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.

Discrimination of polysorbate 20 by high-performance liquid chromatography-charged aerosol detection and characterization for components by expanding compound database and library

Analyzing polysorbate 20(PS20)composition and the impact of each component on stability and safety is crucial due to formulation variations and individual tolerance.The similar structures and polarities of PS20 components make accurate separation,identification,and quantification challenging.In this work,a high-resolution quantitative method was developed using single-dimensional high-performance liquid chromatography(HPLC)with charged aerosol detection(CAD)to separate 18 key components with multiple esters.The separated components were characterized by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UHPLC-Q-TOF-MS)with an identical gradient as the HPLC-CAD analysis.The polysorbate compound database and library were expanded over 7-time compared to the commercial database.The method investigated differences in PS20 samples from various origins and grades for different dosage forms to evaluate the composition-process relationship.UHPLC-Q-TOF-MS identified 1329 to 1511 compounds in 4 batches of PS20 from different sources.The method observed the impact of 4 degradation conditions on peak components,identifying stable components and their tendencies to change.HPLC-CAD and UHPLC-Q-TOF-MS results provided insights into fingerprint differences,distinguishing quasi products.

Multi-omics analyses provide insights into the evolutionary history and the synthesis of medicinal components of the Chinese wingnut

Chinese wingnut(Pterocarya stenoptera)is a medicinally and economically important tree species within the family Juglandaceae.However,the lack of high-quality reference genome has hindered its in-depth research.In this study,we successfully assembled its chromosome-level genome and performed multiomics analyses to address its evolutionary history and synthesis of medicinal components.A thorough examination of genomes has uncovered a significant expansion in the Lateral Organ Boundaries Domain gene family among the winged group in Juglandaceae.This notable increase may be attributed to their frequent exposure to flood-prone environments.After further differentiation between Chinese wingnut and Cyclocarya paliurus,significant positive selection occurred on the genes of NADH dehydrogenase related to mitochondrial aerobic respiration in Chinese wingnut,enhancing its ability to cope with waterlogging stress.Comparative genomic analysis revealed Chinese wingnut evolved more unique genes related to arginine synthesis,potentially endowing it with a higher capacity to purify nutrient-rich water bodies.Expansion of terpene synthase families enables the production of increased quantities of terpenoid volatiles,potentially serving as an evolved defense mechanism against herbivorous insects.Through combined transcriptomic and metabolomic analysis,we identified the candidate genes involved in the synthesis of terpenoid volatiles.Our study offers essential genetic resources for Chinese wingnut,unveiling its evolutionary history and identifying key genes linked to the production of terpenoid volatiles.

Simultaneous purification of minor components in natural products using twin-column recycling chromatography with a step solvent gradient

The isolation of minor components from complex natural product matrices presents a significant challenge in the field of purification science due to their low concentrations and the presence of structurally similar compounds.This study introduces an optimized twin-column recycling chromatography method for the efficient and simultaneous purification of these elusive constituents.By introducing water at a small flowing rate between the twin columns,a step solvent gradient is created,by which the leading edge of concentration band would migrate at a slower rate than the trailing edge as it flowing from the upstream to downstream column.Hence,the band broadening is counterbalanced,resulting in an enrichment effect for those minor components in separation process.Herein,two target substances,which showed similar peak position in high performance liquid chromatography(HPLC)and did not exceed 1.8%in crude paclitaxel were selected as target compounds for separation.By using the twin-column recycling chromatography with a step solvent gradient,a successful purification was achieved in getting the two with the purity almost 100%.We suggest this method is suitable for the separation of most components in natural produces,which shows higher precision and recovery rate compared with the common lab-operated separation ways for natural products(thin-layer chromatography and prep-HPLC).

π-Extended giant dimeric acceptor as a third component enables highly efficient ternary organic solar cells with efficiency over 19.2%

Ternary strategy with a suitable third component is a successful strategy to improve the photovoltaic performance of organic solar cells(OSCs).Very recently,Y-series based giant molecule acceptors or oligomerized acceptors have emerged as promising materials for achieving highly efficient and stable binary OSCs,while application as third component for ternary OSCs is limited.Here a novelπ-extended giant dimeric acceptor,GDF,is developed based on central Y series core fusion and rigid BDT as linker,and then incorporated into the state-of-the-art PM1:PC6 system to construct ternary OSCs.The GDF has a near planar backbone,resulting in increasedπ-conjugation,excellent crystallinity,and good electron transport capacity.When GDF is introduced into the PM1:PC6 system,it ensues in a cascade like the lowest unoccupied molecular orbitals(LUMO)energy level alignment,a complementary absorption band with PM1 and PC6,higher and balanced hole and electron mobility,slightly smaller domain size,and a higher exciton dissociation probability for PM1:PC6:GDF(1:1.1:0.1)blend film.As a consequence,the PM1:PC6:GDF(1:1.1:0.1)ternary OSC achieves a champion PCE of 19.22%,with a significantly higher open-circuit voltage and short-circuit current density,compared to 18.45%for the PM1:PC6(1:1.2)binary OSC.Our findings show that employing aπ-extended giant dimeric acceptor as a third component significantly improves the photovoltaic performance of ternary OSCs.

Meter-Scale Thin-Walled Structure with Lattice Infill for Fuel Tank Supporting Component of Satellite:Multiscale Design and Experimental Verification

Lightweight thin-walled structures with lattice infill are widely desired in satellite for their high stiffness-to-weight ratio and superior buckling strength resulting fromthe sandwich effect.Such structures can be fabricated bymetallic additive manufacturing technique,such as selective laser melting(SLM).However,the maximum dimensions of actual structures are usually in a sub-meter scale,which results in restrictions on their appliance in aerospace and other fields.In this work,a meter-scale thin-walled structure with lattice infill is designed for the fuel tank supporting component of the satellite by integrating a self-supporting lattice into the thickness optimization of the thin-wall.The designed structure is fabricated by SLM of AlSi10Mg and cold metal transfer welding technique.Quasi-static mechanical tests and vibration tests are both conducted to verify the mechanical strength of the designed large-scale lattice thin-walled structure.The experimental results indicate that themeter-scale thin-walled structure with lattice infill could meet the dimension and lightweight requirements of most spacecrafts.

The water-soluble TF3 component from Eupolyphaga sinensis Walker promotes tibial fracture healing in rats by promoting osteoblast proliferation and angiogenesis

Objective:To determine the active components of Eupolyphaga sinensis Walker(Tu Bie Chong)and explore the mechanisms underlying its fracture-healing ability.Methods: A modified Einhorn method was used to develop a rat tibial fracture model.Progression of bone healing was assessed using radiological methods.Safranin O/fast green and CD31 immunohistochemical staining were performed to evaluate the growth of bone cells and angiogenesis at the fracture site.Methylthiazoletetrazolium blue and wound healing assays were used to analyze cell viability and migration.The Transwell assay was used to explore the invasion capacity of the cells.Tubule formation assays were used to assess the angiogenesis capacity of human vascular endothelial cells(HUVECs).qRT-PCR was used to evaluate the changes in gene transcription levels.Results: Tu Bie Chong fraction 3(TF3)significantly shortened the fracture healing time in model rats.X-ray results showed that on day 14,fracture healing in the TF3 treatment group was significantly better than that in the control group(P=.0086).Tissue staining showed that cartilage growth and the number of H-shaped blood vessels at the fracture site of the TF3 treatment group were better than those of the control group.In vitro,TF3 significantly promoted the proliferation and wound healing of MC3T3-E1s and HUVECs(all P<.01).Transwell assays showed that TF3 promoted the migration of HUVECs,but inhibited the migration of MC3T3-E1 cells.Tubule formation experiments confirmed that TF3 markedly promoted the ability of vascular endothelial cells to form microtubules.Gene expression analysis revealed that TF3 significantly promoted the expression of VEGFA,SPOCD1,NGF,and NGFR in HUVECs.In MC3T3-E1 cells,the transcript levels of RUNX2 and COL2A1 were significantly elevated following TF3 treatment.Conclusion: TF3 promotes fracture healing by promoting bone regeneration associated with the RUNX2 pathway and angiogenesis associated with the VEGFA pathway.

Umami taste components in chicken-spices blends and potential effect of aroma on umami taste intensity

In this study,umami taste intensity(UTI)and umami taste components in chicken breast(CB)and chickenspices blends were characterized using sensory and instrumental analysis.Our main objective was to assess the aroma-umami taste interactions in different food matrices and reconcile the aroma-taste perception to assist future product development.The impact of key aroma,including vegetable-note"2-pentylfuran",meaty"methional",green"hexanal",and spicy-note-estragole and caryophyllene"on UTI was evaluated in monosodium glutamate and chicken extract.We found that spices significantly decreased UTI and umami taste components in CB.Interestingly,the perceptually similar odorants and tastants exhibited the potential to enhance UTI in food matrices.Methional was able to increase the UTI,whereas spicy and green-note components could reduce the UTI significantly.This information would be valuable to food engineers and formulators in aroma selection to control the UTI perceived by consumers,thus,improving the quality and acceptability of the chicken products.

Association of complement components with risk of colorectal cancer:A systematic review and meta-analysis

BACKGROUND Complement components could contribute to the tumor microenvironment and the systemic immune response.Nevertheless,their role in colorectal cancer(CRC)remains a contentious subject.AIM To elucidate the relationship between complement components and CRC risk and clinical characteristics.METHODS Searches were conducted in PubMed,the Cochrane Library,and the China National Knowledge Infrastructure database until June 1,2023.We included cohort studies encompassing participants aged≥18 years,investigating the association between complement components and CRC.The studies were of moderate quality or above,as determined by the Agency for Healthcare Research and Quality.The meta-analysis employed fixed-effects or random-effects models based on the I^(2)test,utilizing risk ratio(RR)and their corresponding 95%confidence interval(CI)for outcomes.Sensitivity and subgroup analyses were performed to validate the robustness of the collective estimates and identify the source of heterogeneity.RESULTS Data from 15 studies,comprising 1631 participants that met the inclusion criteria,were included in the meta-analysis.Our findings indicated that protein levels of cluster of differentiation 46(CD46)(RR=3.66,95%CI:1.75-7.64,P<0.001),CD59(RR=2.86,95%CI:1.36-6.01,P=0.005),and component 1(C1)(RR=5.88,95%CI:1.75-19.73,P=0.004)and serum levels of C3(standardized mean difference=1.82,95%CI:0.06-3.58,P=0.040)were significantly elevated in patients with CRC compared to healthy controls.Strong expression of CD55 or CD59 was associated with a higher incidence of lymph node metastasis,whereas strong CD46 expression correlated with a higher incidence of tumor differentiation compared to low CD46 expression(P<0.05 for all).Although specific pooled results demonstrated notable heterogeneity,subgroup analyses pointed to regional differences as the primary source of inconsistency among the studies.CONCLUSION Our analysis underscores that increased levels of specific complement components are associated with a heightened risk of CRC,emphasizing the potential significance of monitoring elevated complement component levels.

A novel approach of jet polishing for interior surface of small-grooved components using three developed setups

It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm.Traditional polishing methods are disabled to polish the component,meanwhile keeping the structure intact.To overcome this challenge,small-grooved components made of aluminum alloy with sizes less than 1 mm were fabricated by a custom-made printer.A novel approach to multi-phase jet(MPJ)polishing is proposed,utilizing a self-developed polisher that incorporates solid,liquid,and gas phases.In contrast,abrasive air jet(AAJ)polishing is recommended,employing a customized polisher that combines solid and gas phases.After jet polishing,surface roughness(Sa)on the interior surface of grooves decreases from pristine 8.596μm to 0.701μm and 0.336μm via AAJ polishing and MPJ polishing,respectively,and Sa reduces 92%and 96%,correspondingly.Furthermore,a formula defining the relationship between linear energy density and unit defect volume has been developed.The optimized parameters in additive manufacturing are that linear energy density varies from 0.135 J mm^(-1)to 0.22 J mm^(-1).The unit area defect volume achieved via the optimized parameters decreases to 1/12 of that achieved via non-optimized ones.Computational fluid dynamics simulation results reveal that material is removed by shear stress,and the alumina abrasives experience multiple collisions with the defects on the heat pipe groove,resulting in uniform material removal.This is in good agreement with the experimental results.The novel proposed setups,approach,and findings provide new insights into manufacturing complex-structured components,polishing the small-grooved structure,and keeping it unbroken.

The bio-active components of the Mongolian medicine Horcha-6 and therapeutic mechanism in the rat migraine model

Background:The active components of Horcha-6 were identified using liquid chromatography with tandem mass spectrometry.Also,we investigated the potential mechanisms that explain why Horcha-6 may be effective in treating migraines through the use of network pharmacology and a rat migraine model.Methods:After identifying the active components of Horcha-6,the corresponding genes of the active components’target were obtained from the Universal Protein database,and a“compound-target-disease”network was constructed using Cytoscape 3.9.0 software.For the in vivo experiments,nitroglycerin was injected intraperitoneally into rats to create a migraine model.Pre-treatment with Horcha-6 was administered orally for 14 days,and rats were subjected to migraine-related behavior tests.RNA sequencing was performed to identify the gene expression regulated by Horcha-6 in the trigeminal nerve.Results:A total of 903 chemical components of Horcha-6 have been collected in the liquid chromatography with tandem mass spectrometry.We discovered 55 of the Horcha-6 bio-active components that were evaluated based on their Percent Human Oral Absorption(≥30%)and DL values(≥0.185)on the traditional Chinese medicine systems pharmacology database.The“compound-target-disease”network contained 163 intersection targets with the migraine state.Gene Ontology analysis indicated that these components significantly regulated the immune response,vascular function,oxidative stress,etc.When Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed,we observed that most of the target genes were significantly enriched in the inflammation and neuro-related signaling pathway,toll-like receptor signaling pathway,neuroactive ligand-receptor interaction,etc.These predictions were further demonstrated via in vivo animal model experiments.The RNA sequencing results showed that 41 genes were down-regulated(P<0.05)and 86 genes were up-regulated(P<0.05)in the Horcha-6 treated group compared with the untreated group.Those genes were mainly involved in neuromodulation,vascular function,and hormone metabolism.Conclusion:The 55 bio-active components in Horcha-6 regulate inflammation,hormone metabolism,and neurotransmitters and have potential as a therapy to treat migraines.

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.

“Component flow”conditions and its effects on enhancing production of continental medium-to-high maturity shale oil

Based on the production curves,changes in hydrocarbon composition and quantities over time,and production systems from key trial production wells in lacustrine shale oil areas in China,fine fraction cutting experiments and molecular dynamics numerical simulations were conducted to investigate the effects of changes in shale oil composition on macroscopic fluidity.The concept of“component flow”for shale oil was proposed,and the formation mechanism and conditions of component flow were discussed.The research reveals findings in four aspects.First,a miscible state of light,medium and heavy hydrocarbons form within micropores/nanopores of underground shale according to similarity and intermiscibility principles,which make components with poor fluidity suspended as molecular aggregates in light and medium hydrocarbon solvents,such as heavy hydrocarbons,thereby decreasing shale oil viscosity and enhancing fluidity and outflows.Second,small-molecule aromatic hydrocarbons act as carriers for component flow,and the higher the content of gaseous and light hydrocarbons,the more conducive it is to inhibit the formation of larger aggregates of heavy components such as resin and asphalt,thus increasing their plastic deformation ability and bringing about better component flow efficiency.Third,higher formation temperatures reduce the viscosity of heavy hydrocarbon components,such as wax,thereby improving their fluidity.Fourth,preservation conditions,formation energy,and production system play important roles in controlling the content of light hydrocarbon components,outflow rate,and forming stable“component flow”,which are crucial factors for the optimal compatibility and maximum flow rate of multi-component hydrocarbons in shale oil.The component flow of underground shale oil is significant for improving single-well production and the cumulative ultimate recovery of shale oil.

Robust Principal Component Analysis Integrating Sparse and Low-Rank Priors

Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Analysis (RPCA) addresses these limitations by decomposing data into a low-rank matrix capturing the underlying structure and a sparse matrix identifying outliers, enhancing robustness against noise and outliers. This paper introduces a novel RPCA variant, Robust PCA Integrating Sparse and Low-rank Priors (RPCA-SL). Each prior targets a specific aspect of the data’s underlying structure and their combination allows for a more nuanced and accurate separation of the main data components from outliers and noise. Then RPCA-SL is solved by employing a proximal gradient algorithm for improved anomaly detection and data decomposition. Experimental results on simulation and real data demonstrate significant advancements.

Optimizing data aggregation and clustering in Internet of things networks using principal component analysis and Q-learning

The Internet of things(IoT)is a wireless network designed to perform specific tasks and plays a crucial role in various fields such as environmental monitoring,surveillance,and healthcare.To address the limitations imposed by inadequate resources,energy,and network scalability,this type of network relies heavily on data aggregation and clustering algorithms.Although various conventional studies have aimed to enhance the lifespan of a network through robust systems,they do not always provide optimal efficiency for real-time applications.This paper presents an approach based on state-of-the-art machine-learning methods.In this study,we employed a novel approach that combines an extended version of principal component analysis(PCA)and a reinforcement learning algorithm to achieve efficient clustering and data reduction.The primary objectives of this study are to enhance the service life of a network,reduce energy usage,and improve data aggregation efficiency.We evaluated the proposed methodology using data collected from sensors deployed in agricultural fields for crop monitoring.Our proposed approach(PQL)was compared to previous studies that utilized adaptive Q-learning(AQL)and regional energy-aware clustering(REAC).Our study outperformed in terms of both network longevity and energy consumption and established a fault-tolerant network.

QTL Mapping of Yield and Yield Components for Elite Hybrid Derived-RILs in Upland Cotton

A population of 180 recombinant inbred lines （RILs） was developed by single seed descended from the cross of high yield Upland cotton （Gossypium hirsutum L.） varieties Zhongmiansuo12 （ZMSI2） and 8891, the two parents of Xiangzamian2 （XZM2）. A genetic linkage map consisting of 132 loci and covering 865.20 cM was constructed using the RIL population chiefly with SSR markers. Yield and yield components were investigated for RILs in three environments in China. The purpose of the present research was to analyze the relationship between yield and its components and to map QTL for yield and yield components in cotton. QTL were tagged with data sets from single environment （separate analysis） and a set of data from means of the three environments （joint analysis）. A total of 34 QTL for yield and yield components were independently detected in three environments, whereas fifteen QTL were found in joint analysis. Notably, a stable lint percentage QTL qLP-A10-1 was detected both in joint analysis and in two environments of separate analysis, which might be of special value for marker-assisted selection. The QTL detected in the present study provide new information on improving yield and yield components. Results of path analysis showed that bolls/plant had the largest contribution to lint yield, which is consistent with the mid-parent heterosis value in F1. Accordingly, in cotton breeding, bolls/plant can be considered first and other yield components measured as a whole to implement variety enhancement and hybrid selection of cotton.

Study on Component Synthesis Active Vibration Suppression Method Using Zero-placement Technique

The component synthesis active vibration suppression method （CSVS） can be applied to suppress the vibration of flexible systems. By this method, several same or similar time-varying components are arranged according to certain rules along the time axis. The synthesized command can suppress the arbitrary unwanted vibration harmonic while achieving the desired rigid body motion. The number of the components increases rapidly when the number of harmonic vibration is growing. In this article, the CSVS based on zero-placement technique is used to construct the synthesized command to suppress the multi-harmonics simultaneously in the discrete domain. The nature of zero-placement method is to put enough zeros to cancel system poles at necessary points. The designed synthesized command has equal time intervals between each component and which is much easier to be implemented. Using this method, the number of components increases linearly with the increasing of the number of being suppressed harmonics. For the spacecraft with flexible appendages, CSVS based on zero-placement is used to design the time optimal large angle maneuver control strategy. Simulations have verified the validity and superiority of the proposed approach.

Construction of Anti-breaking Models of the Main Veins of Flue-cured Tobacco Leaves and Principal Component Analysis

[Objective] This study aimed to explore the related mechanisms of the breaking of flue-cured tobacco leaves. [Method] Anti-breaking models of the main veins of flue-cured tobacco leaves were constructed for principal component analysis on the anti-breaking index, leaf traits and cellulose contents. [Result] The results showed that the growth traits had certain relevance with the cellulose contents while the leaf weight assumed a significant negative correlation with the anti-breaking index, indicating that the heavier the leaf weight was, the weaker the anti-breaking capacity of flue-cured tobacco would be; the cross-sectional area of main veins and the cellulose contents had shown a positive correlation with the anti-breaking index, indicating that the thicker the main vein of flue-cured tobacco was, the higher the cellulose contents would be, and the stronger the anti-breaking capacity of flue-cured tobacco leaves would be. [Conclusion] This study provided theoretical basis and reference to improve tobacco production and enhance the quality of flue-cured tobacco.

Analysis of the major components of root exudates released from several economic forest tree using GC-MS

In 2000 and 2001, 1-year-old seedlings of 7 economic tree species including chestnut, apricot, persimmon, peach, walnut, pear and apple were cultured in garden pots that had a diameter of 40 cm and were filled with clean sand. The major components of exudates released from their roots were isolated and analysed by GC-MS. Totally 200 kinds of organic chemicals were isolated, of which 3 kinds i.e. naphthalene, dimethylbenzene and dibutyl phthalate were principally controlled pollutants according to 'Blacklist of Principal Environment Pollutants in China' and the standard of U.S. Environmental Protection Agency (EPA). The research result provided theoretical evidence for selecting low-pollution economic forest crops in the water source protection area in Miyun Reservoir.

Design Mode for Component-based Virtual Plant Software

According to the morphological structure characteristics of plants, the de- velopment mode for component-based virtual plants software was put forward, and the internal structure of plant organs component under this mode were analyzed, thereby, the overall design mode for virtual plants software was given out, and its characteristics were estimated. Compared with traditional development modes of virtual plants software, component-based virtual plants software had significant advantages in code reusing, development efficiency and expansion of software functions.