The soaring demand for smart portable electronics and electric vehicles is propelling the advancements in high-energy–density lithium-ion batteries.Lithium manganese iron phosphate(LiMn_(x)Fe_(1-x)PO_(4))has garnered...The soaring demand for smart portable electronics and electric vehicles is propelling the advancements in high-energy–density lithium-ion batteries.Lithium manganese iron phosphate(LiMn_(x)Fe_(1-x)PO_(4))has garnered significant attention as a promising positive electrode material for lithium-ion batteries due to its advantages of low cost,high safety,long cycle life,high voltage,good high-temperature performance,and high energy density.Although LiMn_(x)Fe_(1-x)PO_(4)has made significant breakthroughs in the past few decades,there are still facing great challenges in poor electronic conductivity and Li-ion diffusion,manganese dissolution affecting battery cycling performance,as well as low tap density.This review systematically summarizes the reaction mechanisms,various synthesis methods,and electrochemical properties of LiMn_(x)Fe_(1-x)PO_(4)to analyze reaction processes accurately and guide material preparation.Later,the main challenges currently faced are concluded,and the corresponding various modification strategies are discussed to enhance the reaction kinetics and electrochemical performance of LiMn_(x)Fe_(1-x)PO_(4),including multi-scale particle regulation,heteroatom doping,surface coating,as well as microscopic morphology design.Finally,in view of the current research challenges faced by intrinsic reaction processes,kinetics,and energy storage applications,the promising research directions are anticipated.More importantly,it is expected to provide key insights into the development of high-performance and stable LiMn_(x)Fe_(1-x)PO_(4)materials,to achieve practical energy storage requirements.展开更多
Aircraft disturbs the adjacent atmospheric environment in flight,forming spatial distribution features of atmospheric density that differ from the natural background,which may potentially be utilized as tracer charact...Aircraft disturbs the adjacent atmospheric environment in flight,forming spatial distribution features of atmospheric density that differ from the natural background,which may potentially be utilized as tracer characteristics to introduce new technologies for indirectly sensing the presence of aircraft.In this paper,the concept of a long-range aircraft detection based on the atmospheric disturbance density field is proposed,and the detection mode of tomographic imaging of the scattering light of an atmospheric disturbance flow field is designed.By modeling the spatial distribution of the disturbance density field,the scattered echo signal images of active light towards the disturbance field at long distance are simulated.On this basis,the characteristics of the disturbance optical signal at the optimal detection resolution are analyzed.The results show that the atmospheric disturbance flow field of the supersonic aircraft presents circular in the light-scattering echo images.The disturbance signal can be further highlighted by differential processing of the adjacent scattering images.As the distance behind the aircraft increases,the diffusion range of the disturbance signal increases,and the signal intensity and contrast with the background decrease.Under the ground-based observation conditions of the aircraft at a height of 10000 m,a Mach number of1.6,and a detection distance of 100 km,the contrast between the disturbance signal and the back-ground was 30 d B at a distance of one time from the rear of the fuselage,and the diffusion diameter of the disturbance signal was 50 m.At a distance eight times the length of the aircraft,the contrast decreased to 10 dB,and the diameter increased to 290 m.The contrast was reduced to 3 dB at a distance nine times the length of the aircraft,and the diameter was diffused to 310 m.These results indicate the possibility of long-range aircraft detection based on the characteristics of the atmospheric density field.展开更多
Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planti...Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.展开更多
BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free r...BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free rates.AIM To assess the role of VCSD in determining success of SWL in urinary calculi.METHODS Charts review was utilized for collection of data variables.The patients were subjected to SWL,using an electromagnetic lithotripter.Mean stone density(MSD),stone heterogeneity index(SHI),and VCSD were calculated by generating regions of interest on computed tomography(CT)images.Role of these factors were determined by applying the relevant statistical tests for continuous and categorical variables and a P value of<0.05 was gauged to be statistically significant.RESULTS There were a total of 407 patients included in the analysis.The mean age of the subjects in this study was 38.89±14.61 years.In total,165 out of the 407 patients could not achieve stone free status.The successful group had a significantly lower stone volume as compared to the unsuccessful group(P<0.0001).Skin to stone distance was not dissimilar among the two groups(P=0.47).MSD was significantly lower in the successful group(P<0.0001).SHI and VCSD were both significantly higher in the successful group(P<0.0001).CONCLUSION VCSD,a useful CT based parameter,can be utilized to gauge stone fragility and hence the prediction of SWL outcomes.展开更多
The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to ...The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.展开更多
ZGH401 alloy was prepared under varying laser power levels and scanning speeds by the orthogonal test method using selective laser melting(SLM).The effect of different energy densities on microstructure and mechanical...ZGH401 alloy was prepared under varying laser power levels and scanning speeds by the orthogonal test method using selective laser melting(SLM).The effect of different energy densities on microstructure and mechanical properties of the formed alloy was investigated.The microstructure of ZGH401 was analyzed by scanning electron microscope,electron back-scattered diffraction,and electron probe microanalysis.The results show that the defects of the as-built ZGH401 are gradually reduced,the relative density is correspondingly enhanced with increasing the energy density,and the ultimate density can reach 99.6%.An increase in laser power leads to a corresponding rise in hardness of ZGH401,while a faster scanning speed reduces the residual stress in asbuilt ZGH401 samples.In addition,better tensile properties are achieved at room temperature due to more grain boundaries perpendicular to the build direction than parallel to the build direction.The precipitated phases are identified as carbides and Laves phases via chemical composition analysis,with fewer carbides observed at the molten pool boundaries than within the molten pools.展开更多
High-density germanate glasses doped with Tb^(3+)ions were synthesized via the melt-quenching meth-od.The physical and luminescent properties of these glasses were characterized through various techniques,in-cluding d...High-density germanate glasses doped with Tb^(3+)ions were synthesized via the melt-quenching meth-od.The physical and luminescent properties of these glasses were characterized through various techniques,in-cluding density measurement,differential scanning calorimetry(DSC),photoluminescence(PL)spectroscopy,X-ray excited luminescence(XEL)spectroscopy,and fluorescence decay analysis.The densities of the germanate glasses were greater than 6.1 g/cm^(3).Upon excitations of ultraviolet(UV)light and X-rays,the glasses emitted in-tense green emissions.The fluorescence lifetime of the strongest emission peak at 544 nm,measured under 377 nm excitation,ranged from 1.52 ms to 1.32 ms.In the glass specimens,the maximum XEL integral intensity reached roughly 26%of that of the commercially available Bi_(4)Ge_(3)O_(12)(BGO)crystal.These results indicate that Tb^(3+)-doped high-density germanate scintillating glasses hold potential as scintillation materials for X-ray imaging applications.展开更多
We have examined the theoretical implications of combining two main and three auxiliary ligands to form several Ir(Ⅲ)complexes featuring a transition metal as their core atom to identify some appropriate organic ligh...We have examined the theoretical implications of combining two main and three auxiliary ligands to form several Ir(Ⅲ)complexes featuring a transition metal as their core atom to identify some appropriate organic lightemitting diode(OLED)materials.By utilizing electronic structure,frontier molecular orbitals,minimum single-line absorption,triplet excited states,and emission spectral data derived from the density functional theory,the usefulness of these Ir(Ⅲ)complexes,including(piq)_(2)Ir(acac),(piq)_(2)Ir(tmd),(piq)_(2)Ir(tpip),(fpiq)_(2)Ir(acac),(fpiq)_(2)Ir(tmd),and(fpiq)_(2)Ir(tpip),in OLEDs was examined,where piq=1-phenylisoquinoline,fpiq=1-(4-fluorophenyl)isoquinoline,acac=(3Z)-4-hydroxypent-3-en-2-one,tmd=(4Z)-5-hydroxy-2,2,6,6-tetramethylhept-4-en-3-one,and tpip=tetraphenylimido-diphosphonate.These complexes all have low-efficiency roll-off properties,especially(fpiq)_(2)Ir(tpip).Some researchers have successfully synthesized complexes extremely similar to(piq)_(2)Ir(acac)through the Suzuki-Miyaura coupling reaction.展开更多
The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma sheath.Due to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the ...The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma sheath.Due to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the plasma sheath can be challenging.Obtaining the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of vehicles.In this work,the relationship between electromagnetic wave attenuation and electron density is deduced theoretically.The attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron density.This result is used to predict the electron density profile.Furthermore,the average electron density is obtained using a back-propagation neural network algorithm.Finally,the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation depth.Compared to traditional probe measurement methods,the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.展开更多
Extracorporeal shock wave lithotripsy(ESWL)is recognised as the ideal noninvasive procedure for urolithiasis.However,the suitability of ESWL varies depending on the composition of the stone.The chemical structure of t...Extracorporeal shock wave lithotripsy(ESWL)is recognised as the ideal noninvasive procedure for urolithiasis.However,the suitability of ESWL varies depending on the composition of the stone.The chemical structure of the stone may not be uniform throughout the stone and this heterogeneity provides the clue in the form of variation coefficient of stone density.To be aware of the success of the stone breakage by ESWL is an advantage upfront,so that it is possible to apply the technology to the most appropriate patient.This is an important aspect in the successful management of urolithiasis.展开更多
The advancement of planar micro-supercapacitors(PMSCs)for micro-electromechanical systems(MEMS)has been significantly hindered by the challenge of achieving high energy and power densities.This study addresses this is...The advancement of planar micro-supercapacitors(PMSCs)for micro-electromechanical systems(MEMS)has been significantly hindered by the challenge of achieving high energy and power densities.This study addresses this issue by leveraging screen-printing technology to fabricate high-performance PMSCs using innovative composite ink.The ink,a synergistic blend of few-layer graphene(Gt),carbon black(CB),and NiCo_(2)O_(4),was meticulously mixed to form a conductive and robust coating that enhanced the capacitive performance of the PMSCs.The optimized ink formulation and printing process result in a micro-supercapacitor with an exceptional areal capacitance of 18.95 mF/cm^(2)and an areal energy density of 2.63μW·h/cm^(2)at a current density of 0.05 mA/cm^(2),along with an areal power density of 0.025 mW/cm^(2).The devices demonstrated impressive durability with a capacitance retention rate of 94.7%after a stringent 20000-cycle test,demonstrating their potential for long-term applications.Moreover,the PMSCs displayed excellent mechanical flexibility,with a capacitance decrease of only 3.43%after 5000 bending cycles,highlighting their suitability for flexible electronic devices.The ease of integrating these PMSCs into series and parallel configurations for customized power further underscores their practicality for integrated power supply solutions in various technologies.展开更多
Machine learning(ML)has demon-strated significant potential in en-hancing the predictive capabilities of density functional theory methods.In this study,we develop an ML model for correcting B3LYP-D,a density function...Machine learning(ML)has demon-strated significant potential in en-hancing the predictive capabilities of density functional theory methods.In this study,we develop an ML model for correcting B3LYP-D,a density functional approximation that incorporates dispersion correc-tions for non-covalent interactions.This model utilizes semilocal elec-tron density descriptors,and is trained with accurate reference data for both relative and ab-solute energies.Extensive benchmark tests reveal that the ML correction substantially en-hances the generalization ability of the B3LYP-D functional,improving the predictions of at-omization and dissociation energies for complex molecular systems.It retains the accuracy of B3LYP-D in predicting reaction barrier heights and non-covalent interactions while enabling efficient,fully self-consistent field calculations.This work signifies a promising advancement in the development of ML-corrected functionals that surpass the performance of traditional B3LYP-D.展开更多
In this study,a framework for predicting the gas-sensitive properties of gas-sensitive materials by combining machine learning and density functional theory(DFT)has been proposed.The framework rapidly predicts the gas...In this study,a framework for predicting the gas-sensitive properties of gas-sensitive materials by combining machine learning and density functional theory(DFT)has been proposed.The framework rapidly predicts the gas response of materials by establishing relationships between multisource physical parameters and gas-sensitive properties.In order to prove its effectiveness,the perovskite Cs_(3)Cu_(2)I_(5) has been selected as the representative material.The physical parameters before and after the adsorption of various gases have been calculated using DFT,and then a machine learning model has been trained based on these parameters.Previous studies have shown that a single physical parameter alone is not enough to accurately predict the gas sensitivity of materials.Therefore,a variety of physical parameters have been selected for machine learning,and the final machine learning model achieved 92%accuracy in predicting gas sensitivity.It is important to note that although there have been no previous reports on the response of Cs_(3)Cu_(2)I_(5) to hydrogen sulfide,the resulting model predicts the gas response of H2S;it is subsequently confirmed experimentally.This method not only enhances the understanding of the gas sensing mechanism,but also has a universal nature,making it suitable for the development of various new gas-sensitive materials.展开更多
Planting density is a major limiting factor for maize yield,and breeding for density tolerance has become an urgent issue.The leaf structure of the maize ear leaf is the main factor that restricts planting density and...Planting density is a major limiting factor for maize yield,and breeding for density tolerance has become an urgent issue.The leaf structure of the maize ear leaf is the main factor that restricts planting density and yield components.In this study,a natural population of 201 maize inbred lines was used for genome-wide association analysis,which identified nine SNPs on chromosomes 2,5,8,9,and 10 that were significantly associated with ear leaf type structure.Further verification through qRT-PCR confirmed the association of five candidate genes with these SNPs,with the Zm00001d008651 gene showing significant differential expression in the compact and flat maize inbred lines.Enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)databasessuggested that this gene is involved in the glycolysis process.An analysis of the basic properties of this gene revealed that it encodes a stable,basic protein consisting of 593 amino acids with some hydrophobic properties.The promoter region contains stress and hormone(abscisic acid(ABA))related elements.The mutant of this gene increased the first ear leaf angle(eLA)and leaf angle of the first leaf below the first ear(bLA)by 4.96 and 0.97°,respectively,compared with normal inbred lines.Overall,this research sheds light on the regulatory mechanism of ear and leaf structures that influence density tolerance and provides solid foundational work for the development of new varieties.展开更多
Magnesium(Mg)alloys face a critical challenge in balancing performance optimization and unintended density increases caused by high-density secondary phases.To address this,machine learning was employed to predict the...Magnesium(Mg)alloys face a critical challenge in balancing performance optimization and unintended density increases caused by high-density secondary phases.To address this,machine learning was employed to predict the density and volume of Mg-containing binary phases,aiming to guide lightweight alloy design.Using 211 experimentally observed data points,five machine learning(ML)algorithms—Random Forest(RF),Support Vector Machine(SVM),Artificial Neural Network(ANN),K-Nearest Neighbors(KNN),and Bayesian Ridge(Bayes)—were trained and tested.Quantitative results showed that RF achieved exceptional performance in volume prediction,with a testing coefficient of determination(R2)exceeding 0.96 and a mean absolute error(MAE)of 41.0Å^(3),while SVM outperformed others in density prediction with a testing R2 of 0.885 and MAE of 0.421 g/cm^(3).Feature importance analysis revealed that atomic count is the primary determinant of phase volume,whereas density prediction depends on the synergistic interaction of relative atomic mass and stoichiometric ratio,as further validated by SHapley Additive exPlanations(SHAP)analysis.This work establishes a physics-informed predictive model that accelerates the development of lightweight Mg alloys by mitigating high-density secondary phases,and can be extended to other alloy systems.展开更多
The complex symmetry breaking states in AV3Sb5 family have attracted extreme research attention,but controversy still exists,especially in the question of time reversal symmetry breaking of the charge density wave(CDW...The complex symmetry breaking states in AV3Sb5 family have attracted extreme research attention,but controversy still exists,especially in the question of time reversal symmetry breaking of the charge density wave(CDW).Most recently,a chiral CDW has been suggested in kagome magnet FeGe,but the related study is very rare.Here,we use a scanning tunneling microscope to study the symmetry breaking behavior of both the short-and long-range CDWs in FeGe.Different from previous studies,our study reveals an isotropic long-range CDW without obvious symmetry breaking,while local rotational symmetry breaking appears in the short-range CDW,which may be related to the existence of strong structural disorders.Moreover,the charge distribution of the short-range CDW is inert to the applied external magnetic fields and the detailed spin arrangements of FeGe,inconsistent with the expectation of a chiral CDW associated with chiral flux.Our results rule out the existence of spontaneous chiral and rotational symmetry breaking in the CDW state of FeGe,putting strong constraints on the further understanding of CDW mechanism.展开更多
Bioprinting of cell-laden hydrogels is a rapidly growing field in tissue engineering.The advent of digital light processing(DLP)three-dimensional(3D)bioprinting technique has revolutionized the fabrication of complex ...Bioprinting of cell-laden hydrogels is a rapidly growing field in tissue engineering.The advent of digital light processing(DLP)three-dimensional(3D)bioprinting technique has revolutionized the fabrication of complex 3D structures.By adjusting light exposure,it becomes possible to control the mechanical properties of the structure,a critical factor in modulating cell activities.To better mimic cell densities in real tissues,recent progress has been made in achieving high-cell-density(HCD)printing with high resolution.However,regulating the stiffness in HCD constructs remains challenging.The large volume of cells greatly affects the light-based DLP bioprinting by causing light absorption,reflection,and scattering.Here,we introduce a neural network-based machine learning technique to predict the stiffness of cell-laden hydrogel scaffolds.Using comprehensive mechanical testing data from 3D bioprinted samples,the model was trained to deliver accurate predictions.To address the demand of working with precious and costly cell types,we employed various methods to ensure the generalizability of the model,even with limited datasets.We demonstrated a transfer learning method to achieve good performance for a precious cell type with a reduced amount of data.The chosen method outperformed many other machine learning techniques,offering a reliable and efficient solution for stiffness prediction in cell-laden scaffolds.This breakthrough paves the way for the next generation of precision bioprinting and more customized tissue engineering.展开更多
Cluster-basedmodels have numerous application scenarios in vehicular ad-hoc networks(VANETs)and can greatly help improve the communication performance of VANETs.However,the frequent movement of vehicles can often lead...Cluster-basedmodels have numerous application scenarios in vehicular ad-hoc networks(VANETs)and can greatly help improve the communication performance of VANETs.However,the frequent movement of vehicles can often lead to changes in the network topology,thereby reducing cluster stability in urban scenarios.To address this issue,we propose a clustering model based on the density peak clustering(DPC)method and sparrow search algorithm(SSA),named SDPC.First,the model constructs a fitness function based on the parameters obtained from the DPC method and deploys the SSA for iterative optimization to select cluster heads(CHs).Then,the vehicles that have not been selected as CHs are assigned to appropriate clusters by comprehensively considering the distance parameter and link-reliability parameter.Finally,cluster maintenance strategies are considered to tackle the changes in the clusters’organizational structure.To verify the performance of the model,we conducted a simulation on a real-world scenario for multiple metrics related to clusters’stability.The results show that compared with the APROVE and the GAPC,SDPC showed clear performance advantages,indicating that SDPC can effectively ensure VANETs’cluster stability in urban scenarios.展开更多
Recently,it has been observed that during the operation of an inductively coupled plasma(ICP),a luminescent target(BAM,BaMgAl10O17:Eu)can interact with the plasma beam and emit blue light.After excluding the influence...Recently,it has been observed that during the operation of an inductively coupled plasma(ICP),a luminescent target(BAM,BaMgAl10O17:Eu)can interact with the plasma beam and emit blue light.After excluding the influence of ultraviolet(UV)and electromagnetic wave radiation,the results indicate that the BAM target may undergo luminescent excitation due to collisions with electrons and ions.This led us to investigate the physical mechanism behind this plasma luminescence excitation phenomenon.A spectrometer was used to record the luminescent spectroscopy and peak light intensity.Under excitation by argon plasma,the BAM material emits a continuum spectrum from 400 nm to 550 nm,with the peak light intensity located at 462.58 nm,which is the same as the spectrum excited by UV torchlight.To identify the relationship between the plasma parameters and the luminescent intensity,Langmuir and Faraday probes were employed to determine the local plasma parameters such as electron density,electron temperature,and current density.After normalizing the peak light intensity to the plasma parameters,the most interesting point is that the current density is linearly correlated with the luminescent light intensity.To verify the repeatability and lifetime of the plasma-luminescence interaction,a 600 s lifetime test was conducted in a 200 W ICP discharge environment.The maximum difference for the peak light strength of the luminescent spectrum is 6.5%.From a voltage bias experiment and a theoretical derivation,we initially identified that bombardment by ions plays the dominant role in the luminescence excitation process,which also explains the mechanism by which the current density is proportional to the luminescence intensity.This new finding leads us to reconsider the possibility of applying this plasma luminescence phenomenon to optical plasma diagnostics.The BAM light intensity can potentially be used to predict the current density of a plasma beam for large-area two-dimensional(2D)measurements and can capture high spatial resolution in a single test.We believe that this method may lead to high-efficiency,spatially resolved plasma current density measurement.展开更多
The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Usi...The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Using high-resolution micro-camera imaging,this study analyzed 905 skin images,33 skin transcriptomes,272 whole-genome sequences,and 182 downloaded transcriptomes.Morphological assessment from juvenile to adult stages revealed the thickening of hair shafts accompanied by a progressive decline in density,largely attributable to rapid surface expansion of the trunk skin.Transcriptomic comparison between high-and low-CHD individuals identified 572 differentially expressed genes(DEGs).A genome-wide association study detected 25 significant single nucleotide polymorphisms(P<9.07e-8)and mapped 48 annotated genes,with the most prominent association signal located near GJA1 on chr9.15931585-18621011.Literature review and Venn analysis highlighted six genes(GJA1,GPRC5D,CD1D,CD207,TFAM,and CXCL12)with documented roles in skin and hair biology,and three genes(GJA1,GPRC5D,and ATP6V1B1)overlapped with DEGs.Multiple-tissue transcriptomic profiling,western blotting,immunohistochemical staining,and skin single-cell RNA sequencing confirmed that GJA1 and GPRC5D were highly and specifically expressed in skin,particularly within hair follicles.Expression was localized predominantly to follicular stem cells and dermal papilla cells,suggesting a significant role in folliculogenesis and structural maintenance.Cross-validation using four public datasets further demonstrated positive correlations between GJA1 and GPRC5D expression and hair follicle density.The innovative micro-camera application allowed the elucidation of spatiotemporal patterns and genes associated with CHD,thereby addressing a significant knowledge gap in animal hair density.展开更多
基金National Natural Science Foundation of China(52104294)Fundamental Research Funds for the Central Universities(FRF-TP-19-079A1)。
文摘The soaring demand for smart portable electronics and electric vehicles is propelling the advancements in high-energy–density lithium-ion batteries.Lithium manganese iron phosphate(LiMn_(x)Fe_(1-x)PO_(4))has garnered significant attention as a promising positive electrode material for lithium-ion batteries due to its advantages of low cost,high safety,long cycle life,high voltage,good high-temperature performance,and high energy density.Although LiMn_(x)Fe_(1-x)PO_(4)has made significant breakthroughs in the past few decades,there are still facing great challenges in poor electronic conductivity and Li-ion diffusion,manganese dissolution affecting battery cycling performance,as well as low tap density.This review systematically summarizes the reaction mechanisms,various synthesis methods,and electrochemical properties of LiMn_(x)Fe_(1-x)PO_(4)to analyze reaction processes accurately and guide material preparation.Later,the main challenges currently faced are concluded,and the corresponding various modification strategies are discussed to enhance the reaction kinetics and electrochemical performance of LiMn_(x)Fe_(1-x)PO_(4),including multi-scale particle regulation,heteroatom doping,surface coating,as well as microscopic morphology design.Finally,in view of the current research challenges faced by intrinsic reaction processes,kinetics,and energy storage applications,the promising research directions are anticipated.More importantly,it is expected to provide key insights into the development of high-performance and stable LiMn_(x)Fe_(1-x)PO_(4)materials,to achieve practical energy storage requirements.
文摘Aircraft disturbs the adjacent atmospheric environment in flight,forming spatial distribution features of atmospheric density that differ from the natural background,which may potentially be utilized as tracer characteristics to introduce new technologies for indirectly sensing the presence of aircraft.In this paper,the concept of a long-range aircraft detection based on the atmospheric disturbance density field is proposed,and the detection mode of tomographic imaging of the scattering light of an atmospheric disturbance flow field is designed.By modeling the spatial distribution of the disturbance density field,the scattered echo signal images of active light towards the disturbance field at long distance are simulated.On this basis,the characteristics of the disturbance optical signal at the optimal detection resolution are analyzed.The results show that the atmospheric disturbance flow field of the supersonic aircraft presents circular in the light-scattering echo images.The disturbance signal can be further highlighted by differential processing of the adjacent scattering images.As the distance behind the aircraft increases,the diffusion range of the disturbance signal increases,and the signal intensity and contrast with the background decrease.Under the ground-based observation conditions of the aircraft at a height of 10000 m,a Mach number of1.6,and a detection distance of 100 km,the contrast between the disturbance signal and the back-ground was 30 d B at a distance of one time from the rear of the fuselage,and the diffusion diameter of the disturbance signal was 50 m.At a distance eight times the length of the aircraft,the contrast decreased to 10 dB,and the diameter increased to 290 m.The contrast was reduced to 3 dB at a distance nine times the length of the aircraft,and the diameter was diffused to 310 m.These results indicate the possibility of long-range aircraft detection based on the characteristics of the atmospheric density field.
文摘Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.
文摘BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free rates.AIM To assess the role of VCSD in determining success of SWL in urinary calculi.METHODS Charts review was utilized for collection of data variables.The patients were subjected to SWL,using an electromagnetic lithotripter.Mean stone density(MSD),stone heterogeneity index(SHI),and VCSD were calculated by generating regions of interest on computed tomography(CT)images.Role of these factors were determined by applying the relevant statistical tests for continuous and categorical variables and a P value of<0.05 was gauged to be statistically significant.RESULTS There were a total of 407 patients included in the analysis.The mean age of the subjects in this study was 38.89±14.61 years.In total,165 out of the 407 patients could not achieve stone free status.The successful group had a significantly lower stone volume as compared to the unsuccessful group(P<0.0001).Skin to stone distance was not dissimilar among the two groups(P=0.47).MSD was significantly lower in the successful group(P<0.0001).SHI and VCSD were both significantly higher in the successful group(P<0.0001).CONCLUSION VCSD,a useful CT based parameter,can be utilized to gauge stone fragility and hence the prediction of SWL outcomes.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030001)the National Key Research and Development Program of China(Grant No.2021YFB3802300)the Foundation of National Key Laboratory of Shock Wave and Detonation Physics(Grant No.JCKYS2022212004)。
文摘The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.
基金National Defense Science and Technology Project Management Center(2021-JCJQ-JJ-0092)。
文摘ZGH401 alloy was prepared under varying laser power levels and scanning speeds by the orthogonal test method using selective laser melting(SLM).The effect of different energy densities on microstructure and mechanical properties of the formed alloy was investigated.The microstructure of ZGH401 was analyzed by scanning electron microscope,electron back-scattered diffraction,and electron probe microanalysis.The results show that the defects of the as-built ZGH401 are gradually reduced,the relative density is correspondingly enhanced with increasing the energy density,and the ultimate density can reach 99.6%.An increase in laser power leads to a corresponding rise in hardness of ZGH401,while a faster scanning speed reduces the residual stress in asbuilt ZGH401 samples.In addition,better tensile properties are achieved at room temperature due to more grain boundaries perpendicular to the build direction than parallel to the build direction.The precipitated phases are identified as carbides and Laves phases via chemical composition analysis,with fewer carbides observed at the molten pool boundaries than within the molten pools.
文摘High-density germanate glasses doped with Tb^(3+)ions were synthesized via the melt-quenching meth-od.The physical and luminescent properties of these glasses were characterized through various techniques,in-cluding density measurement,differential scanning calorimetry(DSC),photoluminescence(PL)spectroscopy,X-ray excited luminescence(XEL)spectroscopy,and fluorescence decay analysis.The densities of the germanate glasses were greater than 6.1 g/cm^(3).Upon excitations of ultraviolet(UV)light and X-rays,the glasses emitted in-tense green emissions.The fluorescence lifetime of the strongest emission peak at 544 nm,measured under 377 nm excitation,ranged from 1.52 ms to 1.32 ms.In the glass specimens,the maximum XEL integral intensity reached roughly 26%of that of the commercially available Bi_(4)Ge_(3)O_(12)(BGO)crystal.These results indicate that Tb^(3+)-doped high-density germanate scintillating glasses hold potential as scintillation materials for X-ray imaging applications.
文摘We have examined the theoretical implications of combining two main and three auxiliary ligands to form several Ir(Ⅲ)complexes featuring a transition metal as their core atom to identify some appropriate organic lightemitting diode(OLED)materials.By utilizing electronic structure,frontier molecular orbitals,minimum single-line absorption,triplet excited states,and emission spectral data derived from the density functional theory,the usefulness of these Ir(Ⅲ)complexes,including(piq)_(2)Ir(acac),(piq)_(2)Ir(tmd),(piq)_(2)Ir(tpip),(fpiq)_(2)Ir(acac),(fpiq)_(2)Ir(tmd),and(fpiq)_(2)Ir(tpip),in OLEDs was examined,where piq=1-phenylisoquinoline,fpiq=1-(4-fluorophenyl)isoquinoline,acac=(3Z)-4-hydroxypent-3-en-2-one,tmd=(4Z)-5-hydroxy-2,2,6,6-tetramethylhept-4-en-3-one,and tpip=tetraphenylimido-diphosphonate.These complexes all have low-efficiency roll-off properties,especially(fpiq)_(2)Ir(tpip).Some researchers have successfully synthesized complexes extremely similar to(piq)_(2)Ir(acac)through the Suzuki-Miyaura coupling reaction.
基金Project supported by the Natural Science Foundation of Henan Province,China(Grant No.242300420634)the Cultivative Plan of Henan University of Technology(Grant No.2024PYJH035)+3 种基金the Research Foundation for Advanced Talents of Henan University of Technology(Grant Nos.2022BS067 and 2022BS068)the National Natural Science Foundation of China(Grant No.62301211)the Key Research and Development and Promotion Special Project(Science and Technology Research)in Henan Province,China(Grant No.232102211068)the Innovative Funds Plan of Henan University of Technology(Grant No.2022ZKCJ15)。
文摘The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma sheath.Due to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the plasma sheath can be challenging.Obtaining the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of vehicles.In this work,the relationship between electromagnetic wave attenuation and electron density is deduced theoretically.The attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron density.This result is used to predict the electron density profile.Furthermore,the average electron density is obtained using a back-propagation neural network algorithm.Finally,the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation depth.Compared to traditional probe measurement methods,the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.
文摘Extracorporeal shock wave lithotripsy(ESWL)is recognised as the ideal noninvasive procedure for urolithiasis.However,the suitability of ESWL varies depending on the composition of the stone.The chemical structure of the stone may not be uniform throughout the stone and this heterogeneity provides the clue in the form of variation coefficient of stone density.To be aware of the success of the stone breakage by ESWL is an advantage upfront,so that it is possible to apply the technology to the most appropriate patient.This is an important aspect in the successful management of urolithiasis.
基金supported by the Shanxi Province Central Guidance Fund for Local Science and Technology Development Project(YDZJSX2024D030)the National Natural Science Foundation of China(22075197,22278290)+2 种基金the Shanxi Province Key Research and Development Program Project(2021020660301013)the Shanxi Provincial Natural Science Foundation of China(202103021224079)the Research and Development Project of Key Core and Common Technology of Shanxi Province(20201102018).
文摘The advancement of planar micro-supercapacitors(PMSCs)for micro-electromechanical systems(MEMS)has been significantly hindered by the challenge of achieving high energy and power densities.This study addresses this issue by leveraging screen-printing technology to fabricate high-performance PMSCs using innovative composite ink.The ink,a synergistic blend of few-layer graphene(Gt),carbon black(CB),and NiCo_(2)O_(4),was meticulously mixed to form a conductive and robust coating that enhanced the capacitive performance of the PMSCs.The optimized ink formulation and printing process result in a micro-supercapacitor with an exceptional areal capacitance of 18.95 mF/cm^(2)and an areal energy density of 2.63μW·h/cm^(2)at a current density of 0.05 mA/cm^(2),along with an areal power density of 0.025 mW/cm^(2).The devices demonstrated impressive durability with a capacitance retention rate of 94.7%after a stringent 20000-cycle test,demonstrating their potential for long-term applications.Moreover,the PMSCs displayed excellent mechanical flexibility,with a capacitance decrease of only 3.43%after 5000 bending cycles,highlighting their suitability for flexible electronic devices.The ease of integrating these PMSCs into series and parallel configurations for customized power further underscores their practicality for integrated power supply solutions in various technologies.
基金supported by the National Natural Science Foundation of China(Nos.22393912,22425301,22373091,22173088)the AI for Science Foundation of Fudan University(No.Fudan X24AI023)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0450101).
文摘Machine learning(ML)has demon-strated significant potential in en-hancing the predictive capabilities of density functional theory methods.In this study,we develop an ML model for correcting B3LYP-D,a density functional approximation that incorporates dispersion correc-tions for non-covalent interactions.This model utilizes semilocal elec-tron density descriptors,and is trained with accurate reference data for both relative and ab-solute energies.Extensive benchmark tests reveal that the ML correction substantially en-hances the generalization ability of the B3LYP-D functional,improving the predictions of at-omization and dissociation energies for complex molecular systems.It retains the accuracy of B3LYP-D in predicting reaction barrier heights and non-covalent interactions while enabling efficient,fully self-consistent field calculations.This work signifies a promising advancement in the development of ML-corrected functionals that surpass the performance of traditional B3LYP-D.
基金supported by Natural Science Foundation of Jiangsu Province(No.BK20210494)National Natural Science Foundation of China(No.52303356).
文摘In this study,a framework for predicting the gas-sensitive properties of gas-sensitive materials by combining machine learning and density functional theory(DFT)has been proposed.The framework rapidly predicts the gas response of materials by establishing relationships between multisource physical parameters and gas-sensitive properties.In order to prove its effectiveness,the perovskite Cs_(3)Cu_(2)I_(5) has been selected as the representative material.The physical parameters before and after the adsorption of various gases have been calculated using DFT,and then a machine learning model has been trained based on these parameters.Previous studies have shown that a single physical parameter alone is not enough to accurately predict the gas sensitivity of materials.Therefore,a variety of physical parameters have been selected for machine learning,and the final machine learning model achieved 92%accuracy in predicting gas sensitivity.It is important to note that although there have been no previous reports on the response of Cs_(3)Cu_(2)I_(5) to hydrogen sulfide,the resulting model predicts the gas response of H2S;it is subsequently confirmed experimentally.This method not only enhances the understanding of the gas sensing mechanism,but also has a universal nature,making it suitable for the development of various new gas-sensitive materials.
基金supported by the Key Research and Development Project of Heilongjiang Province,China(2022ZX02B01)。
文摘Planting density is a major limiting factor for maize yield,and breeding for density tolerance has become an urgent issue.The leaf structure of the maize ear leaf is the main factor that restricts planting density and yield components.In this study,a natural population of 201 maize inbred lines was used for genome-wide association analysis,which identified nine SNPs on chromosomes 2,5,8,9,and 10 that were significantly associated with ear leaf type structure.Further verification through qRT-PCR confirmed the association of five candidate genes with these SNPs,with the Zm00001d008651 gene showing significant differential expression in the compact and flat maize inbred lines.Enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)databasessuggested that this gene is involved in the glycolysis process.An analysis of the basic properties of this gene revealed that it encodes a stable,basic protein consisting of 593 amino acids with some hydrophobic properties.The promoter region contains stress and hormone(abscisic acid(ABA))related elements.The mutant of this gene increased the first ear leaf angle(eLA)and leaf angle of the first leaf below the first ear(bLA)by 4.96 and 0.97°,respectively,compared with normal inbred lines.Overall,this research sheds light on the regulatory mechanism of ear and leaf structures that influence density tolerance and provides solid foundational work for the development of new varieties.
基金supported by Jinhua City Science and Technology Plan Project(2024-1-106)the National Natural Science Foundation of China(U24A2035).
文摘Magnesium(Mg)alloys face a critical challenge in balancing performance optimization and unintended density increases caused by high-density secondary phases.To address this,machine learning was employed to predict the density and volume of Mg-containing binary phases,aiming to guide lightweight alloy design.Using 211 experimentally observed data points,five machine learning(ML)algorithms—Random Forest(RF),Support Vector Machine(SVM),Artificial Neural Network(ANN),K-Nearest Neighbors(KNN),and Bayesian Ridge(Bayes)—were trained and tested.Quantitative results showed that RF achieved exceptional performance in volume prediction,with a testing coefficient of determination(R2)exceeding 0.96 and a mean absolute error(MAE)of 41.0Å^(3),while SVM outperformed others in density prediction with a testing R2 of 0.885 and MAE of 0.421 g/cm^(3).Feature importance analysis revealed that atomic count is the primary determinant of phase volume,whereas density prediction depends on the synergistic interaction of relative atomic mass and stoichiometric ratio,as further validated by SHapley Additive exPlanations(SHAP)analysis.This work establishes a physics-informed predictive model that accelerates the development of lightweight Mg alloys by mitigating high-density secondary phases,and can be extended to other alloy systems.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12374140,12494593,11790312,12004056,11774060,and 92065201)the National Key R&D Program of China(Grant No.2023YFA1406304)+2 种基金the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302803)the Fundamental Research Funds for the Central Universities of China(Grant Nos.2022CDJXY-002 and WK9990000103)the New Cornerstone Science Foundation.
文摘The complex symmetry breaking states in AV3Sb5 family have attracted extreme research attention,but controversy still exists,especially in the question of time reversal symmetry breaking of the charge density wave(CDW).Most recently,a chiral CDW has been suggested in kagome magnet FeGe,but the related study is very rare.Here,we use a scanning tunneling microscope to study the symmetry breaking behavior of both the short-and long-range CDWs in FeGe.Different from previous studies,our study reveals an isotropic long-range CDW without obvious symmetry breaking,while local rotational symmetry breaking appears in the short-range CDW,which may be related to the existence of strong structural disorders.Moreover,the charge distribution of the short-range CDW is inert to the applied external magnetic fields and the detailed spin arrangements of FeGe,inconsistent with the expectation of a chiral CDW associated with chiral flux.Our results rule out the existence of spontaneous chiral and rotational symmetry breaking in the CDW state of FeGe,putting strong constraints on the further understanding of CDW mechanism.
基金supported in part by the National Institutes of Health(Nos.R01HD112026 and R21ES034455)National Science Foundation(NSF,Nos.2135720 and 2223669)performed at San Diego Nanotechnology Infrastructure(SDNI)of UCSD,a member of the National Nanotechnology Coordinated Infrastructure(NNCI),which is supported by NSF(Grant No.ECCS-2025752).
文摘Bioprinting of cell-laden hydrogels is a rapidly growing field in tissue engineering.The advent of digital light processing(DLP)three-dimensional(3D)bioprinting technique has revolutionized the fabrication of complex 3D structures.By adjusting light exposure,it becomes possible to control the mechanical properties of the structure,a critical factor in modulating cell activities.To better mimic cell densities in real tissues,recent progress has been made in achieving high-cell-density(HCD)printing with high resolution.However,regulating the stiffness in HCD constructs remains challenging.The large volume of cells greatly affects the light-based DLP bioprinting by causing light absorption,reflection,and scattering.Here,we introduce a neural network-based machine learning technique to predict the stiffness of cell-laden hydrogel scaffolds.Using comprehensive mechanical testing data from 3D bioprinted samples,the model was trained to deliver accurate predictions.To address the demand of working with precious and costly cell types,we employed various methods to ensure the generalizability of the model,even with limited datasets.We demonstrated a transfer learning method to achieve good performance for a precious cell type with a reduced amount of data.The chosen method outperformed many other machine learning techniques,offering a reliable and efficient solution for stiffness prediction in cell-laden scaffolds.This breakthrough paves the way for the next generation of precision bioprinting and more customized tissue engineering.
文摘Cluster-basedmodels have numerous application scenarios in vehicular ad-hoc networks(VANETs)and can greatly help improve the communication performance of VANETs.However,the frequent movement of vehicles can often lead to changes in the network topology,thereby reducing cluster stability in urban scenarios.To address this issue,we propose a clustering model based on the density peak clustering(DPC)method and sparrow search algorithm(SSA),named SDPC.First,the model constructs a fitness function based on the parameters obtained from the DPC method and deploys the SSA for iterative optimization to select cluster heads(CHs).Then,the vehicles that have not been selected as CHs are assigned to appropriate clusters by comprehensively considering the distance parameter and link-reliability parameter.Finally,cluster maintenance strategies are considered to tackle the changes in the clusters’organizational structure.To verify the performance of the model,we conducted a simulation on a real-world scenario for multiple metrics related to clusters’stability.The results show that compared with the APROVE and the GAPC,SDPC showed clear performance advantages,indicating that SDPC can effectively ensure VANETs’cluster stability in urban scenarios.
基金partly supported by National Natural Science Foundation of China(Nos.52302464 and 52177128)supported by the Key Scientific Research Project for Institutions of Higher Education of Henan Province(No.22B140002).
文摘Recently,it has been observed that during the operation of an inductively coupled plasma(ICP),a luminescent target(BAM,BaMgAl10O17:Eu)can interact with the plasma beam and emit blue light.After excluding the influence of ultraviolet(UV)and electromagnetic wave radiation,the results indicate that the BAM target may undergo luminescent excitation due to collisions with electrons and ions.This led us to investigate the physical mechanism behind this plasma luminescence excitation phenomenon.A spectrometer was used to record the luminescent spectroscopy and peak light intensity.Under excitation by argon plasma,the BAM material emits a continuum spectrum from 400 nm to 550 nm,with the peak light intensity located at 462.58 nm,which is the same as the spectrum excited by UV torchlight.To identify the relationship between the plasma parameters and the luminescent intensity,Langmuir and Faraday probes were employed to determine the local plasma parameters such as electron density,electron temperature,and current density.After normalizing the peak light intensity to the plasma parameters,the most interesting point is that the current density is linearly correlated with the luminescent light intensity.To verify the repeatability and lifetime of the plasma-luminescence interaction,a 600 s lifetime test was conducted in a 200 W ICP discharge environment.The maximum difference for the peak light strength of the luminescent spectrum is 6.5%.From a voltage bias experiment and a theoretical derivation,we initially identified that bombardment by ions plays the dominant role in the luminescence excitation process,which also explains the mechanism by which the current density is proportional to the luminescence intensity.This new finding leads us to reconsider the possibility of applying this plasma luminescence phenomenon to optical plasma diagnostics.The BAM light intensity can potentially be used to predict the current density of a plasma beam for large-area two-dimensional(2D)measurements and can capture high spatial resolution in a single test.We believe that this method may lead to high-efficiency,spatially resolved plasma current density measurement.
基金supported by the National Key Research and Development Program of China(2022YFD1300202)Collection,Utilization,and Innovation of Animal Resources by Research Institutes and Enterprises of Chongqing(Cqnyncw-kqlhtxm),Chongqing Modern Agricultural Industry Technology System(CQMAITS202413)National Training Program of Innovation and Entrepreneurship for Undergraduates(S202310635040)。
文摘The genetic regulation of hair density in animals remains poorly understood.The Dazu black goat,characterized by its black coarse hair and white skin,provides a unique model for dissecting coarse hair density(CHD).Using high-resolution micro-camera imaging,this study analyzed 905 skin images,33 skin transcriptomes,272 whole-genome sequences,and 182 downloaded transcriptomes.Morphological assessment from juvenile to adult stages revealed the thickening of hair shafts accompanied by a progressive decline in density,largely attributable to rapid surface expansion of the trunk skin.Transcriptomic comparison between high-and low-CHD individuals identified 572 differentially expressed genes(DEGs).A genome-wide association study detected 25 significant single nucleotide polymorphisms(P<9.07e-8)and mapped 48 annotated genes,with the most prominent association signal located near GJA1 on chr9.15931585-18621011.Literature review and Venn analysis highlighted six genes(GJA1,GPRC5D,CD1D,CD207,TFAM,and CXCL12)with documented roles in skin and hair biology,and three genes(GJA1,GPRC5D,and ATP6V1B1)overlapped with DEGs.Multiple-tissue transcriptomic profiling,western blotting,immunohistochemical staining,and skin single-cell RNA sequencing confirmed that GJA1 and GPRC5D were highly and specifically expressed in skin,particularly within hair follicles.Expression was localized predominantly to follicular stem cells and dermal papilla cells,suggesting a significant role in folliculogenesis and structural maintenance.Cross-validation using four public datasets further demonstrated positive correlations between GJA1 and GPRC5D expression and hair follicle density.The innovative micro-camera application allowed the elucidation of spatiotemporal patterns and genes associated with CHD,thereby addressing a significant knowledge gap in animal hair density.
