It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in...It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.展开更多
Spinal muscular atrophy(SMA)is a genetic condition that results in selective lower motor neuron loss with concomitant muscle weakness and atrophy.The genetic cause of SMA was understood in 1995 when loss or impairment...Spinal muscular atrophy(SMA)is a genetic condition that results in selective lower motor neuron loss with concomitant muscle weakness and atrophy.The genetic cause of SMA was understood in 1995 when loss or impairment of the survival motor neuron 1(SMN1)gene was identified as the main contributing factor(Lefebvre et al.,1995).This,in combination with the discovery that humans have a“back-up”gene,SMN2,which can produce low levels(approximately 10%)of the full-length functional SMN protein,has led to the generation of SMA-specific gene therapies.SMA was traditionally classified according to age of symptom onset and developmental milestones achieved,with life expectancy and severity varying between individuals.Now,SMN2 copy number is used as a proxy for the prediction of disease severity,with higher SMN2 copy number typically being associated with reduced severity of SMA,although this relationship is not absolute:some individuals with low SMN2 copy number have less severe SMA phenotypes and vice versa.Additionally,the etiology of SMA is further complicated by other factors,such as non-typical nucleotide variants and SMN2-independent modifiers of disease severity.展开更多
The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we pr...The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we prove that a bounded above N-complex X is absolutely clean if and only if X,is an absolutely clean module for each n e Z.We also show that under certain hypotheses,an Ncomplex X is Gorenstein AC-injective if and only if Z;(X)is a Gorenstein AC-injective module for each n e Z and t=1,2,.,N.展开更多
Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a ...Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.展开更多
Quasi-zero stiffness(QZS)isolators have received considerable attention over the past years due to their outstanding vibration isolation performance in low-frequency bands.However,traditional mechanisms for achieving ...Quasi-zero stiffness(QZS)isolators have received considerable attention over the past years due to their outstanding vibration isolation performance in low-frequency bands.However,traditional mechanisms for achieving QZS suffer from low stiffness regions and significant nonlinear restoring forces with hardening characteristics,often struggling to withstand excitations with high amplitude.This paper presents a novel QZS vibration isolator that utilizes a more compact spring-rod mechanism(SRM)to provide primary negative stiffness.The nonlinearity of SRM is adjustable via altering the raceway of its spring-rod end,along with the compensatory force provided by the cam-roller mechanism so as to avoid complex nonlinear behaviors.The absolute zero stiffness can be achieved by a well-designed raceway curve with a concise mathematical expression.The nonlinear stiffness with softening properties can also be achieved by parameter adjustment.The study begins with the forcedisplacement relationship of the integrated mechanism first,followed by the design theory of the cam profile.The dynamic response and absolute displacement transmissibility of the isolation system are obtained based on the harmonic balance method.The experimental results show that the proposed vibration isolator maintains relatively low-dynamic stiffness even under non-ideal conditions,and exhibits enhanced vibration isolation performance compared to the corresponding linear isolator.展开更多
A Bose-Einstein condensate (BEC) is a topic of significant interest within the scientific community. It is well understood that Rb-87 and Yb2Si2O7 have been utilized in experiments to explore this phenomenon. These st...A Bose-Einstein condensate (BEC) is a topic of significant interest within the scientific community. It is well understood that Rb-87 and Yb2Si2O7 have been utilized in experiments to explore this phenomenon. These studies have demonstrated that these materials can achieve the BEC phase, a state that has been experimentally validated. In this paper, we further establish, from the perspective of theoretical physics, that silicon is also capable of exhibiting BEC properties. Our approach differs from prior studies in that it uses innovatively certain boundary conditions. Specifically, we employed Yb-70 as a gamma-ray radiation source and a 1 nm linewidth (as the half-width of a 2 nm line). Additionally, we utilized the concept of half-value thickness from nuclear physics absorption models to optimize the semiconductor process. This method effectively removes ytterbium (Yb) during the process, leaving only silicon, silicon-based materials, or silicon topological superconductors on the wafer. This technical procedure results in the creation of “BEC silicon” at absolute zero temperature (0 K), introducing a novel material for BEC realization.展开更多
Knowing the influence of the size of datasets for regression models can help in improving the accuracy of a solar power forecast and make the most out of renewable energy systems.This research explores the influence o...Knowing the influence of the size of datasets for regression models can help in improving the accuracy of a solar power forecast and make the most out of renewable energy systems.This research explores the influence of dataset size on the accuracy and reliability of regression models for solar power prediction,contributing to better forecasting methods.The study analyzes data from two solar panels,aSiMicro03036 and aSiTandem72-46,over 7,14,17,21,28,and 38 days,with each dataset comprising five independent and one dependent parameter,and split 80–20 for training and testing.Results indicate that Random Forest consistently outperforms other models,achieving the highest correlation coefficient of 0.9822 and the lowest Mean Absolute Error(MAE)of 2.0544 on the aSiTandem72-46 panel with 21 days of data.For the aSiMicro03036 panel,the best MAE of 4.2978 was reached using the k-Nearest Neighbor(k-NN)algorithm,which was set up as instance-based k-Nearest neighbors(IBk)in Weka after being trained on 17 days of data.Regression performance for most models(excluding IBk)stabilizes at 14 days or more.Compared to the 7-day dataset,increasing to 21 days reduced the MAE by around 20%and improved correlation coefficients by around 2.1%,highlighting the value of moderate dataset expansion.These findings suggest that datasets spanning 17 to 21 days,with 80%used for training,can significantly enhance the predictive accuracy of solar power generation models.展开更多
This paper explores pole placement techniques for the 4th order C1 DC-to-DC Buck converter focusing on optimizing various performance metrics. Refinements were made to existing ITAE (Integral of Time-weighted Absolute...This paper explores pole placement techniques for the 4th order C1 DC-to-DC Buck converter focusing on optimizing various performance metrics. Refinements were made to existing ITAE (Integral of Time-weighted Absolute Error) polynomials. Additionally, metrics such as IAE (Integral Absolute Error), ISE (Integral of Square Error), ITSE (Integral of Time Squared Error), a MaxMin metric as well as LQR (Linear Quadratic Regulator) were evaluated. PSO (Particle Swarm Optimization) was employed for metric optimization. Time domain response to a step disturbance input was evaluated. The design which optimized the ISE metric proved to be the best performing, followed by IAE and MaxMin (with equivalent results) and then LQR.展开更多
One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are ...One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.展开更多
High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters ...High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters analyzed were collected monthly from January 2021 to December 2021.Multivariate statistical techniques,such as the absolute principal component score-multiple linear regression model(APCS-MLR),correlation analysis,and analysis of variance were used to identify and quantify the potential sources or factors affecting water quality and to analyze the spatial-temporal variation in water quality.The water quality indices(WQIs),ranging from 67.96 to 70.67,showed that the water quality was at an intermediate level in the estuaries during both the flood and nonflood seasons.The concentrations of total phosphorus(TP),ammonia N(AN),and organic pollutants were greater in the Haihe River Basin than in the Liaohe River and Huanghe-Huaihe River Basins.The concentration of total nitrogen(TN)in the Haihe River Basin was lower than that in the Liaohe River and Huanghe-Huaihe River Basins.Heavy metal concentrations in the Liaohe River Basin were greater than those in the Haihe River and Huanghe-Huaihe River Basins.The annual mean concentrations of AN in the estuaries of the Haihe,Liaohe,and Huanghe(Yellow)rivers exhibited significant decreasing trends from 2013 to 2022,but no significant decreasing trends were found for permanganate index(COD_(Mn))or the TP.The concentrations of TN and AN were lower in the flood season than in the nonflood season,and the TP concentration was greater in the flood season than in the nonflood season.However,the concentrations of organic pollutants did not exhibit significant differences.Domestic sewage and industrial wastewater,substance exchange between air and water,nonpoint sources from rural and urban areas,and aquaculture wastewater were the major sources or factors responsible for water pollution in the estuaries.展开更多
In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited ...In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.展开更多
An electronic circular dichroism(ECD)-based chiroptical sensing method has been developed forβ-andγ-chiral primary amines via a C-H activation reaction.With the addition of Pd(OAc)_(2),the flexible remote chiral pri...An electronic circular dichroism(ECD)-based chiroptical sensing method has been developed forβ-andγ-chiral primary amines via a C-H activation reaction.With the addition of Pd(OAc)_(2),the flexible remote chiral primary amine fragment in the bidentate ligand intermediate was fixed to form a cyclopalladium complex,producing an intense ECD response.The correlation between the sign of Cotton effects and the absolute configuration of substrates was proposed,together with theoretical verification using timedependent density functional theory(TDDFT).Chiroptical sensing of an important drug raw material was performed to provide rapid and accurate information on the absolute optical purity.This work introduces an alternative perspective of C-H activation reaction as well as a feasible chiroptical sensing method of remote chiral amines.展开更多
The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^...The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^(2+),O_(2)^(2+)O^(+),O^(2+),and their total)and two Coulomb explosion channels(O^(+)+O^(+)and O^(2+)+O^(+))are obtained by putting the data of O^(2+)on the scale of Ar+from O_(2)and Ar gases mixed with a fixed relative flow ratio of 1:1.The experimental errors are assessed by taking uncertainties of various factors into account.The present absolute cross sections are well consistent with the previous data in the overlapped energy range below 1000 eV.展开更多
Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamen...Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.展开更多
The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with ...The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.展开更多
BACKGROUND Difficulty of colonoscopy insertion(DCI)significantly affects colonoscopy effectiveness and serves as a key quality indicator.Predicting and evaluating DCI risk preoperatively is crucial for optimizing intr...BACKGROUND Difficulty of colonoscopy insertion(DCI)significantly affects colonoscopy effectiveness and serves as a key quality indicator.Predicting and evaluating DCI risk preoperatively is crucial for optimizing intraoperative strategies.AIM To evaluate the predictive performance of machine learning(ML)algorithms for DCI by comparing three modeling approaches,identify factors influencing DCI,and develop a preoperative prediction model using ML algorithms to enhance colonoscopy quality and efficiency.METHODS This cross-sectional study enrolled 712 patients who underwent colonoscopy at a tertiary hospital between June 2020 and May 2021.Demographic data,past medical history,medication use,and psychological status were collected.The endoscopist assessed DCI using the visual analogue scale.After univariate screening,predictive models were developed using multivariable logistic regression,least absolute shrinkage and selection operator(LASSO)regression,and random forest(RF)algorithms.Model performance was evaluated based on discrimination,calibration,and decision curve analysis(DCA),and results were visualized using nomograms.RESULTS A total of 712 patients(53.8%male;mean age 54.5 years±12.9 years)were included.Logistic regression analysis identified constipation[odds ratio(OR)=2.254,95%confidence interval(CI):1.289-3.931],abdominal circumference(AC)(77.5–91.9 cm,OR=1.895,95%CI:1.065-3.350;AC≥92 cm,OR=1.271,95%CI:0.730-2.188),and anxiety(OR=1.071,95%CI:1.044-1.100)as predictive factors for DCI,validated by LASSO and RF methods.Model performance revealed training/validation sensitivities of 0.826/0.925,0.924/0.868,and 1.000/0.981;specificities of 0.602/0.511,0.510/0.562,and 0.977/0.526;and corresponding area under the receiver operating characteristic curves(AUCs)of 0.780(0.737-0.823)/0.726(0.654-0.799),0.754(0.710-0.798)/0.723(0.656-0.791),and 1.000(1.000-1.000)/0.754(0.688-0.820),respectively.DCA indicated optimal net benefit within probability thresholds of 0-0.9 and 0.05-0.37.The RF model demonstrated superior diagnostic accuracy,reflected by perfect training sensitivity(1.000)and highest validation AUC(0.754),outperforming other methods in clinical applicability.CONCLUSION The RF-based model exhibited superior predictive accuracy for DCI compared to multivariable logistic and LASSO regression models.This approach supports individualized preoperative optimization,enhancing colonoscopy quality through targeted risk stratification.展开更多
Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence t...Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.展开更多
Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous ...Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.展开更多
The mechanisms of mushroom polysaccharides on immune functions and lipid metabolism of aged mammals have not been fully elucidated.In the present study,after assessing the impacts of one type of Lentinula edodes-deriv...The mechanisms of mushroom polysaccharides on immune functions and lipid metabolism of aged mammals have not been fully elucidated.In the present study,after assessing the impacts of one type of Lentinula edodes-derived polysaccharides,named L2,on immune functions and blood lipid profiles,isobaric tags for relative and absolute quantification(iTRAQ)-based proteomic profiling of the small intestinal tissues from aged mice treated with L2 was performed.L2 reversed immune function declines and modulated the lipid metabolism of aged mice evidenced by increased levels of serum TC,HDL-C,and LDL-C,and reduced levels of serum TG.Moreover,a total of 95 differentially regulated proteins(DRPs) were identified,of which75 were up-regulated and 20 were down-regulated.Most of the DRPs were involved in intracellular and extracellular structure organization,and cellular and metabolic regulation.Particularly,approximately 16 and 9 DRPs participated in the regulation of immune functions and lipid metabolism,respectively.Furthermore,protein-protein interaction analysis highlighted that cadherin-1,plectin,cadherin-17,Ras GTPase-activating-like protein IQGAP2,and ezrin might be key proteins in response to L2 treatment.These findings provide new insights into the biological mechanisms of mushroom polysaccharides in anti-aging from a proteomic perspective.展开更多
基金supported by the National Natural Science Foundation of China(42122017,41821002)the Independent Innovation Research Program of China University of Petroleum(East China)(21CX06001A).
文摘It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs.To address the problem of low resolution in logging curves,this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification,working with the Shahejie For-mation,Bohai Bay Basin,China.The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features.The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition+total organic carbon)of shale,while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type.The research results show that the grayscale phase model can identify shale lithofacies well,and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition,as well as corresponding re-lationships between relative amplitudes and laminae development in shales.Four lithofacies are iden-tified in the target layer of the study area:massive mixed shale,laminated mixed shale,massive calcareous shale and laminated calcareous shale.This method can not only effectively characterize the material composition of shale,but also numerically characterize the development degree of shale laminae,and solve the problem that difficult to identify millimeter-scale laminae based on logging curves,which can provide technical support for shale lithofacies identification,sweet spot evaluation and prediction of complex continental lacustrine basins.
基金supported by the Faculty Research Fund(Faculty of Medicine&Health Science,Keele University)Career Development Award–(April 2022)(to SJB)。
文摘Spinal muscular atrophy(SMA)is a genetic condition that results in selective lower motor neuron loss with concomitant muscle weakness and atrophy.The genetic cause of SMA was understood in 1995 when loss or impairment of the survival motor neuron 1(SMN1)gene was identified as the main contributing factor(Lefebvre et al.,1995).This,in combination with the discovery that humans have a“back-up”gene,SMN2,which can produce low levels(approximately 10%)of the full-length functional SMN protein,has led to the generation of SMA-specific gene therapies.SMA was traditionally classified according to age of symptom onset and developmental milestones achieved,with life expectancy and severity varying between individuals.Now,SMN2 copy number is used as a proxy for the prediction of disease severity,with higher SMN2 copy number typically being associated with reduced severity of SMA,although this relationship is not absolute:some individuals with low SMN2 copy number have less severe SMA phenotypes and vice versa.Additionally,the etiology of SMA is further complicated by other factors,such as non-typical nucleotide variants and SMN2-independent modifiers of disease severity.
基金Supported by the National Natural Science Foundation of China (12061061)Fundamental Research Funds for the Central Universities (31920230173)+1 种基金Longyuan Young Talents of Gansu ProvinceYoung Talents Team Project of Gansu Province (2025QNTD49)。
文摘The notion of absolutely clean N-complexes is studied.We show that an N-complex X is absolutely clean if and only if X is Nexact and Z,(X)is an absolutely clean module for each n e Z and i=1,2,..,N.In particular,we prove that a bounded above N-complex X is absolutely clean if and only if X,is an absolutely clean module for each n e Z.We also show that under certain hypotheses,an Ncomplex X is Gorenstein AC-injective if and only if Z;(X)is a Gorenstein AC-injective module for each n e Z and t=1,2,.,N.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC2307305,2021YFF0703300)the Shenzhen Medical Research Fund(No.B2303003)+3 种基金Shenzhen Research Funding Program(Nos.JCYJ20220818102014028,RCBS20210609104339043)National Natural Science Foundation of China(No.22174167)Guangdong Basic and Applied Basic Research(No.2024A1515011281)Fundamental Research Funds for the Central Universities(No.24qnpy087)from Sun Yat-sen University。
文摘Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.
基金supported by the National Natural Science Foundation of China(Grant No.11732006)the“Qinglan Project”of Jiangsu Higher Education Institutions.
文摘Quasi-zero stiffness(QZS)isolators have received considerable attention over the past years due to their outstanding vibration isolation performance in low-frequency bands.However,traditional mechanisms for achieving QZS suffer from low stiffness regions and significant nonlinear restoring forces with hardening characteristics,often struggling to withstand excitations with high amplitude.This paper presents a novel QZS vibration isolator that utilizes a more compact spring-rod mechanism(SRM)to provide primary negative stiffness.The nonlinearity of SRM is adjustable via altering the raceway of its spring-rod end,along with the compensatory force provided by the cam-roller mechanism so as to avoid complex nonlinear behaviors.The absolute zero stiffness can be achieved by a well-designed raceway curve with a concise mathematical expression.The nonlinear stiffness with softening properties can also be achieved by parameter adjustment.The study begins with the forcedisplacement relationship of the integrated mechanism first,followed by the design theory of the cam profile.The dynamic response and absolute displacement transmissibility of the isolation system are obtained based on the harmonic balance method.The experimental results show that the proposed vibration isolator maintains relatively low-dynamic stiffness even under non-ideal conditions,and exhibits enhanced vibration isolation performance compared to the corresponding linear isolator.
文摘A Bose-Einstein condensate (BEC) is a topic of significant interest within the scientific community. It is well understood that Rb-87 and Yb2Si2O7 have been utilized in experiments to explore this phenomenon. These studies have demonstrated that these materials can achieve the BEC phase, a state that has been experimentally validated. In this paper, we further establish, from the perspective of theoretical physics, that silicon is also capable of exhibiting BEC properties. Our approach differs from prior studies in that it uses innovatively certain boundary conditions. Specifically, we employed Yb-70 as a gamma-ray radiation source and a 1 nm linewidth (as the half-width of a 2 nm line). Additionally, we utilized the concept of half-value thickness from nuclear physics absorption models to optimize the semiconductor process. This method effectively removes ytterbium (Yb) during the process, leaving only silicon, silicon-based materials, or silicon topological superconductors on the wafer. This technical procedure results in the creation of “BEC silicon” at absolute zero temperature (0 K), introducing a novel material for BEC realization.
文摘Knowing the influence of the size of datasets for regression models can help in improving the accuracy of a solar power forecast and make the most out of renewable energy systems.This research explores the influence of dataset size on the accuracy and reliability of regression models for solar power prediction,contributing to better forecasting methods.The study analyzes data from two solar panels,aSiMicro03036 and aSiTandem72-46,over 7,14,17,21,28,and 38 days,with each dataset comprising five independent and one dependent parameter,and split 80–20 for training and testing.Results indicate that Random Forest consistently outperforms other models,achieving the highest correlation coefficient of 0.9822 and the lowest Mean Absolute Error(MAE)of 2.0544 on the aSiTandem72-46 panel with 21 days of data.For the aSiMicro03036 panel,the best MAE of 4.2978 was reached using the k-Nearest Neighbor(k-NN)algorithm,which was set up as instance-based k-Nearest neighbors(IBk)in Weka after being trained on 17 days of data.Regression performance for most models(excluding IBk)stabilizes at 14 days or more.Compared to the 7-day dataset,increasing to 21 days reduced the MAE by around 20%and improved correlation coefficients by around 2.1%,highlighting the value of moderate dataset expansion.These findings suggest that datasets spanning 17 to 21 days,with 80%used for training,can significantly enhance the predictive accuracy of solar power generation models.
文摘This paper explores pole placement techniques for the 4th order C1 DC-to-DC Buck converter focusing on optimizing various performance metrics. Refinements were made to existing ITAE (Integral of Time-weighted Absolute Error) polynomials. Additionally, metrics such as IAE (Integral Absolute Error), ISE (Integral of Square Error), ITSE (Integral of Time Squared Error), a MaxMin metric as well as LQR (Linear Quadratic Regulator) were evaluated. PSO (Particle Swarm Optimization) was employed for metric optimization. Time domain response to a step disturbance input was evaluated. The design which optimized the ISE metric proved to be the best performing, followed by IAE and MaxMin (with equivalent results) and then LQR.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2024B08。
文摘One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.
基金Supported by the National Natural Science Foundation of China(No.41571479)。
文摘High-dimensional data(a dataset with many features)were collected from 64 sampling sites to analyze the water quality in estuaries along the coast of the Bohai Sea,North China.The twenty-five water quality parameters analyzed were collected monthly from January 2021 to December 2021.Multivariate statistical techniques,such as the absolute principal component score-multiple linear regression model(APCS-MLR),correlation analysis,and analysis of variance were used to identify and quantify the potential sources or factors affecting water quality and to analyze the spatial-temporal variation in water quality.The water quality indices(WQIs),ranging from 67.96 to 70.67,showed that the water quality was at an intermediate level in the estuaries during both the flood and nonflood seasons.The concentrations of total phosphorus(TP),ammonia N(AN),and organic pollutants were greater in the Haihe River Basin than in the Liaohe River and Huanghe-Huaihe River Basins.The concentration of total nitrogen(TN)in the Haihe River Basin was lower than that in the Liaohe River and Huanghe-Huaihe River Basins.Heavy metal concentrations in the Liaohe River Basin were greater than those in the Haihe River and Huanghe-Huaihe River Basins.The annual mean concentrations of AN in the estuaries of the Haihe,Liaohe,and Huanghe(Yellow)rivers exhibited significant decreasing trends from 2013 to 2022,but no significant decreasing trends were found for permanganate index(COD_(Mn))or the TP.The concentrations of TN and AN were lower in the flood season than in the nonflood season,and the TP concentration was greater in the flood season than in the nonflood season.However,the concentrations of organic pollutants did not exhibit significant differences.Domestic sewage and industrial wastewater,substance exchange between air and water,nonpoint sources from rural and urban areas,and aquaculture wastewater were the major sources or factors responsible for water pollution in the estuaries.
基金supported by the National Natural Science Foundation of China(No.U2037602)。
文摘In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.
基金supported by the CAMS Innovation Fund for Medical Sciences(CIFMS,No.2023-I2M-2-009).
文摘An electronic circular dichroism(ECD)-based chiroptical sensing method has been developed forβ-andγ-chiral primary amines via a C-H activation reaction.With the addition of Pd(OAc)_(2),the flexible remote chiral primary amine fragment in the bidentate ligand intermediate was fixed to form a cyclopalladium complex,producing an intense ECD response.The correlation between the sign of Cotton effects and the absolute configuration of substrates was proposed,together with theoretical verification using timedependent density functional theory(TDDFT).Chiroptical sensing of an important drug raw material was performed to provide rapid and accurate information on the absolute optical purity.This work introduces an alternative perspective of C-H activation reaction as well as a feasible chiroptical sensing method of remote chiral amines.
基金supported by the National Key Research and Development Program of China(No.2022YFA1602502)the National Natural Science Foundation of China(No.12127804).
文摘The direct and dissociative ionizations of oxygen molecule are investigated experimen-tally by electron collision with energies from 350 eV to 8000 eV.The absolute ionization cross sections for the product ions(O_(2)^(2+),O_(2)^(2+)O^(+),O^(2+),and their total)and two Coulomb explosion channels(O^(+)+O^(+)and O^(2+)+O^(+))are obtained by putting the data of O^(2+)on the scale of Ar+from O_(2)and Ar gases mixed with a fixed relative flow ratio of 1:1.The experimental errors are assessed by taking uncertainties of various factors into account.The present absolute cross sections are well consistent with the previous data in the overlapped energy range below 1000 eV.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC2204601)the National Natural Science Foundation of China(Grant Nos.11925503 and 12275093)+1 种基金the Natural Science Foundation of Hubei Province(Grant No.2021CFB019)the State Key Laboratory of Applied Optics(Grant No.SKLAO2022001A10).
文摘Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272123 and 12302047)the Natural Science Foundation of Jiangsu Province(Grant No.BK20231185)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX24_0192).
文摘The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.
基金the Chinese Clinical Trial Registry(No.ChiCTR2000040109)approved by the Hospital Ethics Committee(No.20210130017).
文摘BACKGROUND Difficulty of colonoscopy insertion(DCI)significantly affects colonoscopy effectiveness and serves as a key quality indicator.Predicting and evaluating DCI risk preoperatively is crucial for optimizing intraoperative strategies.AIM To evaluate the predictive performance of machine learning(ML)algorithms for DCI by comparing three modeling approaches,identify factors influencing DCI,and develop a preoperative prediction model using ML algorithms to enhance colonoscopy quality and efficiency.METHODS This cross-sectional study enrolled 712 patients who underwent colonoscopy at a tertiary hospital between June 2020 and May 2021.Demographic data,past medical history,medication use,and psychological status were collected.The endoscopist assessed DCI using the visual analogue scale.After univariate screening,predictive models were developed using multivariable logistic regression,least absolute shrinkage and selection operator(LASSO)regression,and random forest(RF)algorithms.Model performance was evaluated based on discrimination,calibration,and decision curve analysis(DCA),and results were visualized using nomograms.RESULTS A total of 712 patients(53.8%male;mean age 54.5 years±12.9 years)were included.Logistic regression analysis identified constipation[odds ratio(OR)=2.254,95%confidence interval(CI):1.289-3.931],abdominal circumference(AC)(77.5–91.9 cm,OR=1.895,95%CI:1.065-3.350;AC≥92 cm,OR=1.271,95%CI:0.730-2.188),and anxiety(OR=1.071,95%CI:1.044-1.100)as predictive factors for DCI,validated by LASSO and RF methods.Model performance revealed training/validation sensitivities of 0.826/0.925,0.924/0.868,and 1.000/0.981;specificities of 0.602/0.511,0.510/0.562,and 0.977/0.526;and corresponding area under the receiver operating characteristic curves(AUCs)of 0.780(0.737-0.823)/0.726(0.654-0.799),0.754(0.710-0.798)/0.723(0.656-0.791),and 1.000(1.000-1.000)/0.754(0.688-0.820),respectively.DCA indicated optimal net benefit within probability thresholds of 0-0.9 and 0.05-0.37.The RF model demonstrated superior diagnostic accuracy,reflected by perfect training sensitivity(1.000)and highest validation AUC(0.754),outperforming other methods in clinical applicability.CONCLUSION The RF-based model exhibited superior predictive accuracy for DCI compared to multivariable logistic and LASSO regression models.This approach supports individualized preoperative optimization,enhancing colonoscopy quality through targeted risk stratification.
基金supported by the National Natural Science Foundation of China(62175156,81827807)the Science and Technology Commission of Shanghai Municipality(22S31903000)+3 种基金the Collaborative Innovation Project of Shanghai Institute of Technology(XTCX2022-27)the Shenzhen Basic Research Key Project(JCYJ20220818103212026)the Shenzhen Key Technology Project(JSGGZD20220822095200002)the Shenzhen Outstanding Scientific and Technological Innovation Talents Distinguished Young Scientists(RCJC20210609104443085).
文摘Visualizing blood flow velocity distribution is essential for comprehending the pathogenesis of various diseases and facilitating early diagnosis and treatment.Current hemodynamic studies utilizing optical coherence tomography(OCT)primarily rely on Doppler OCT(D-OCT)and OCT Angiography(OCTA),which measure axial blood vessel velocity or visualize the vascular architecture,respectively.However,these techniques have limitations in accurately quantifying the absolute velocity of red blood cells(RBCs).This study presents a novel method based on microsphere tracking,which enables precise quantification of absolute blood flow velocity along a blood vessel.In phantom experiments,freshly harvested blood mixed with microspheres was infused into a cellulose tube to simulate a single blood vessel.Experimental results,demon-strating an error margin of less than 10%,validated the effectiveness of this method.Blood flow velocities ranging from 0.472 mm/s to 18.9 mm/s were accurately measured.A preliminary in vivo examination of rabbit ear vessels was conducted,further validating the reliability of this method.This study presents a potential method for specific disease diagnosis by detecting tar-geted vessel flow velocity variations using swept-source optical coherence tomography(SS-OCT)combined with microsphere tracking.
基金supported by Shanghai Municipal Commission of Science and Technology,China(Grant No.:19XD1400300)the National Natural Science Foundation of China(Grant Nos.:821040821,82273867,and 82030107).
文摘Amphiphiles,including surfactants,have emerged as indispensable elements in materials science and pharmaceutical science,and their functions are highly relying on the critical micelle concentration(CMC)[1,2].Numerous fluorimetry-based probes have been developed to measure CMCs[3](Fig.S1).However,CMC measurements using these probes suffer from a time-consuming and laborious procedure and large uncertainties,primarily due to their poor photo-stabilities and highly fluctuating fluorescence backgrounds.
基金supported by the Key-Area Research and Development Program of Guangdong Province (2021B0707060001)the Program for Scientific Research Start-Up Funds of Guangdong Ocean UniversityChina Postdoctoral Science Foundation (2016T90787)。
文摘The mechanisms of mushroom polysaccharides on immune functions and lipid metabolism of aged mammals have not been fully elucidated.In the present study,after assessing the impacts of one type of Lentinula edodes-derived polysaccharides,named L2,on immune functions and blood lipid profiles,isobaric tags for relative and absolute quantification(iTRAQ)-based proteomic profiling of the small intestinal tissues from aged mice treated with L2 was performed.L2 reversed immune function declines and modulated the lipid metabolism of aged mice evidenced by increased levels of serum TC,HDL-C,and LDL-C,and reduced levels of serum TG.Moreover,a total of 95 differentially regulated proteins(DRPs) were identified,of which75 were up-regulated and 20 were down-regulated.Most of the DRPs were involved in intracellular and extracellular structure organization,and cellular and metabolic regulation.Particularly,approximately 16 and 9 DRPs participated in the regulation of immune functions and lipid metabolism,respectively.Furthermore,protein-protein interaction analysis highlighted that cadherin-1,plectin,cadherin-17,Ras GTPase-activating-like protein IQGAP2,and ezrin might be key proteins in response to L2 treatment.These findings provide new insights into the biological mechanisms of mushroom polysaccharides in anti-aging from a proteomic perspective.
