Multiple Tin Compounds Modified Carbon Fibers to Construct Heterogeneous Interfaces for Corrosion Prevention and Electromagnetic Wave Absorption

Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is considered an effective means to achieve high-efficiency EMW absorption.However,interface modulation engineering has not been fully discussed and has great potential in the field of EMW absorption.In this study,multi-component tin compound fiber composites based on carbon fiber(CF)substrate were prepared by electrospinning,hydrothermal synthesis,and high-temperature thermal reduction.By utilizing the different properties of different substances,rich heterogeneous interfaces are constructed.This effectively promotes charge transfer and enhances interfacial polarization and conduction loss.The prepared SnS/SnS_(2)/SnO_(2)/CF composites with abundant heterogeneous interfaces have and exhibit excellent EMW absorption properties at a loading of 50 wt%in epoxy resin.The minimum reflection loss(RL)is−46.74 dB and the maximum effective absorption bandwidth is 5.28 GHz.Moreover,SnS/SnS_(2)/SnO_(2)/CF epoxy composite coatings exhibited long-term corrosion resistance on Q235 steel surfaces.Therefore,this study provides an effective strategy for the design of high-efficiency EMW absorbing materials in complex and harsh environments.

Kangfuxin solution alleviates esophageal stenosis after endoscopic submucosal dissection:A natural ingredient strategy

BACKGROUND Esophageal stricture ranks among the most significant complications following endoscopic submucosal dissection(ESD).Excessive fibrotic repair is a typical pathological feature leading to stenosis after ESD.AIM To examine the effectiveness and underlying mechanism of Kangfuxin solution(KFX)in mitigating excessive fibrotic repair of the esophagus post-ESD.METHODS Pigs received KFX at 0.74 mL/kg/d for 21 days after esophageal full circumferential ESD.Endoscopic examinations occurred on days 7 and 21 post-ESD.In vitro,recombinant transforming growth factor(TGF)-β1(5 ng/mL)induced a fibrotic microenvironment in primary esophageal fibroblasts(pEsF).After 24 hours of KFX treatment(at 1.5%,1%,and 0.5%),expression ofα-smooth muscle actin-2(ACTA2),fibronectin(FN),and type collagen I was assessed.Profibrotic signaling was analyzed,including TGF-β1,Smad2/3,and phosphor-smad2/3(p-Smad2/3).RESULTS Compared to the Control group,the groups treated with KFX and prednisolone exhibited reduced esophageal stenosis,lower weight loss rates,and improved food tolerance 21 d after ESD.After treatment,Masson staining revealed thinner and less dense collagen fibers in the submucosal layer.Additionally,the expression of fibrotic effector molecules was notably inhibited.Mechanistically,KFX downregulated the transduction levels of fibrotic functional molecules such as TGF-β1,Smad2/3,and p-Smad2/3.In vitro,pEsF exposed to TGF-β1-induced fibrotic microenvironment displayed increased fibrotic activity,which was reversed by KFX treatment,leading to reduced activation of ACTA2,FN,and collagen I.The 1.5%KFX treatment group showed decreased expression of p-Smad 2/3 in TGF-β1-activated pEsF.CONCLUSION KFX showed promise as a therapeutic option for post-full circumferential esophageal ESD strictures,potentially by suppressing fibroblast fibrotic activity through modulation of the TGF-β1/Smads signaling pathway.

Dip2a regulates stress susceptibility in the basolateral amygdala

Dysregulation of neurotransmitter metabolism in the central nervous system contributes to mood disorders such as depression, anxiety, and post–traumatic stress disorder. Monoamines and amino acids are important types of neurotransmitters. Our previous results have shown that disco-interacting protein 2 homolog A(Dip2a) knockout mice exhibit brain development disorders and abnormal amino acid metabolism in serum. This suggests that DIP2A is involved in the metabolism of amino acid–associated neurotransmitters. Therefore, we performed targeted neurotransmitter metabolomics analysis and found that Dip2a deficiency caused abnormal metabolism of tryptophan and thyroxine in the basolateral amygdala and medial prefrontal cortex. In addition, acute restraint stress induced a decrease in 5-hydroxytryptamine in the basolateral amygdala. Additionally, Dip2a was abundantly expressed in excitatory neurons of the basolateral amygdala, and deletion of Dip2a in these neurons resulted in hopelessness-like behavior in the tail suspension test. Altogether, these findings demonstrate that DIP2A in the basolateral amygdala may be involved in the regulation of stress susceptibility. This provides critical evidence implicating a role of DIP2A in affective disorders.

Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.

Cortico-striatal gamma oscillations are modulated by dopamine D3 receptors in dyskinetic rats

Long-term levodopa administration can lead to the development of levodopa-induced dyskinesia.Gamma oscillations are a widely recognized hallmark of abnormal neural electrical activity in levodopa-induced dyskinesia.Currently,studies have reported increased oscillation power in cases of levodopa-induced dyskinesia.However,little is known about how the other electrophysiological parameters of gamma oscillations are altered in levodopa-induced dyskinesia.Furthermore,the role of the dopamine D3 receptor,which is implicated in levodopa-induced dyskinesia,in movement disorder-related changes in neural oscillations is unclear.We found that the cortico-striatal functional connectivity of beta oscillations was enhanced in a model of Parkinson’s disease.Furthermore,levodopa application enhanced cortical gamma oscillations in cortico-striatal projections and cortical gamma aperiodic components,as well as bidirectional primary motor cortex(M1)↔dorsolateral striatum gamma flow.Administration of PD128907(a selective dopamine D3 receptor agonist)induced dyskinesia and excessive gamma oscillations with a bidirectional M1↔dorsolateral striatum flow.However,administration of PG01037(a selective dopamine D3 receptor antagonist)attenuated dyskinesia,suppressed gamma oscillations and cortical gamma aperiodic components,and decreased gamma causality in the M1→dorsolateral striatum direction.These findings suggest that the dopamine D3 receptor plays a role in dyskinesia-related oscillatory activity,and that it has potential as a therapeutic target for levodopa-induced dyskinesia.

Effects of ultrasonic-assisted extraction on bioactive compounds,volatile flavors and antioxidant activities of vine tea water extracts

Background:Ampelopsis grossedentata,vine tea,which is the tea alternative beverages in China.In vine tea processing,a large amount of broken tea is produced,which has low commercial value.Methods:This study investigates the influence of different extraction methods(room temperature water extraction,boiling water extraction,ultrasonic-assisted room temperature water extraction,and ultrasonic-assisted boiling water extraction,referred to as room temperature water extraction(RE),boiling water extraction(BE),ultrasonic assistance at room temperature water extraction(URE),and ultrasonic assistance in boiling water extraction(UBE))on the yield,dihydromyricetin(DMY)content,free amino acid composition,volatile aroma components,and antioxidant properties of vine tea extracts.Results:A notable influence of extraction temperature on the yield of vine tea extracts(P<0.05),with BE yielding the highest at 43.13±0.26%,higher than that of RE(34.29±0.81%).Ultrasound-assisted extraction significantly increased the DMY content of the extracts(P<0.05),whereas DMY content in the RE extracts was 59.94±1.70%,that of URE reached 66.14±2.78%.Analysis revealed 17 amino acids,with L-serine and aspartic acid being the most abundant in the extracts,nevertheless ultrasound-assisted extraction reduced total free amino acid content.Gas chromatography-mass spectrometry analysis demonstrated an increase in the diversity and quantity of compounds in the vine tea water extracts obtained through ultrasonic-assisted extraction.Specifically,69 and 68 volatile compounds were found in URE and UBE extracts,which were higher than the number found in RE and BE extracts.In vitro,antioxidant activity assessments revealed varying antioxidant capacities among different extraction methods,with RE exhibiting the highest DPPH scavenging rate,URE leading in ABTS•+free radical scavenging,and BE demonstrating superior ferric ion reducing antioxidant activity.Conclusion:The findings suggest that extraction methods significantly influence the chemical composition and antioxidant properties of vine tea extracts.Ultrasonic-assisted extraction proved instrumental in elevating the DMY content in vine tea extracts,thereby enriching its flavor profile while maintaining its antioxidant properties.

Based on non-targeted metabolomics for differential components screening of Rosae Chinensis Flos and Rosae Rugosae Flos and their quality evaluation

Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.

Valorization of Camellia oleifera oil processing byproducts to value-added chemicals and biobased materials: A critical review

The C.oleifera oil processing industry generates large amounts of solid wastes,including C.oleifera shell(COS)and C.oleifera cake(COC).Distinct from generally acknowledged lignocellulosic biomass(corn stover,bamboo,birch,etc.),Camellia wastes contain diverse bioactive substances in addition to the abundant lignocellulosic components,and thus,the biorefinery utilization of C.oleifera processing byproducts involves complicated processing technologies.This reviewfirst summarizes various technologies for extracting and converting the main components in C.oleifera oil processing byproducts into value-added chemicals and biobased materials,as well as their potential applications.Microwave,ultrasound,and Soxhlet extractions are compared for the extraction of functional bioactive components(tannin,flavonoid,saponin,etc.),while solvothermal conversion and pyrolysis are discussed for the conversion of lignocellulosic components into value-added chemicals.The application areas of these chemicals according to their properties are introduced in detail,including utilizing antioxidant and anti-in-flammatory properties of the bioactive substances for the specific application,as well as drop-in chemicals for the substitution of unrenewable fossil fuel-derived products.In addition to chemical production,biochar fabricated from COS and its applications in thefields of adsorption,supercapacitor,soil remediation and wood composites are comprehensively reviewed and discussed.Finally,based on the compositions and structural characteristics of C.oleifera byproducts,the development of full-component valorization strategies and the expansion of the appli-cationfields are proposed.

Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

Nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in aerospace community:a comparative analysis

The aerospace community widely uses difficult-to-cut materials,such as titanium alloys,high-temperature alloys,metal/ceramic/polymer matrix composites,hard and brittle materials,and geometrically complex components,such as thin-walled structures,microchannels,and complex surfaces.Mechanical machining is the main material removal process for the vast majority of aerospace components.However,many problems exist,including severe and rapid tool wear,low machining efficiency,and poor surface integrity.Nontraditional energy-assisted mechanical machining is a hybrid process that uses nontraditional energies(vibration,laser,electricity,etc)to improve the machinability of local materials and decrease the burden of mechanical machining.This provides a feasible and promising method to improve the material removal rate and surface quality,reduce process forces,and prolong tool life.However,systematic reviews of this technology are lacking with respect to the current research status and development direction.This paper reviews the recent progress in the nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in the aerospace community.In addition,this paper focuses on the processing principles,material responses under nontraditional energy,resultant forces and temperatures,material removal mechanisms,and applications of these processes,including vibration-,laser-,electric-,magnetic-,chemical-,advanced coolant-,and hybrid nontraditional energy-assisted mechanical machining.Finally,a comprehensive summary of the principles,advantages,and limitations of each hybrid process is provided,and future perspectives on forward design,device development,and sustainability of nontraditional energy-assisted mechanical machining processes are discussed.

Lignin-derived hard carbon anode with a robust solid electrolyte interphase for boosted sodium storage performance

Hard carbon is regarded as a promising anode candidate for sodium-ion batteries due to its low cost,relatively low working voltage,and satisfactory specific capacity.However,it still remains a challenge to obtain a high-performance hard carbon anode from cost-effective carbon sources.In addition,the solid electrolyte interphase(SEI)is subjected to continuous rupture during battery cycling,leading to fast capacity decay.Herein,a lignin-based hard carbon with robust SEI is developed to address these issues,effectively killing two birds with one stone.An innovative gas-phase removal-assisted aqueous washing strategy is developed to remove excessive sodium in the precursor to upcycle industrial lignin into high-value hard carbon,which demonstrated an ultrahigh sodium storage capacity of 359 mAh g^(-1).It is found that the residual sodium components from lignin on hard carbon act as active sites that controllably regulate the composition and morphology of SEI and guide homogeneous SEI growth by a near-shore aggregation mechanism to form thin,dense,and organic-rich SEI.Benefiting from these merits,the as-developed SEI shows fast Na+transfer at the interphases and enhanced structural stability,thus preventing SEI rupture and reformation,and ultimately leading to a comprehensive improvement in sodium storage performance.

Effects of main components on energy output characteristics of thermobaric explosive——A case study of typical formulations

As a kind of high-efficiency explosive with compound destructive capability, the energy output law of thermobaric explosives has been receiving great attention. In order to investigate the effects of main components on the explosive characteristics of thermobaric explosives, various high explosives and oxidants were selected to formulate five different types of thermobaric explosive. Then they were tested in both open space and closed space respectively. Pressure measurement system, high-speed camera,infrared thermal imager and multispectral temperature measurement system were used for pressure,temperature and fireball recording. The effects of different components on the explosive characteristics of thermobaric explosive were analyzed. The results showed that in open space, the overpressure is dominated by the high explosives content in the formulation. The addition of the oxidants will decrease the explosion overpressure but will increase the duration and overall brightness of the fireball. While in closed space, the quasi-static pressure formed after the explosion is positively correlated with the temperature and gas production. In addition, it was found that the differences in shell constraints can also alter the afterburning reaction of thermobaric explosives, thus affecting their energy output characteristics. PVC shell constraint obviously increases the overpressure and makes the fireball burn more violently.

Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo trials.However,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based implants.Thus,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities.The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model.In addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical applications.Compared to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation.The bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in humerus.In the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy site.Principal component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D scoring.The study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

Comparison of debris flow susceptibility assessment methods:support vector machine,particle swarm optimization,and feature selection techniques

The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.

Photobiomodulation inhibits the expression of chondroitin sulfate proteoglycans after spinal cord injury via the Sox9 pathway

Both glial cells and glia scar greatly affect the development of spinal cord injury and have become hot spots in research on spinal cord injury treatment.The cellular deposition of dense extracellular matrix proteins such as chondroitin sulfate proteoglycans inside and around the glial scar is known to affect axonal growth and be a major obstacle to autogenous repair.These proteins are thus candidate targets for spinal cord injury therapy.Our previous studies demonstrated that 810 nm photo biomodulation inhibited the formation of chondroitin sulfate proteoglycans after spinal cord injury and greatly improved motor function in model animals.However,the specific mechanism and potential targets involved remain to be clarified.In this study,to investigate the therapeutic effect of photo biomodulation,we established a mouse model of spinal cord injury by T9 clamping and irradiated the injury site at a power density of 50 mW/cm~2 for 50 minutes once a day for 7 consecutive days.We found that photobiomodulation greatly restored motor function in mice and down regulated chondroitin sulfate proteoglycan expression in the injured spinal cord.Bioinformatics analysis revealed that photobiomodulation inhibited the expression of proteoglycan-related genes induced by spinal cord injury,and versican,a type of proteoglycan,was one of the most markedly changed molecules.Immunofluorescence staining showed that after spinal cord injury,versican was present in astrocytes in spinal cord tissue.The expression of versican in primary astrocytes cultured in vitro increased after inflammation induction,whereas photobiomodulation inhibited the expression of ve rsican.Furthermore,we found that the increased levels of p-Smad3,p-P38 and p-Erk in inflammatory astrocytes were reduced after photobiomodulation treatment and after delivery of inhibitors including FR 180204,(E)-SIS3,and SB 202190.This suggests that Sma d 3/Sox9 and MAP K/Sox9 pathways may be involved in the effects of photobiomodulation.In summary,our findings show that photobiomodulation modulates the expression of chondroitin sulfate proteoglycans,and versican is one of the key target molecules of photo biomodulation.MAPK/Sox9 and Smad3/Sox9 pathways may play a role in the effects of photo biomodulation on chondroitin sulfate proteoglycan accumulation after spinal cord injury.

U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

Clarifying the relationship between PM2.5 and ozone complex pollution and synoptic patterns in a typical petrochemical city in the Bohai Rim region of China:Implications for air pollution forecasting and control

Meteorological conditions are vital to PM_(2.5)and ozone(O_(3))complex pollution.Herein,the T-mode principal com-ponent analysis method was employed to objectively classify the 925-hPa geopotential height field of Dongying from 2017 to 2022.Synoptic patterns associated with four pollution types-namely,PM_(2.5)-only pollution,O_(3)-only pollution,Co-occurring of PM_(2.5)and O_(3)pollution,Non-occurring of PM_(2.5)and O_(3)pollution-were characterized at different time scales.The results indicated that synoptic classes conducive to PM_(2.5)-only pollution were“high-pressure top front”,“offshore high-pressure rear”,and“high-pressure inside”,while those conducive to O_(3)-only pollution were“offshore high-pressure rear”,“subtropical high”,and“high and low systems”.The Co-occurring of PM_(2.5)and O_(3)pollution were influenced by high pressure,and the Non-occurring of PM_(2.5)and O_(3)pollution were linked to precipitation and strong northerly winds.The variation in dominant synoptic patterns is crucial in the frequency changes of the four pollution types,which was further validated through the analysis of typical cases.Under the favorable meteorological conditions of high-pressure control with strong northerly winds or a subtropical high and inverted trough both with strong precipitation,there is potential to achieve coordinated control of PM_(2.5)and O_(3)in Dongying.Additionally,measures like artificially manipulating local humidity could be adopted to alleviate pollution levels.This study reveals the importance of comprehending the meteorological factors contributing to the formation of PM_(2.5)and O_(3)complex pollution for the improvement of urban air quality in the Bohai Rim region of China when emissions are high and the concentration of air pollutants exhibits high meteorological sensitivity.

多向孔零件机器人去毛刺工作站设计与仿真

针对多向孔零件人工去毛刺工作量大、成本高、效率低且质量不够理想的问题以及相关自动化生产的研究较少的情况,通过分析其去毛刺工艺要求,设计了一种由1台机器人和2台变位机组成的自动化去毛刺工作站。利用SolidWorks设计了去毛刺专用工装组件和去毛刺自动跟踪系统,在数字化仿真平台Visual Components中搭建了机器人去毛刺工作站布局,采用遗传算法规划最优去毛刺路径,利用仿真平台完成了编程与仿真。仿真结果表明所建立工作站布局的正确性,该研究可为多向孔零件去毛刺自动化生产线的设计与调试提供参考和理论依据。

Yields,growth and water use under chemical topping in relations to row configuration and plant density in drip-irrigated cotton

Background Water deficit is an important problem in agricultural production in arid regions.With the advent of wholly mechanized technology for cotton planting in Xinjiang,it is important to determine which planting mode could achieve high yield,fiber quality and water use efficiency(WUE).This study aimed to explore if chemical topping affected cotton yield,quality and water use in relation to row configuration and plant densities.Results Experiments were carried out in Xinjiang China,in 2020 and 2021 with two topping method,manual topping and chemical topping,two plant densities,low and high,and two row configurations,i.e.,76 cm equal rows and 10+66 cm narrow-wide rows,which were commonly applied in matching harvest machine.Chemical topping increased seed cotton yield,but did not affect cotton fiber quality comparing to traditional manual topping.Under equal row spacing,the WUE in higher density was 62.4%higher than in the lower one.However,under narrow-wide row spacing,the WUE in lower density was 53.3%higher than in higher one(farmers’practice).For machine-harvest cotton in Xinjiang,the optimal row configuration and plant density for chemical topping was narrow-wide rows with 15 plants m-2 or equal rows with 18 plants m-2.Conclusion The plant density recommended in narrow-wide rows was less than farmers’practice and the density in equal rows was moderate with local practice.Our results provide new knowledge on optimizing agronomic managements of machine-harvested cotton for both high yield and water efficient.