these reactions were carefully determined using two independent methodologies: conventional (Method A) and microwave (Method B). The results indicated that the proposed method B could be used effectively in the future to synthesize novel furans with short reaction times and acceptable yields (87-94 %), and products were purified by column chromatography and preparative thin layer chromatography (PTLC). All new compounds were characterized by 1H-NMR, 13C-NMR, LC-MS, and elemental analyses.

Increasing susceptibility and shortening response time of vegetation productivity to drought from 2001 to 2021

Drought generally causes the significant reduction of vegetation productivity. Most studies focus on the vegetation response to gradual water variabilities instead of anomalies in water availability, however, the spatiotemporal patterns of vegetation response to extreme water deficits during drought are still unclear. Here, based on leaf area index (LAI) and solar-induced chlorophyll fluorescence (SIF), we employed coincidence analysis to identify the susceptibility and response time of vegetation productivity to drought, and further investigated the spatiotemporal changes of them during 2001-2021 across the globe. We found stronger susceptibility and shorter response time both in areas occupied by more grasses and in more arid regions. Temporally, we revealed a predominately increasing susceptibility (P < 0.05) and shortening response time (P < 0.05) in drought-sensitive regions from 2001 to 2021. These changes have been majorly attributable to the elevated atmospheric CO2, which tended to strengthen the susceptibility in areas covered by more grasses and in arid regions. Our finding highlighted the increasing risk of decline in vegetation production under drought particular in grasslands and drylands.

The fungal protease BbAorsin contributes to growth, conidiation, germination, virulence, and antiphytopathogenic activities in Beauveria bassiana (Hypocreales: Cordycipitaceae)

The fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), is one of the most destructive agricultural pests. The entomopathogenic fungus Beauveria bassiana (Hypocreales: Clavicipitaceae) is a biopesticide widely used for biocontrol of various pests. Secreted fungal proteases are critical for insect cuticle destruction and successful infection. We have previously shown that the serine protease BbAorsin in B. bassiana has entomopathogenic and antiphytopathogenic activities. However, the contribution of BbAorsin to fungal growth, conidiation, germination, virulence and antiphytopathogenic activities remains unclear. In this study, the deletion (ΔBbAorsin), complementation (Comp), and overexpression (BbAorsinOE) strains of B. bassiana were generated for comparative studies. The results showed that ΔBbAorsin exhibited slower growth, reduced conidiation, lower germination rate, and longer germination time compared to WT and Comp. In contrast, BbAorsinOE showed higher growth rate, increased conidiation, higher germination rate and shorter germination time. Injection of BbAorsinOE showed the highest virulence against S. frugiperda larvae, while injection of ΔBbAorsin showed the lowest virulence. Feeding BbAorsinOE resulted in lower pupation and adult eclosion rates and malformed adults. 16S rRNA sequencing revealed no changes in the gut microbiota after feeding either WT or BbAorsinOE. However, BbAorsinOE caused a disrupted midgut, leakage of gut microbiota into the hemolymph, and upregulation of apoptosis and immunity-related genes. BbAorsin can disrupt the cell wall of the phytopathogen Fusarium graminearum and alleviate symptoms in wheat seedlings and cherry tomatoes infected with F. graminearum. These results highlight the importance of BbAorsin for B. bassiana and its potential as a multifunctional biopesticide.

Assessment of biorational larvicides and botanical oils against Culex quinquefasciatus Say (Diptera: Culicidae) larvae in laboratory conditions

Mosquitoes are known vectors that transmit deadly diseases to millions of people across the globe. The reliance on synthetic insecticides has been the sole way to combat mosquito vectors for decades. In recent years, the extensive use of conventional insecticides in mosquito suppression has led to significant pesticide resistance and serious human health hazards. In this light, investigating the potential application of biorational compounds for vector management has drawn significant attention. We, hereby, evaluated the efficacy of three microbial derivative biorational insecticides, abamectin, spinosad, and buprofezin, and two botanical oils, neem (Azadirachta indica A. Juss) and karanja oil ( Pongamia pinnata Linn.) against the Culex quinquefasciatus under laboratory conditions. The fourth-instar C. quinquefasciatus larvae were exposed to different concentrations of the selected larvicides and lethality was estimated based on LC50 and LT50 with Probit analysis. All larvicides showed concentration-dependent significant effects on survival and demonstrated larvicidal activity against C. quinquefasciatus larvae. However, abamectin exerted the highest toxicity (LC50= 10.36 ppm), exhibited statistically significant effects on C. quinquefasciatus larval mortality, followed by spinosad (LC50= 21.32 ppm) and buprofezin (LC50= 56.34 ppm). Abamectin caused larval mortality ranged from 30.00 to 53.33% and 53.00 to 70.00% at 06 and 07 hours after treatment (HAT), respectively. In the case of botanicals, karanja oil (LC50 = 216.61 ppm) was more lethal (more than 1.5 times) and had a shorter lethal time than neem oil (LC50 = 330.93 ppm) and showed a classic pattern of relationship between concentrations and mortality over time. Overall, the present study highlighted the potential of deploying new generation biorational pesticides and botanicals in mosquito vector control programs.

RAC1high NK cell-based immunotherapy in hepatocellular carcinoma via STAT3-NKG2D axis

Natural killer (NK) cells exert an indispensable role in innate immune responses against cancer progression, however NK cell dysfunction has been rarely reported in hepatocellular carcinoma (HCC). This study sought to uncover the immunoregulatory mechanisms of tumor-infiltrating NK cells in HCC. A consensus NK cell-based signature (NKS) was constructed using integrative machine learning algorithms based on multi-omics data of HCC patients. HCC tumors had lower numbers of infiltrating NK cells than para-tumor normal liver tissues. Based on the NK cell-associated genes, the NKS was built for HCC prognostic prediction and clinical utilities. Drug targets and novel compounds were then identified for high-NKS groups. RAC1 was confirmed as the hub gene in the NKS genes. RAC1 was upregulated in HCC tumors and positively correlated with shorter survival time. RAC1 overexpression in NK-92 cells facilitated the cancer-killing capacity by the anticancer cytotoxic effectors and the upregulated NKG2D. The survival time of PDX-bearing mice was also prolonged upon NK-92RAC1 cells. Mechanistically, RAC1 interacted with STAT3 and facilitated its activation, thereby enabling its binding to the promoter region of NKG2D and functioning as a transcriptional regulator in NK-92 via molecular docking, Co-IP assay, CHIP and luciferase experiments. Collectively, our study describes a novel function of RAC1 in potentiating NK cell-mediated cytotoxicity against HCC, highlighting the clinical utilities of NKS score and RAC1high NK cell subset in HCC immunotherapy.

Mechanochemical and Microwave Multistep Organic Reactions

Abstract: The development of more sustainable chemical reactions and processes has been the focus of recent research activities. Advances in the field of organic synthesis have led to the emergence of new methodologies and techniques involving non-conventional energy sources. These include the applications of mechanical energy (mechanochemistry) and microwave radiation (MW) methods. This article reviews the advances in multistep organic synthesis of biologically relevant organic molecules using mechanochemistry and microwave techniques. Among them, various heterocyclic molecules (with nitrogen, oxygen, and sulphur atoms), amides, and peptides have been synthesized by multistep mechanochemical or MW reactions. Performing multiple synthetic steps using more sustainable methods shows cumulative advantages over multistep processes under conventional conditions in terms of reduced solvent use, shorter reaction times, better turnovers, and reaction yields. Simplification of protocols by carrying out two or more reaction steps in the same reaction vessel is another advantage of multistep syntheses.

Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

Unmanned aerial vehicles (UAVs) have been used for many applications including military, construction, image and video mapping, medical, search and rescue, wireless communications, and aerial surveillance. One key research topic involving UAVs is pose estimation in autonomous navigation. A standard procedure for this process for UAVs is to combine inertial navigation system (INS) sensor information with the global navigation satellite system (GNSS) signal. However, some factors can interfere with the GNSS signal, such as natural phenomena (ionospheric scintillation) or malicious attacks (jamming or spoofing). One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images. But a high effort is required for image edge extraction. In this paper, a support vector regression (SVR) model is proposed to reduce the computational load and processing time for image edge detection. The dynamic partial reconfiguration (DPR) of part of the SVR datapath was implementated to accelerate the process, reduce the area, and analyze its granularity aspect by increasing the grain size of the reconfigurable region. Results show that the implementation in hardware is 68 times faster than that in software. This kind of architecure with DPR also facilitates the low power consumption of 4 mW, leading to a reduction of 57 % compared with that without DPR, which is also the lowest power consumption compared with other machine learning (ML) hardware implementations. Besides, the circuitry area is 41 times smaller. SVR with Gaussian kernel showed a success rate of 99.18 % and minimum square error of 0.0146 for testing with the planning trajectory. This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application, thus contributing to lower power consumption, smaller hardware area, and shorter execution time.

An online battery–state of charge estimation method using the varying forgetting factor recursive least square - unscented Kalman filter algorithm on electric vehicles

Accurate and fast estimation of the state of charge is important for the battery management system of electric vehicles. This paper proposes a method to estimate the state of charge of Lithium-ion batteries by the &lt;span lang="EN-US"&gt;variable&lt;/span&gt; forgetting factor recursive least square (VFFRLS) – unscented Kalman filter (UKF) algorithm in real-time without the off-line battery testing data. Since the state observation requires an accurate model, an equivalent circuit model was constructed. Then, the VFFRLS algorithm is used to identify online the battery model parameters based on voltage and current measurements. An advantage of this algorithm is that it requires less initial information and shorter identification time than offline parameter identification. After the model parameters are well identified, the unscented Kalman filter estimates the state of charge and minimizes noise characteristics and uncertainty in the parameter identification process. The VFFRLS algorithm applied in this paper has shown a good result with the model output error of less than 1%, and the identification achieves real-time response. The state of charge obtained by the UKF algorithm has shown satisfactory estimation results with fast convergence speed and small errors. The UKF filter provides the results with a 1.5% error from the reference and converges after 10 cycles.

Effect of high temperature short time infrared roasting of peanuts

Effect of high temperature short time infrared roasting of peanuts

Wetting permeability of surface active agent droplets impacting on a layer of coal dust

The wetting and penetration of the coal dust layer by liquid droplet is crucial for suppressing coal dust. A combination of experimental and simulation methods was employed to investigate the impact of surfactant concentration, droplet velocity, and particle size on the penetration properties and their underlying mechanisms. Droplet impact wetting experiments were employed to evaluate their dynamic wetting behavior on the coal dust layer. The experimental results show that increasing the impact velocity of droplets is advantageous for enhancing the maximum dimensionless wetting length. Increasing the surfactant concentration can expedite the droplet reaching maximum dimensionless wetting volume in the dust layer. The larger the particle size of coal dust, the shorter time required for droplet to reach maximum wetting volume. The research results provide a theoretical basis for selecting and efficiently applying surfactants in treating coal dust.

Endoscopic Versus Open Carpal Tunnel Release: An Umbrella Review and a Meta-analysis.

Whether endoscopic carpal tunnel release (ECTR) versus open carpal tunnel release (OCTR) has superior outcomes remains a controversial topic. Therefore, we sought to perform an umbrella review and meta-analysis to compare ECTR and OCTR with regards to (1) postoperative functional ability, (2) operative outcomes, and (3) time to return to work. A PubMed, Scopus, and Cochrane database search was conducted for all meta-analyses comparing ECTR and OCTR performed between 2000 and 2022 in accordance to PRISMA and Joanna Briggs Institute guidance for umbrella reviews. The primary outcomes were as follows: (1) functional ability-symptoms severity, postoperative grip strength, postoperative pinch strength, 2-point discrimination, and pain; (2) operative outcomes-operation time, total complications, nerve injury, and scar-related complication; and (3) time to return to work. Quality was assessed using the Assessment of Multiple Systematic Reviews. Pooled analysis was performed to compare several clinical outcome measures between groups, depending on the availability of data using Review Manager Version 5.2.11. A total of 9 meta-analyses were included, 5 were of high quality and 4 were moderate quality. For functional ability, ECTR was associated with better pinch strength after 3 months (0.70, 95% confidence interval [CI] = 0.00, 1.40, P = 0.05) and 6 months (0.77, 95% CI = 0.14, 1.40, P = 0.02, I2 = 84%). For return to work, OCTR was associated with longer return to work compared with ECTR (-10.89, 95% CI = -15.14, -6.64, P < 0.00001, I2= 83%). There were no significant differences between OCTR and ECTR in the hand function, symptom severity, grip strength, pain, operation time, and total complications. In an umbrella review and meta-analysis of ECTR versus OCTR, ECTR was associated with a higher pinch strength, and a shorter time to return to work. Differences in major complications, such as nerve injury, were unclear due to statistical inconsistency and bias.

Investigating the chemical stability and thermal functionality of DMPT promoted TiO2 nanoparticles on unsaturated polyester resin

The incessant emergence of failures in mining roofs, along with escalating demands for high and sustainable roof support products such as resin anchor bolt capsules (resin), necessitates strengthening these elements. This study explores the transformative influence of Titanium oxide nanoparticles (TiO2) and its concentration on the chemical properties, stability, and thermal performance of polyester resin (UPE) nanocomposites. The investigation was carried out using Fourier-transform infrared (FTIR), Raman spectroscopy, and X-ray diffraction (XRD). Rheological behavior was assessed with a Brookfield viscometer, while thermal stability was examined via thermogravimetric analysis (TGA, DTG, and DTA). From the results obtained, the addition of nanoparticle TiO2 yielded a little significant change in the shift of the FTIR wavelength. However, substantial Raman peak disappearance from the peaks of the UPE neat compared to composites. The shift in Raman is associated with an increase in crystallinity due to TiO2 content. X-ray diffraction confirms the seamless presence of anatase TiO2 nanoparticles in the polyester resin matrix. The resin curing kinetics exhibit a 50-second reduction in the time to reach the exothermic peak when the nanomaterial content reaches 3% in TiO2. An increase in nanomaterial content leads to a shorter time to peak at a higher exothermic temperature, indicating improved resin cure rates. This study substantiates enhanced chemical and thermal stabilities with increasing nanomaterial content, affirming the positive impact of nanomaterial infusion on resin resilience and stability.

Proximal Junctional Degeneration and Failure Modes: A Novel Classification and Clinical Implications.

Case-control study. To introduce a classification system that will include the major types of degenerative changes and failures related to the proximal junction, and to determine the clinical course and characteristics for the different types of proximal junctional degeneration (PJD). Proximal junctional kyphosis (PJK) and failures are well recognized after adult spinal fusion, however, a standardized classification is lacking. The proposed system identified four different patterns of PJD: Type 1 (multi-level symmetrical collapse), Type 2 (Single adjacent level collapse), Type 3 (fracture) and Type 4 (spondylolisthesis). A single center database was reviewed from 2018 to 2021. Patients ≥18 years of age, who underwent posterior spinal fusion of ≥3 levels with an upper instrumented vertebral level between T8-L2, and a follow-up of ≥2 years were included. Radiographic measurements, revision surgery and time to revision were the primary outcomes. 150 patients were included with a mean age of 65.1 (±9.8) years and a mean follow-up of 3.2 (±1) years. 69 patients (46%) developed significant degenerative changes in the proximal junction, and were classified accordingly. 20 (13%) were Type 1, 17 (11%) were Type 2, 22 (15%) were Type 3 and 10 (7%) were Type 4. Type 3 had a significantly shorter time to revision with a mean of 0.9 (±0.9) years. Types 3 and 4 had greater preoperative sagittal vertical axis, and Types 1 and 3 had greater final follow-up lumbar lordosis. Bone density measured by Hounsfield units showed lower measurements for Type 3. Types 1 and 4 had lower rates of developing PJK. Type 1 had the lowest revision rate with 40% (types 2, 3 and 4 were 77%, 73% and 80%, respectively, P=0.045). This novel classification system defines different modes of degeneration and failures at the proximal junction, and future studies with larger sample sizes are needed for validation. 3.

Fast Pareto set approximation for multi-objective flexible job shop scheduling via parallel preference-conditioned graph reinforcement learning

The Multi-Objective Flexible Job Shop Scheduling Problem (MOFJSP) is a complex challenge in manufacturing, requiring balancing multiple, often conflicting objectives. Traditional methods, such as Multi-Objective Evolutionary Algorithms (MOEA), can be time-consuming and unsuitable for real-time applications. This paper introduces a novel Graph Reinforcement Learning (GRL) approach, named Preference-Conditioned GRL, which efficiently approximates the Pareto set for MOFJSP in a parallelized manner. By decomposing the MOFJSP into distinct sub-problems based on preferences and leveraging a parallel multi-objective training algorithm, our method efficiently produces high-quality Pareto sets, significantly outperforming MOEA methods in both solution quality and speed, especially for large-scale problems. Extensive experiments demonstrate the superiority of our approach, with remarkable results on large instances, showcasing its potential for real-time scheduling in dynamic manufacturing environments. Notably, for large instances (50 × 20), our approach outperforms MOEA baselines with remarkably shorter computation time (less than 1% of that of MOEA baselines). The robust generalization performance across various instances also highlights the practical value of our method for decision-makers seeking optimized production resource utilization.