The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates ...The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.展开更多
Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CA...Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.展开更多
Objective:To collate and summarize phenotypic insecticide susceptibility data of Indian malaria vectors from 2017 to 2024,focusing on insecticides used in adult vector control,dichloro diphenyl trichloroethane,malathi...Objective:To collate and summarize phenotypic insecticide susceptibility data of Indian malaria vectors from 2017 to 2024,focusing on insecticides used in adult vector control,dichloro diphenyl trichloroethane,malathion,deltamethrin,alpha-cypermethrin,and permethrin to identify resistance patterns to different classes of insecticides.Methods:The data included information on vector species,location of the study(state/district),insecticide tested,mortality percentage,and susceptibility classification based on the World Health Organization interpretation criteria.Retrospective data were collected from peer-reviewed publications(2017-2024)and up to June 2025.The data were collated for five major malaria vector species,namely Anopheles(An.)culicifacies,An.fluviatilis,An.stephensi,An.baimaii,and An.minimus.Results:Insecticide susceptibility data were available from 86 districts across 16 Indian states for 40615 mosquitoes.The majority of the data was on An.culicifacies(n=28308),followed by An.stephensi(n=5611),An.fluviatilis(n=5967),An.baimaii(n=365),and An.minimus(n=364).Intensity bioassays revealed low to moderate resistance levels in An.culicifacies populations from selected districts in 3 states,Odisha,Madhya Pradesh,and Chhattisgarh against deltamethrin and alpha-cypermethrin.Conclusions:This review highlights spatial and species-level variations in insecticide susceptibility among Indian malaria vectors.The low to moderate intensity suggested that it may not yet be severe enough to cause operational failure with current vector control interventions.Continued monitoring of insecticide resistance,as well as the use of new-generation insecticides and interventions,is suggested to sustain vector control efficacy and manage insecticide resistance in malaria vectors to support India’s malaria elimination.展开更多
In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family...In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family of vertex operator algebras V_(√kA_(1)) associated to rank-one positive definite even lattices √kA_(1) for arbitrary positive integers k to characterize these even lattice vertex operator algebras.In such a family of lattice vertex operator algebras V_(√kA_(1)),the vertex operator algebra V_(√2A_(1)) is different from others.Hence we describe the varieties of semi-conformal vectors of V_(√2A_(1)) and the fixed vertex operator subalgebra V^(+)√2A_(1).Moreover,as applications,we study the relations between vertex operator algebras V_(√kA_(1) )and L_(sl_(2))(k,0)for arbitrary positive integers k by the viewpoint of semi-conformal homomorphisms of vertex operator algebras.For case k=2,in the series of rational simple affine vertex operator algebras L_(sl_(2))(k,0)for positive integers k,we show that L_(sl_(2))(2,0)is a unique frame vertex operator algebra with rank 3.展开更多
Intervertebral disc degeneration is a leading cause of lower back pain and is characterized by pathological processes such as nucleus pulposus cell apoptosis,extracellular matrix imbalance,and annulus fibrosus rupture...Intervertebral disc degeneration is a leading cause of lower back pain and is characterized by pathological processes such as nucleus pulposus cell apoptosis,extracellular matrix imbalance,and annulus fibrosus rupture.These pathological changes result in disc height loss and functional decline,potentially leading to disc herniation.This comprehensive review aimed to address the current challenges in intervertebral disc degeneration treatment by evaluating the regenerative potential of stem cell-based therapies,with a particular focus on emerging technologies such as exosomes and gene vector systems.Through mechanisms such as differentiation,paracrine effects,and immunomodulation,stem cells facilitate extracellular matrix repair and reduce nucleus pulposus cell apoptosis.Despite recent advancements,clinical applications are hindered by challenges such as hypoxic disc environments and immune rejection.By analyzing recent preclinical and clinical findings,this review provided insights into optimizing stem cell therapy to overcome these obstacles and highlighted future directions in the field.展开更多
This paper presents an improved,energy-efficient Model Predictive Current Control(MPCC)strategy based on centroid-based virtual voltage vector synthesis for three-phase inverter-fed induction motor drives in electric ...This paper presents an improved,energy-efficient Model Predictive Current Control(MPCC)strategy based on centroid-based virtual voltage vector synthesis for three-phase inverter-fed induction motor drives in electric vehicle(EV)applications.Unlike conventional finite-set MPCC methods that rely on cost function evaluation over discrete switching states,the proposed approach eliminates the need for look-up tables by employing a pre-defined set of virtual vectors.These centroid-based virtual voltage vectors are synthesized by combining two adjacent active vectors and two nonzero voltage vectors in opposite directions adjacent to the sector replacing the traditional switching set.They approximate the reference voltage vector in both magnitude and phase angle,thereby reducing current tracking error through a simplified cost function.The number of candidate vectors is reduced,preserving computational efficiency.Furthermore,the scheme ensures zero average common-mode voltage(CMV)per sampling interval by completely avoiding zero-voltage vectors(ZVVs).The proposed method reduces torque ripple by up to 17%compared to the conventional approach and lowers stator current total harmonic distortion(THD)by 37%,while ensuring evenly distributed switching transitions among inverter legs.This results in reduced switching losses and enhanced drive efficiency-particularly advantageous in EV applications.Experimental validation under the high-speed extra urban driving cycle(EUDC)and low-speed ECE-R15 cycle,including torque ripple and energy consumption analysis,confirms the effectiveness of the approach,achieving an overall efficiency of 83.3%.展开更多
This paper is devoted to the investigation of the Landau–Ginzburg–Higgs equation(LGHe),which serves as a mathematical model to understand phenomena such as superconductivity and cyclotron waves.The LGHe finds applic...This paper is devoted to the investigation of the Landau–Ginzburg–Higgs equation(LGHe),which serves as a mathematical model to understand phenomena such as superconductivity and cyclotron waves.The LGHe finds applications in various scientific fields,including fluid dynamics,plasma physics,biological systems,and electricity-electronics.The study adopts Lie symmetry analysis as the primary framework for exploration.This analysis involves the identification of Lie point symmetries that are admitted by the differential equation.By leveraging these Lie point symmetries,symmetry reductions are performed,leading to the discovery of group invariant solutions.To obtain explicit solutions,several mathematical methods are applied,including Kudryashov's method,the extended Jacobi elliptic function expansion method,the power series method,and the simplest equation method.These methods yield solutions characterized by exponential,hyperbolic,and elliptic functions.The obtained solutions are visually represented through 3D,2D,and density plots,which effectively illustrate the nature of the solutions.These plots depict various patterns,such as kink-shaped,singular kink-shaped,bell-shaped,and periodic solutions.Finally,the paper employs the multiplier method and the conservation theorem introduced by Ibragimov to derive conserved vectors.These conserved vectors play a crucial role in the study of physical quantities,such as the conservation of energy and momentum,and contribute to the understanding of the underlying physics of the system.展开更多
A naïve discussion of Fermat’s last theorem conundrum is described. The present theorem’s proof is grounded on the well-known properties of sums of powers of the sine and cosine functions, the Minkowski norm de...A naïve discussion of Fermat’s last theorem conundrum is described. The present theorem’s proof is grounded on the well-known properties of sums of powers of the sine and cosine functions, the Minkowski norm definition, and some vector-specific structures.展开更多
Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. ...Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.展开更多
[Objective] The aim was to study the construction and expression of eukaryotic expression vectors of antibacterial peptides （mytilin and myticin） from Mytilus coruscus.[Method] By the screening of antibacterial pept...[Objective] The aim was to study the construction and expression of eukaryotic expression vectors of antibacterial peptides （mytilin and myticin） from Mytilus coruscus.[Method] By the screening of antibacterial peptide genes of mytilin and myticin of Mytilus coruscus,five antibacterial peptide genes were selected.Then,the relative eukaryotic expressing vectors were constructed by the use of PCR technique and DNA recombinant technology.Subsequently,they were transferred in to S78 Saccharomyces cerevisia by using LiAC transformation method,and then preliminary expressing analysis was carried out.[Result] Five eukaryotic expressing vectors of antibacterial peptides from Mytilus coruscus were successfully constructed,and the results of mRNA detection revealed that the five antibacterial peptides from Mytilus coruscus were successfully transcribed.[Conclusion] The results provide a basis for using genetic engineering to express antibacterial peptides of mytilin and myticin from Mytilus coruscus,and for developing the further study of antibacterial peptides from Mytilus coruscus based on this.展开更多
Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex int...Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.展开更多
Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cott...Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cotton delta-12 oleate desat- urase gene GhFAD2-1 containing an open reading frame of 1 158 bp was cloned for constructing RNAi vector. A 515 bp long specific fragment of this gene was se- lected for constructing ihpRNA vector under the control of a seed-specific promoter NAPIN, named pFGC1008-NAPIN-FAD2-1; meanwhile miRNA gene-silencing vector pCAMBIA1302-amiRNA-FAD2-1 targeting GhFAD2-1 was also constructed.展开更多
[Objective] To construct prokaryotic expression vectors encoding gene Erb3binding protein （EBP1）, which plays important roles in regulating plant organ size from Nervilia fordii （Hance） Schltr. [Methods] PCR produ...[Objective] To construct prokaryotic expression vectors encoding gene Erb3binding protein （EBP1）, which plays important roles in regulating plant organ size from Nervilia fordii （Hance） Schltr. [Methods] PCR products of NfEBP1 with particular restriction sites and expression vectors, pET-28 and pET-16b were digested. Ligation, transformation and selection were performed to construct the recombinant plasmids pET-28-NfEBP1 and pET-16-NfEBP1. The recombinant plasmids were transformed into E. coli BL21 using heat -shock transformation. [Results] Recombinant plasmids pET-28-NfEBP1-1188 and pET-16-NfEBP1-1188 were constructed and transformed into expressional host cells, E. coli BL21, and validated by colony PCR, sequencing and double digestion. [Conclusion] Prokaryotic expression vectors of EBP1 gene from N. fordii were successfully constructed, which laid the foundation for characterization of the gene function.展开更多
Glucose molecules are of great significance being one of the most important molecules in metabolic chain.However,due to the small Raman scattering cross-section and weak/non-adsorption on bare metals,accurately obtain...Glucose molecules are of great significance being one of the most important molecules in metabolic chain.However,due to the small Raman scattering cross-section and weak/non-adsorption on bare metals,accurately obtaining their"fingerprint information"remains a huge obstacle.Herein,we developed a tip-enhanced Raman scattering(TERS)technique to address this challenge.Adopting an optical fiber radial vector mode internally illuminates the plasmonic fiber tip to effectively suppress the background noise while generating a strong electric-field enhanced tip hotspot.Furthermore,the tip hotspot approaching the glucose molecules was manipulated via the shear-force feedback to provide more freedom for selecting substrates.Consequently,our TERS technique achieves the visualization of all Raman modes of glucose molecules within spectral window of 400-3200 cm^(-1),which is not achievable through the far-field/surface-enhanced Raman,or the existing TERS techniques.Our TERS technique offers a powerful tool for accurately identifying Raman scattering of molecules,paving the way for biomolecular analysis.展开更多
Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the eva...Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the evaluation of numerical weather prediction models.In this study,the authors treat vector winds as a whole by employing a vector field evaluation method,and evaluate the mesoscale model of the China Meteorological Administration(CMA-MESO)and ECMWF forecast,with reference to ERA5 reanalysis,in terms of multiple aspects of vector winds over eastern China in 2022.The results show that the ECMWF forecast is superior to CMA-MESO in predicting the spatial distribution and intensity of 10-m vector winds.Both models overestimate the wind speed in East China,and CMA-MESO overestimates the wind speed to a greater extent.The forecasting skill of the vector wind field in both models decreases with increasing lead time.The forecasting skill of CMA-MESO fluctuates more and decreases faster than that of the ECMWF forecast.There is a significant negative correlation between the model vector wind forecasting skill and terrain height.This study provides a scientific evaluation of the local application of vector wind forecasts of the CMA-MESO model and ECMWF forecast.展开更多
Diagnosing cardiac diseases relies heavily on electrocardiogram(ECG)analysis,but detecting myocardial infarction-related arrhythmias remains challenging due to irregular heartbeats and signal variations.Despite advanc...Diagnosing cardiac diseases relies heavily on electrocardiogram(ECG)analysis,but detecting myocardial infarction-related arrhythmias remains challenging due to irregular heartbeats and signal variations.Despite advancements in machine learning,achieving both high accuracy and low computational cost for arrhythmia classification remains a critical issue.Computer-aided diagnosis systems can play a key role in early detection,reducing mortality rates associated with cardiac disorders.This study proposes a fully automated approach for ECG arrhythmia classification using deep learning and machine learning techniques to improve diagnostic accuracy while minimizing processing time.The methodology consists of three stages:1)preprocessing,where ECG signals undergo noise reduction and feature extraction;2)feature Identification,where deep convolutional neural network(CNN)blocks,combined with data augmentation and transfer learning,extract key parameters;3)classification,where a hybrid CNN-SVM model is employed for arrhythmia recognition.CNN-extracted features were fed into a binary support vector machine(SVM)classifier,and model performance was assessed using five-fold cross-validation.Experimental findings demonstrated that the CNN2 model achieved 85.52%accuracy,while the hybrid CNN2-SVM approach significantly improved accuracy to 97.33%,outperforming conventional methods.This model enhances classification efficiency while reducing computational complexity.The proposed approach bridges the gap between accuracy and processing speed in ECG arrhythmia classification,offering a promising solution for real-time clinical applications.Its superior performance compared to nonlinear classifiers highlights its potential for improving automated cardiac diagnosis.展开更多
The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limite...The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.展开更多
In underground mining,especially in entry-type excavations,the instability of surrounding rock structures can lead to incalculable losses.As a crucial tool for stability analysis in entry-type excavations,the critical...In underground mining,especially in entry-type excavations,the instability of surrounding rock structures can lead to incalculable losses.As a crucial tool for stability analysis in entry-type excavations,the critical span graph must be updated to meet more stringent engineering requirements.Given this,this study introduces the support vector machine(SVM),along with multiple ensemble(bagging,adaptive boosting,and stacking)and optimization(Harris hawks optimization(HHO),cuckoo search(CS))techniques,to overcome the limitations of the traditional methods.The analysis indicates that the hybrid model combining SVM,bagging,and CS strategies has a good prediction performance,and its test accuracy reaches 0.86.Furthermore,the partition scheme of the critical span graph is adjusted based on the CS-BSVM model and 399 cases.Compared with previous empirical or semi-empirical methods,the new model overcomes the interference of subjective factors and possesses higher interpretability.Since relying solely on one technology cannot ensure prediction credibility,this study further introduces genetic programming(GP)and kriging interpolation techniques.The explicit expressions derived through GP can offer the stability probability value,and the kriging technique can provide interpolated definitions for two new subclasses.Finally,a prediction platform is developed based on the above three approaches,which can rapidly provide engineering feedback.展开更多
The Macao Science Satellite-1(known as MSS-1)is the first scientific exploration satellite that was designed to measure the Earth's low latitude magnetic field at high resolution and with high precision by collect...The Macao Science Satellite-1(known as MSS-1)is the first scientific exploration satellite that was designed to measure the Earth's low latitude magnetic field at high resolution and with high precision by collecting data in a near-equatorial orbit.Magnetic field data from MSS-1's onboard Vector Fluxgate Magnetometer(VFM),collected at a sample rate of 50 Hz,allows us to detect and investigate sources of magnetic data contamination,from DC to relevant Nyquist frequency.Here we report two types of artificial disturbances in the VFM data.One is V-shaped events concentrated at night,with frequencies sweeping from the Nyquist frequency down to zero and back up.The other is 5-Hz events(ones that exhibit a distinct 5 Hz spectrum peak);these events are always accompanied by intervals of spiky signals,and are clearly related to the attitude control of the satellite.Our analyses show that VFM noise levels in daytime are systematically lower than in nighttime.The daily average noise levels exhibit a period of about 52 days.The V-shaped events are strongly correlated with higher VFM noise levels.展开更多
基金supported by grants PID2020-120308RB-I00 and PID2023-147802OB-I00 funded by MICIU/AEI/10.13039/501100011033FEDER,UE,by Aligning Science Across Parkinson’s(ref.ASAP-020505)through the Michael J.Fox Foundation for Parkinson’s Research+1 种基金by CiberNed Intramural Collaborative Projects(ref.PI2020/09)by the Spanish Fundación Mutua Madrile?a de Investigación Médica(to JLL)。
文摘The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.
基金supported by grants from the Noncommunicable Chronic Diseases-National Science and Technology Major Project(Grant No.2023ZD0501300)Science Technology Department of Zhejiang Province(Grant No.2021C03117)+2 种基金National Natural Science Foundation of China(Grant No.82350104 and 82170219)Natural Science Foundation of Zhejiang Province,China(Grant No.LY23H080004 and LY24H080001)Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(Grant No.2021KY199)。
文摘Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.
文摘Objective:To collate and summarize phenotypic insecticide susceptibility data of Indian malaria vectors from 2017 to 2024,focusing on insecticides used in adult vector control,dichloro diphenyl trichloroethane,malathion,deltamethrin,alpha-cypermethrin,and permethrin to identify resistance patterns to different classes of insecticides.Methods:The data included information on vector species,location of the study(state/district),insecticide tested,mortality percentage,and susceptibility classification based on the World Health Organization interpretation criteria.Retrospective data were collected from peer-reviewed publications(2017-2024)and up to June 2025.The data were collated for five major malaria vector species,namely Anopheles(An.)culicifacies,An.fluviatilis,An.stephensi,An.baimaii,and An.minimus.Results:Insecticide susceptibility data were available from 86 districts across 16 Indian states for 40615 mosquitoes.The majority of the data was on An.culicifacies(n=28308),followed by An.stephensi(n=5611),An.fluviatilis(n=5967),An.baimaii(n=365),and An.minimus(n=364).Intensity bioassays revealed low to moderate resistance levels in An.culicifacies populations from selected districts in 3 states,Odisha,Madhya Pradesh,and Chhattisgarh against deltamethrin and alpha-cypermethrin.Conclusions:This review highlights spatial and species-level variations in insecticide susceptibility among Indian malaria vectors.The low to moderate intensity suggested that it may not yet be severe enough to cause operational failure with current vector control interventions.Continued monitoring of insecticide resistance,as well as the use of new-generation insecticides and interventions,is suggested to sustain vector control efficacy and manage insecticide resistance in malaria vectors to support India’s malaria elimination.
基金Supported by National Natural Science Foundation of China(Grant No.12475002).
文摘In this paper,we shall study structures of even lattice vertex operator algebras by using the geometry of the varieties of their semi-conformal vectors.We first give the varieties of semi-conformal vectors of a family of vertex operator algebras V_(√kA_(1)) associated to rank-one positive definite even lattices √kA_(1) for arbitrary positive integers k to characterize these even lattice vertex operator algebras.In such a family of lattice vertex operator algebras V_(√kA_(1)),the vertex operator algebra V_(√2A_(1)) is different from others.Hence we describe the varieties of semi-conformal vectors of V_(√2A_(1)) and the fixed vertex operator subalgebra V^(+)√2A_(1).Moreover,as applications,we study the relations between vertex operator algebras V_(√kA_(1) )and L_(sl_(2))(k,0)for arbitrary positive integers k by the viewpoint of semi-conformal homomorphisms of vertex operator algebras.For case k=2,in the series of rational simple affine vertex operator algebras L_(sl_(2))(k,0)for positive integers k,we show that L_(sl_(2))(2,0)is a unique frame vertex operator algebra with rank 3.
基金Supported by Henan Province Key Research and Development Program,No.231111311000Henan Provincial Science and Technology Research Project,No.232102310411+2 种基金Henan Province Medical Science and Technology Key Project,No.LHGJ20220566 and No.LHGJ20240365Henan Province Medical Education Research Project,No.WJLX2023079Zhengzhou Medical and Health Technology Innovation Guidance Program,No.2024YLZDJH022.
文摘Intervertebral disc degeneration is a leading cause of lower back pain and is characterized by pathological processes such as nucleus pulposus cell apoptosis,extracellular matrix imbalance,and annulus fibrosus rupture.These pathological changes result in disc height loss and functional decline,potentially leading to disc herniation.This comprehensive review aimed to address the current challenges in intervertebral disc degeneration treatment by evaluating the regenerative potential of stem cell-based therapies,with a particular focus on emerging technologies such as exosomes and gene vector systems.Through mechanisms such as differentiation,paracrine effects,and immunomodulation,stem cells facilitate extracellular matrix repair and reduce nucleus pulposus cell apoptosis.Despite recent advancements,clinical applications are hindered by challenges such as hypoxic disc environments and immune rejection.By analyzing recent preclinical and clinical findings,this review provided insights into optimizing stem cell therapy to overcome these obstacles and highlighted future directions in the field.
文摘This paper presents an improved,energy-efficient Model Predictive Current Control(MPCC)strategy based on centroid-based virtual voltage vector synthesis for three-phase inverter-fed induction motor drives in electric vehicle(EV)applications.Unlike conventional finite-set MPCC methods that rely on cost function evaluation over discrete switching states,the proposed approach eliminates the need for look-up tables by employing a pre-defined set of virtual vectors.These centroid-based virtual voltage vectors are synthesized by combining two adjacent active vectors and two nonzero voltage vectors in opposite directions adjacent to the sector replacing the traditional switching set.They approximate the reference voltage vector in both magnitude and phase angle,thereby reducing current tracking error through a simplified cost function.The number of candidate vectors is reduced,preserving computational efficiency.Furthermore,the scheme ensures zero average common-mode voltage(CMV)per sampling interval by completely avoiding zero-voltage vectors(ZVVs).The proposed method reduces torque ripple by up to 17%compared to the conventional approach and lowers stator current total harmonic distortion(THD)by 37%,while ensuring evenly distributed switching transitions among inverter legs.This results in reduced switching losses and enhanced drive efficiency-particularly advantageous in EV applications.Experimental validation under the high-speed extra urban driving cycle(EUDC)and low-speed ECE-R15 cycle,including torque ripple and energy consumption analysis,confirms the effectiveness of the approach,achieving an overall efficiency of 83.3%.
基金the South African National Space Agency (SANSA) for funding this work
文摘This paper is devoted to the investigation of the Landau–Ginzburg–Higgs equation(LGHe),which serves as a mathematical model to understand phenomena such as superconductivity and cyclotron waves.The LGHe finds applications in various scientific fields,including fluid dynamics,plasma physics,biological systems,and electricity-electronics.The study adopts Lie symmetry analysis as the primary framework for exploration.This analysis involves the identification of Lie point symmetries that are admitted by the differential equation.By leveraging these Lie point symmetries,symmetry reductions are performed,leading to the discovery of group invariant solutions.To obtain explicit solutions,several mathematical methods are applied,including Kudryashov's method,the extended Jacobi elliptic function expansion method,the power series method,and the simplest equation method.These methods yield solutions characterized by exponential,hyperbolic,and elliptic functions.The obtained solutions are visually represented through 3D,2D,and density plots,which effectively illustrate the nature of the solutions.These plots depict various patterns,such as kink-shaped,singular kink-shaped,bell-shaped,and periodic solutions.Finally,the paper employs the multiplier method and the conservation theorem introduced by Ibragimov to derive conserved vectors.These conserved vectors play a crucial role in the study of physical quantities,such as the conservation of energy and momentum,and contribute to the understanding of the underlying physics of the system.
文摘A naïve discussion of Fermat’s last theorem conundrum is described. The present theorem’s proof is grounded on the well-known properties of sums of powers of the sine and cosine functions, the Minkowski norm definition, and some vector-specific structures.
文摘Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.
基金Supported by Agricultural Research Project of Science and Technology Department of Zhejiang Province(2008C22026,2009C32016)Open Topic of Key Open Laboratory of Marine and Estuarine Fishery Resources and Ecology, Ministry of Agriculture ( Open-09-10 )+1 种基金Technology Bureau Project of Zhoushan City (Y20082080)Innovative Business Incubation Program of College Students~~
文摘[Objective] The aim was to study the construction and expression of eukaryotic expression vectors of antibacterial peptides （mytilin and myticin） from Mytilus coruscus.[Method] By the screening of antibacterial peptide genes of mytilin and myticin of Mytilus coruscus,five antibacterial peptide genes were selected.Then,the relative eukaryotic expressing vectors were constructed by the use of PCR technique and DNA recombinant technology.Subsequently,they were transferred in to S78 Saccharomyces cerevisia by using LiAC transformation method,and then preliminary expressing analysis was carried out.[Result] Five eukaryotic expressing vectors of antibacterial peptides from Mytilus coruscus were successfully constructed,and the results of mRNA detection revealed that the five antibacterial peptides from Mytilus coruscus were successfully transcribed.[Conclusion] The results provide a basis for using genetic engineering to express antibacterial peptides of mytilin and myticin from Mytilus coruscus,and for developing the further study of antibacterial peptides from Mytilus coruscus based on this.
基金funded by the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture under Grant GJZJ20220802。
文摘Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.
文摘Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cotton delta-12 oleate desat- urase gene GhFAD2-1 containing an open reading frame of 1 158 bp was cloned for constructing RNAi vector. A 515 bp long specific fragment of this gene was se- lected for constructing ihpRNA vector under the control of a seed-specific promoter NAPIN, named pFGC1008-NAPIN-FAD2-1; meanwhile miRNA gene-silencing vector pCAMBIA1302-amiRNA-FAD2-1 targeting GhFAD2-1 was also constructed.
基金Supported by Research Fund of the Doctoral Program of Higher Education (200805720004)Scientific Research Foundation for Returned Scholars, Ministry of Education of China ([2009]1001)~~
文摘[Objective] To construct prokaryotic expression vectors encoding gene Erb3binding protein （EBP1）, which plays important roles in regulating plant organ size from Nervilia fordii （Hance） Schltr. [Methods] PCR products of NfEBP1 with particular restriction sites and expression vectors, pET-28 and pET-16b were digested. Ligation, transformation and selection were performed to construct the recombinant plasmids pET-28-NfEBP1 and pET-16-NfEBP1. The recombinant plasmids were transformed into E. coli BL21 using heat -shock transformation. [Results] Recombinant plasmids pET-28-NfEBP1-1188 and pET-16-NfEBP1-1188 were constructed and transformed into expressional host cells, E. coli BL21, and validated by colony PCR, sequencing and double digestion. [Conclusion] Prokaryotic expression vectors of EBP1 gene from N. fordii were successfully constructed, which laid the foundation for characterization of the gene function.
基金supported by National Natural Science Foundation of China(12374358,91950207)Guangdong Basic and Applied Basic Research Foundation(2024A1515010420).
文摘Glucose molecules are of great significance being one of the most important molecules in metabolic chain.However,due to the small Raman scattering cross-section and weak/non-adsorption on bare metals,accurately obtaining their"fingerprint information"remains a huge obstacle.Herein,we developed a tip-enhanced Raman scattering(TERS)technique to address this challenge.Adopting an optical fiber radial vector mode internally illuminates the plasmonic fiber tip to effectively suppress the background noise while generating a strong electric-field enhanced tip hotspot.Furthermore,the tip hotspot approaching the glucose molecules was manipulated via the shear-force feedback to provide more freedom for selecting substrates.Consequently,our TERS technique achieves the visualization of all Raman modes of glucose molecules within spectral window of 400-3200 cm^(-1),which is not achievable through the far-field/surface-enhanced Raman,or the existing TERS techniques.Our TERS technique offers a powerful tool for accurately identifying Raman scattering of molecules,paving the way for biomolecular analysis.
基金primarily supported by the National Key R&D Program of China[grant number 2021YFC3000904]the Jiangsu Provincial Key Technology R&D Program[grant number BE2022851]National Natural Science Foundation of China[grant number 42405035]。
文摘Vector winds play a crucial role in weather and climate,as well as the effective utilization of wind energy resources.However,limited research has been conducted on treating the wind field as a vector field in the evaluation of numerical weather prediction models.In this study,the authors treat vector winds as a whole by employing a vector field evaluation method,and evaluate the mesoscale model of the China Meteorological Administration(CMA-MESO)and ECMWF forecast,with reference to ERA5 reanalysis,in terms of multiple aspects of vector winds over eastern China in 2022.The results show that the ECMWF forecast is superior to CMA-MESO in predicting the spatial distribution and intensity of 10-m vector winds.Both models overestimate the wind speed in East China,and CMA-MESO overestimates the wind speed to a greater extent.The forecasting skill of the vector wind field in both models decreases with increasing lead time.The forecasting skill of CMA-MESO fluctuates more and decreases faster than that of the ECMWF forecast.There is a significant negative correlation between the model vector wind forecasting skill and terrain height.This study provides a scientific evaluation of the local application of vector wind forecasts of the CMA-MESO model and ECMWF forecast.
文摘Diagnosing cardiac diseases relies heavily on electrocardiogram(ECG)analysis,but detecting myocardial infarction-related arrhythmias remains challenging due to irregular heartbeats and signal variations.Despite advancements in machine learning,achieving both high accuracy and low computational cost for arrhythmia classification remains a critical issue.Computer-aided diagnosis systems can play a key role in early detection,reducing mortality rates associated with cardiac disorders.This study proposes a fully automated approach for ECG arrhythmia classification using deep learning and machine learning techniques to improve diagnostic accuracy while minimizing processing time.The methodology consists of three stages:1)preprocessing,where ECG signals undergo noise reduction and feature extraction;2)feature Identification,where deep convolutional neural network(CNN)blocks,combined with data augmentation and transfer learning,extract key parameters;3)classification,where a hybrid CNN-SVM model is employed for arrhythmia recognition.CNN-extracted features were fed into a binary support vector machine(SVM)classifier,and model performance was assessed using five-fold cross-validation.Experimental findings demonstrated that the CNN2 model achieved 85.52%accuracy,while the hybrid CNN2-SVM approach significantly improved accuracy to 97.33%,outperforming conventional methods.This model enhances classification efficiency while reducing computational complexity.The proposed approach bridges the gap between accuracy and processing speed in ECG arrhythmia classification,offering a promising solution for real-time clinical applications.Its superior performance compared to nonlinear classifiers highlights its potential for improving automated cardiac diagnosis.
基金the National Key Research and Development Program of China(2021YFC2900300)the Natural Science Foundation of Guangdong Province(2024A1515030216)+2 种基金MOST Special Fund from State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202437)the Guangdong Province Introduced of Innovative R&D Team(2021ZT09H399)the Third Xinjiang Scientific Expedition Program(2022xjkk1301).
文摘The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.
基金supported by the National Natural Science Foundation of China(Grant No.42177164)the Distinguished Youth Science Foundation of Hunan Province of China(Grant No.2022JJ10073)the Outstanding Youth Project of Hunan Provincial Department of Education,China(Grant No.23B0008).
文摘In underground mining,especially in entry-type excavations,the instability of surrounding rock structures can lead to incalculable losses.As a crucial tool for stability analysis in entry-type excavations,the critical span graph must be updated to meet more stringent engineering requirements.Given this,this study introduces the support vector machine(SVM),along with multiple ensemble(bagging,adaptive boosting,and stacking)and optimization(Harris hawks optimization(HHO),cuckoo search(CS))techniques,to overcome the limitations of the traditional methods.The analysis indicates that the hybrid model combining SVM,bagging,and CS strategies has a good prediction performance,and its test accuracy reaches 0.86.Furthermore,the partition scheme of the critical span graph is adjusted based on the CS-BSVM model and 399 cases.Compared with previous empirical or semi-empirical methods,the new model overcomes the interference of subjective factors and possesses higher interpretability.Since relying solely on one technology cannot ensure prediction credibility,this study further introduces genetic programming(GP)and kriging interpolation techniques.The explicit expressions derived through GP can offer the stability probability value,and the kriging technique can provide interpolated definitions for two new subclasses.Finally,a prediction platform is developed based on the above three approaches,which can rapidly provide engineering feedback.
基金supported by the National Key R&D Program of China(Grant2022YFF0503700)the National Natural Science Foundation of China(42474200 and 42174186)。
文摘The Macao Science Satellite-1(known as MSS-1)is the first scientific exploration satellite that was designed to measure the Earth's low latitude magnetic field at high resolution and with high precision by collecting data in a near-equatorial orbit.Magnetic field data from MSS-1's onboard Vector Fluxgate Magnetometer(VFM),collected at a sample rate of 50 Hz,allows us to detect and investigate sources of magnetic data contamination,from DC to relevant Nyquist frequency.Here we report two types of artificial disturbances in the VFM data.One is V-shaped events concentrated at night,with frequencies sweeping from the Nyquist frequency down to zero and back up.The other is 5-Hz events(ones that exhibit a distinct 5 Hz spectrum peak);these events are always accompanied by intervals of spiky signals,and are clearly related to the attitude control of the satellite.Our analyses show that VFM noise levels in daytime are systematically lower than in nighttime.The daily average noise levels exhibit a period of about 52 days.The V-shaped events are strongly correlated with higher VFM noise levels.
