There is substantial individual variation in the growth rates of sea cucumber Apostiehopus japonicus individuals. This necessitates additional work to grade the seed stock and lengthens the production period. We evalu...There is substantial individual variation in the growth rates of sea cucumber Apostiehopus japonicus individuals. This necessitates additional work to grade the seed stock and lengthens the production period. We evaluated the influence of three culture methods （free-mixed, isolated-mixed, isolated-alone） on individual variation in growth and assessed the relationship between feeding, energy conversion efficiency, and individual growth variation in individually cultured sea cucumbers. Of the different culture methods, animals grew best when reared in the isolated-mixed treatment （i.e., size classes were held separately）, though there was no difference in individual variation in growth between rearing treatment groups. The individual variation in growth was primarily attributed to genetic factors. The difference in food conversion efficiency caused by genetic differences among individuals was thought to be the origin of the variance. The level of individual growth variation may be altered by interactions among individuals and environmental heterogeneity. Our results suggest that, in addition to traditional seed grading, design of a new kind of substrate that changes the spatial distribution of sea cucumbers would effectively enhance growth and reduce individual variation in growth of sea cucumbers in culture.展开更多
There is a close relationship between individual spontaneous behavior and Industrial design. As individual spontaneous behavior can sent especial meaning for industrial design, there is a great necessity for creating ...There is a close relationship between individual spontaneous behavior and Industrial design. As individual spontaneous behavior can sent especial meaning for industrial design, there is a great necessity for creating design guided by this behavior. The design method carries out in four steps, first step is to focus on the analysis of individual action phase, pay attention to the explora- tion of the relationship between actions and tool ,and then list the importance order in the action phase, the third step is to take out the in-depth anatomical analysis of the stage, analyze the reason of the operational difficulty .and at last carries out the design concept to resolve the problem. All in all, this method revolves around the main stage of spontaneous behavior, and analyzes it in interim and solves the problem in stage.展开更多
In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firs...In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.展开更多
Requirements for research assessments There are huge differences in mission, emphasis, inherent capability, and targeted utilization of research among scientific institutions. Hence, when it comes to assessments, a on...Requirements for research assessments There are huge differences in mission, emphasis, inherent capability, and targeted utilization of research among scientific institutions. Hence, when it comes to assessments, a one-size-fits-all approach cannot meet the goal(s) of these assessments. Probably even larger differences exist between individuals, research teams and departments.展开更多
There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning met...There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning methods,which can locate and identify different objects,but boundary identifications are not accurate enough.Both of them cannot generate entire segmentation information.In order to obtain accurate edge detection and semantic information,an Adaptive Boundary and Semantic Composite Segmentation method(ABSCS)is proposed.This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances.It includes adaptively dividing and modifying the aerial images with the proposed principles and methods,using the deep learning method to semantic segment and preprocess the small divided pieces,using three traditional methods to segment and preprocess original-size aerial images,adaptively selecting traditional results tomodify the boundaries of individual objects in deep learning results,and combining the results of different objects.Individual object semantic segmentation experiments are conducted by using the AeroScapes dataset,and their results are analyzed qualitatively and quantitatively.The experimental results demonstrate that the proposed method can achieve more promising object boundaries than the original deep learning method.This work also demonstrates the advantages of the proposed method in applications of point cloud semantic segmentation and image inpainting.展开更多
Objectives:This study examined the hypothesis that whether any significant differences exist or not in individual temperament and somatotype components in young athletes.Methods:The cross-sectional study was carried o...Objectives:This study examined the hypothesis that whether any significant differences exist or not in individual temperament and somatotype components in young athletes.Methods:The cross-sectional study was carried out with 202 male athletes(age=23 years±2.7,mean±SE).They were categorized into four groups according to their temperaments by using a questionnaire.Also,the Heath-Carter method was applied to estimate the somatotype components.One-Way ANOVA followed by Scheffe’s tests was organized(p<0.05)for data analysis.Results:In this research,the highest mesomorphy,ectomorphy and endomorphy components were observed in the Blood,Yellow Bile and Phlegm temperaments,respectively with means of 6.1±0.28,3.9±0.11,and 5.9±0.32.Also,a significant difference was observed between Blood temperament and mesomorphy component(p<0.001)but Blood temperament had insignificant differences with other studied somatotype components(p>0.05).Ectomorphy and mesomorphy components significantly differ among Yellow Bile temperament(p<0.05),while an insignificant difference was found between Yellow Bile temperament and endomorphy component(p>0.05).Significant differences also were showed between Black Bile temperament and all somatotype components(p<0.05).Among Phlegm temperament and endomorphy component was a significant difference(p<0.001),but there were no significant differences between the Phlegm temperament and the other two somatotype components(p>0.05).Conclusions:Given the importance of body type in sports performance,current findings suggest that coaches should be aware of the individual temperaments which could serve as a guide to design special training schedules for athletes.展开更多
The studies show that numerous complex networks have clustering effect.It is an indispensable step to identify node clusters in network,namely community,in which nodes are closely related,and in many applications such...The studies show that numerous complex networks have clustering effect.It is an indispensable step to identify node clusters in network,namely community,in which nodes are closely related,and in many applications such as identification of ringleaders in anti-criminal and anti-terrorist network,efficient storage of data in Wireless Sensor Network(WSN).At present,most of community identification methods still require the specifications of the number or the scale of community by user and still can not handle overlapping nodes.In an attempt to solve these problems,a network community identification method based on utility value is proposed,which is a function of each node's clustering coefficient and degree.This method makes use of individual-centered theory for reference and can automatically determine the number of communities.In addition,this method is an overlapping community identification method in nature.It is shown through contrastive experiments that this method is more efficient than other methods based on individual-centered theory when they control the same amount of information.Finally,a research direction is proposed for network community identification method based on the individual-centered theory.展开更多
Objective:To explore the application effect of video assessment method in clinical nurses’nursing operation skills.Method:To select 58 nurses who participated in the individual soldier standard in the children’s hos...Objective:To explore the application effect of video assessment method in clinical nurses’nursing operation skills.Method:To select 58 nurses who participated in the individual soldier standard in the children’s hospital in 2019 and 2020 as the research objects,among which the nurses who participated in the individual soldier standard in 2019 were the nurses who participated in the individual soldier standard in 2019 and 2020.A total of 29 people in the first batch were set as the control group,using traditional assessment methods.In 2020,the second batch of 29 nurses who participated in the individual soldier standard reached the experimental group.Using the video assessment method,there was no significant difference in general information between the two groups(P>0.05).After the assessment,the scores,coping with work pressure,and proactiveness of the two groups of research subjects were compared.Results:The experimental group’s nursing operation assessment scores,coping with work pressure,and proactiveness were significantly better than those of the control group,the difference was statistically significant(P<0.05).Conclusion:The application of the video assessment method improves the passing rate of nurses’operational skills examination,enhances nurses’initiative in learning,reduces examination pressure,and can be accurately,timely,and safely applied to clinical nursing work,which is worthy of study and promotion.展开更多
Research on nutrigenomics has accumulated sufficient data in the past two decades that have dem on strated phe no types of single n ucleotide polymorphisms (SNPs) betwee n healthy and micronutrient-deficient populatio...Research on nutrigenomics has accumulated sufficient data in the past two decades that have dem on strated phe no types of single n ucleotide polymorphisms (SNPs) betwee n healthy and micronutrient-deficient populations. For instance, Zhang et al. showed that the genes MTHFR C677T, MTRR A66G, and MTR A2756G were the genetic factors resp on sible for low absorptio n and bioavailability of vitamins such as folate, B6/ and B12. It has also been reported that these nutrients are closely associated with the prevale nee of neural tube defects in newborn infants。展开更多
The physiological markers of 310 individuals aged 2 through 19 were evaluated for the effects of the Masgutova Neurosensorimotor Reflex Integration Method on their four body systems: respiratory, cardiovascular, diges...The physiological markers of 310 individuals aged 2 through 19 were evaluated for the effects of the Masgutova Neurosensorimotor Reflex Integration Method on their four body systems: respiratory, cardiovascular, digestive, and nervous systems of individuals with neurodevelopmental deficits—cerebral palsy (CP), seizures, traumatic and acute brain injury, attention deficit and hyperactive disorders (ADD, ADHD), autism spectrum disorders, anxiety, post-trauma and post-traumatic stress disorders. We found that 53.33% of physiological markers and 66.67% of reflex patterns on the pre-test demonstrated to be poorly functioning. Both evaluation results showed statistically significant improvements after 8-days of intensive training using the Masgutova Neurosensorimotor Reflex Integration Method. Improvements according to 60.0% of the physiological markers positively correlated with functionality gains in 77.5% of reflex patterns in all four study groups compared to the control group, which did not receive the Reflex Integration training program (p-value < 0.05). The magnitude of improvement depended upon the severity of symptoms indicating the essentiality for individualized training in accordance with the diagnosis and individual neurological deficits. Results of this study show that reflex integrative techniques can lead to a reduction of stress and other negative factors blocking health homeostasis, limiting perception, and causing dysregulation in behavior and emotions, especially following traumatic events. Positive changes in physiological markers and reflex pattern functions indicate potential benefits for survival and stress resiliency through supporting neuro-physiological and neuro-psychological aspects of overall health and well-being in individuals with neurological deficits.展开更多
Introduction: The MNRI (Masgutova Neurosensorimotor Reflex Integration) method was developed in 1989 in Russia and has spread world-wide to treat individuals with certain types reflex development deficits, behavior di...Introduction: The MNRI (Masgutova Neurosensorimotor Reflex Integration) method was developed in 1989 in Russia and has spread world-wide to treat individuals with certain types reflex development deficits, behavior disorders, disorders of speech or language development, and learning disabilities. MNRI is based on techniques called “repatterning” or remodulation, meaning re-education, recoding the reflex nerve pathways specific for dynamic and postural reflex schemes. Objectives: Repatterning activates the extra pyramidal nervous system responsible for automatic mechanisms and processes, the extension of links between neurons, the growth of neural nets, myelination, and the creation of new nerve routing. This potential result was tested utilizing urinary measurements of the following neurotransmitters: epinephrine, norepinephrine, dopamine, DOPAC, serotonin, 5-HIAA, glycine, taurine, GABA, glutamate, PEA, and histamine. Methods: Neurological impact of the Masgutova Neurosensorimotor Reflex Method on the magnitude of changes in neurotransmitters was assessed by an external controlled and double-blind method using patients from one of the four diagnosis groups: 1) global developmental disorders;2) cerebral palsy, Traumatic Brain Injury (TBI), Acute Brain Injury (ABI), and seizures;3) ADD/ADHD;and 4) anxiety disorders. Results: The post-MNRI results in participants show a tendency for regulation of the above neurotransmitters resulting in their calming down, decrease of hypervigilance, stress resilience increase, improvements in behavioral and emotional regulation, positive emotions, and cognitive processes control. Conclusion: The application of the Masgutova Neurosensorimotor Reflex Method as a therapy modality offers a novelty paradigm for the treatment using neuro- and immune-modulation technologies presenting a non-pharmaceutical approach, based on use of neurosensorimotor reflex circuit concept.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ...Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.展开更多
In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least s...In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least squares(IMLS)method,which enhances the efficiency and stability of the numerical solution.The numerical solution formulas are derived using the improved element-free Galerkin(IEFG)method.We introduce the solid isotropic microstructures with penalization(SIMP)model to formulate a mathematical model for topology opti-mization,which effectively penalizes intermediate densities.The optimization problem is defined with the numerical solution formula and volume fraction as constraints.The objective function,which is the minimum value of flexibility,is optimized iteratively using the optimization criterion method to update the design variables efficiently and converge to an optimal solution.Sensitivity analysis is performed using the adjoint method,which provides accurate and efficient gradient information for the optimization algorithm.We validate the proposed framework through a series of numerical examples,including clamped beam,cantilever beam,and simply supported beam made of orthotropic materials.The convergence of the objective function is demonstrated by increasing the number of iterations.Additionally,the stability of the iterative process is analyzed by examining the fluctuation law of the volume fraction.By adjusting the parameters to an appropriate range,we achieve the final optimization results of the IEFG method without the checkerboard phenomenon.Comparative studies between the Element-Free Galerkin(EFG)and IEFG methods reveal that both methods yield consistent optimization results under identical parameter settings.However,the IEFG method significantly reduces computational time,highlighting its efficiency and suitability for orthotropic materials.展开更多
Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The t...Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.展开更多
Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performa...RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.展开更多
The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) metho...The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) method to address these limitations. In the vLEC method, the waverider is directly designed from the preassigned leading edge and the variable shock angle distribution based on the Leading-Edge Cone (LEC) concept. Since the vLEC method is an approximate method, two test waveriders are designed and evaluated using numerical simulations to validate the shock design accuracy and the effectiveness of the vLEC method. The results show that the shocks of the test waveriders coincide well with the preassigned positions. Furthermore, four specifically designed application cases are conducted to analyze the performance benefits of the vLEC waveriders. The results of these cases indicate that, due to their variable shock angle distributions, the vLEC waveriders exhibit higher lift-to-drag ratios and better longitudinal static stability than conventional waveriders. Additionally, the vLEC waveriders demonstrate superior volumetric capacities near the symmetry plane, albeit with a minor decrease in volumetric efficiency.展开更多
基金Supported by the National Natural Science Foundation of China(No.41106134)the National Marine Public Welfare Research Project of China(No.201305043)+1 种基金the National High Technology Research and Development Program of China(863 Program)(No.2012AA10A412)the Agriculture Science Technology Achievement Transformation Fund(No.2012GB24910656)
文摘There is substantial individual variation in the growth rates of sea cucumber Apostiehopus japonicus individuals. This necessitates additional work to grade the seed stock and lengthens the production period. We evaluated the influence of three culture methods （free-mixed, isolated-mixed, isolated-alone） on individual variation in growth and assessed the relationship between feeding, energy conversion efficiency, and individual growth variation in individually cultured sea cucumbers. Of the different culture methods, animals grew best when reared in the isolated-mixed treatment （i.e., size classes were held separately）, though there was no difference in individual variation in growth between rearing treatment groups. The individual variation in growth was primarily attributed to genetic factors. The difference in food conversion efficiency caused by genetic differences among individuals was thought to be the origin of the variance. The level of individual growth variation may be altered by interactions among individuals and environmental heterogeneity. Our results suggest that, in addition to traditional seed grading, design of a new kind of substrate that changes the spatial distribution of sea cucumbers would effectively enhance growth and reduce individual variation in growth of sea cucumbers in culture.
文摘There is a close relationship between individual spontaneous behavior and Industrial design. As individual spontaneous behavior can sent especial meaning for industrial design, there is a great necessity for creating design guided by this behavior. The design method carries out in four steps, first step is to focus on the analysis of individual action phase, pay attention to the explora- tion of the relationship between actions and tool ,and then list the importance order in the action phase, the third step is to take out the in-depth anatomical analysis of the stage, analyze the reason of the operational difficulty .and at last carries out the design concept to resolve the problem. All in all, this method revolves around the main stage of spontaneous behavior, and analyzes it in interim and solves the problem in stage.
基金Sponsored by the Nation Nature Science Foundation of China(Grant No.61201237,61301095)the Nature Science Foundation of Heilongjiang Province of China(Grant No.QC2012C069)the Fundamental Research Funds for the Central Universities(Grant No.HEUCFZ1129,HEUCF130817,HEUCF130810)
文摘In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.
文摘Requirements for research assessments There are huge differences in mission, emphasis, inherent capability, and targeted utilization of research among scientific institutions. Hence, when it comes to assessments, a one-size-fits-all approach cannot meet the goal(s) of these assessments. Probably even larger differences exist between individuals, research teams and departments.
基金funded in part by the Equipment Pre-Research Foundation of China,Grant No.61400010203in part by the Independent Project of the State Key Laboratory of Virtual Reality Technology and Systems.
文摘There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning methods,which can locate and identify different objects,but boundary identifications are not accurate enough.Both of them cannot generate entire segmentation information.In order to obtain accurate edge detection and semantic information,an Adaptive Boundary and Semantic Composite Segmentation method(ABSCS)is proposed.This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances.It includes adaptively dividing and modifying the aerial images with the proposed principles and methods,using the deep learning method to semantic segment and preprocess the small divided pieces,using three traditional methods to segment and preprocess original-size aerial images,adaptively selecting traditional results tomodify the boundaries of individual objects in deep learning results,and combining the results of different objects.Individual object semantic segmentation experiments are conducted by using the AeroScapes dataset,and their results are analyzed qualitatively and quantitatively.The experimental results demonstrate that the proposed method can achieve more promising object boundaries than the original deep learning method.This work also demonstrates the advantages of the proposed method in applications of point cloud semantic segmentation and image inpainting.
文摘Objectives:This study examined the hypothesis that whether any significant differences exist or not in individual temperament and somatotype components in young athletes.Methods:The cross-sectional study was carried out with 202 male athletes(age=23 years±2.7,mean±SE).They were categorized into four groups according to their temperaments by using a questionnaire.Also,the Heath-Carter method was applied to estimate the somatotype components.One-Way ANOVA followed by Scheffe’s tests was organized(p<0.05)for data analysis.Results:In this research,the highest mesomorphy,ectomorphy and endomorphy components were observed in the Blood,Yellow Bile and Phlegm temperaments,respectively with means of 6.1±0.28,3.9±0.11,and 5.9±0.32.Also,a significant difference was observed between Blood temperament and mesomorphy component(p<0.001)but Blood temperament had insignificant differences with other studied somatotype components(p>0.05).Ectomorphy and mesomorphy components significantly differ among Yellow Bile temperament(p<0.05),while an insignificant difference was found between Yellow Bile temperament and endomorphy component(p>0.05).Significant differences also were showed between Black Bile temperament and all somatotype components(p<0.05).Among Phlegm temperament and endomorphy component was a significant difference(p<0.001),but there were no significant differences between the Phlegm temperament and the other two somatotype components(p>0.05).Conclusions:Given the importance of body type in sports performance,current findings suggest that coaches should be aware of the individual temperaments which could serve as a guide to design special training schedules for athletes.
基金Sponsored by the National Natural Science Foundation of China (Grant No. 61073041,60873037,61100008 and 61073043)the Natural Science Foundation of Heilongjiang Province (Grant No. F200901 and F201023 )+1 种基金the Harbin Special Funds for Technological Innovation Research (Grant No.2010RFXXG002 and 2011RFXXG015)the Fundamental Research Funds for the Central Universities of China(Grant No. HEUCF100602)
文摘The studies show that numerous complex networks have clustering effect.It is an indispensable step to identify node clusters in network,namely community,in which nodes are closely related,and in many applications such as identification of ringleaders in anti-criminal and anti-terrorist network,efficient storage of data in Wireless Sensor Network(WSN).At present,most of community identification methods still require the specifications of the number or the scale of community by user and still can not handle overlapping nodes.In an attempt to solve these problems,a network community identification method based on utility value is proposed,which is a function of each node's clustering coefficient and degree.This method makes use of individual-centered theory for reference and can automatically determine the number of communities.In addition,this method is an overlapping community identification method in nature.It is shown through contrastive experiments that this method is more efficient than other methods based on individual-centered theory when they control the same amount of information.Finally,a research direction is proposed for network community identification method based on the individual-centered theory.
文摘Objective:To explore the application effect of video assessment method in clinical nurses’nursing operation skills.Method:To select 58 nurses who participated in the individual soldier standard in the children’s hospital in 2019 and 2020 as the research objects,among which the nurses who participated in the individual soldier standard in 2019 were the nurses who participated in the individual soldier standard in 2019 and 2020.A total of 29 people in the first batch were set as the control group,using traditional assessment methods.In 2020,the second batch of 29 nurses who participated in the individual soldier standard reached the experimental group.Using the video assessment method,there was no significant difference in general information between the two groups(P>0.05).After the assessment,the scores,coping with work pressure,and proactiveness of the two groups of research subjects were compared.Results:The experimental group’s nursing operation assessment scores,coping with work pressure,and proactiveness were significantly better than those of the control group,the difference was statistically significant(P<0.05).Conclusion:The application of the video assessment method improves the passing rate of nurses’operational skills examination,enhances nurses’initiative in learning,reduces examination pressure,and can be accurately,timely,and safely applied to clinical nursing work,which is worthy of study and promotion.
基金supported by Rural compulsory education student nutrition improvement plan-student nutrition and health condition in-depth monitoring and evaluation project [2016-019]
文摘Research on nutrigenomics has accumulated sufficient data in the past two decades that have dem on strated phe no types of single n ucleotide polymorphisms (SNPs) betwee n healthy and micronutrient-deficient populations. For instance, Zhang et al. showed that the genes MTHFR C677T, MTRR A66G, and MTR A2756G were the genetic factors resp on sible for low absorptio n and bioavailability of vitamins such as folate, B6/ and B12. It has also been reported that these nutrients are closely associated with the prevale nee of neural tube defects in newborn infants。
文摘The physiological markers of 310 individuals aged 2 through 19 were evaluated for the effects of the Masgutova Neurosensorimotor Reflex Integration Method on their four body systems: respiratory, cardiovascular, digestive, and nervous systems of individuals with neurodevelopmental deficits—cerebral palsy (CP), seizures, traumatic and acute brain injury, attention deficit and hyperactive disorders (ADD, ADHD), autism spectrum disorders, anxiety, post-trauma and post-traumatic stress disorders. We found that 53.33% of physiological markers and 66.67% of reflex patterns on the pre-test demonstrated to be poorly functioning. Both evaluation results showed statistically significant improvements after 8-days of intensive training using the Masgutova Neurosensorimotor Reflex Integration Method. Improvements according to 60.0% of the physiological markers positively correlated with functionality gains in 77.5% of reflex patterns in all four study groups compared to the control group, which did not receive the Reflex Integration training program (p-value < 0.05). The magnitude of improvement depended upon the severity of symptoms indicating the essentiality for individualized training in accordance with the diagnosis and individual neurological deficits. Results of this study show that reflex integrative techniques can lead to a reduction of stress and other negative factors blocking health homeostasis, limiting perception, and causing dysregulation in behavior and emotions, especially following traumatic events. Positive changes in physiological markers and reflex pattern functions indicate potential benefits for survival and stress resiliency through supporting neuro-physiological and neuro-psychological aspects of overall health and well-being in individuals with neurological deficits.
文摘Introduction: The MNRI (Masgutova Neurosensorimotor Reflex Integration) method was developed in 1989 in Russia and has spread world-wide to treat individuals with certain types reflex development deficits, behavior disorders, disorders of speech or language development, and learning disabilities. MNRI is based on techniques called “repatterning” or remodulation, meaning re-education, recoding the reflex nerve pathways specific for dynamic and postural reflex schemes. Objectives: Repatterning activates the extra pyramidal nervous system responsible for automatic mechanisms and processes, the extension of links between neurons, the growth of neural nets, myelination, and the creation of new nerve routing. This potential result was tested utilizing urinary measurements of the following neurotransmitters: epinephrine, norepinephrine, dopamine, DOPAC, serotonin, 5-HIAA, glycine, taurine, GABA, glutamate, PEA, and histamine. Methods: Neurological impact of the Masgutova Neurosensorimotor Reflex Method on the magnitude of changes in neurotransmitters was assessed by an external controlled and double-blind method using patients from one of the four diagnosis groups: 1) global developmental disorders;2) cerebral palsy, Traumatic Brain Injury (TBI), Acute Brain Injury (ABI), and seizures;3) ADD/ADHD;and 4) anxiety disorders. Results: The post-MNRI results in participants show a tendency for regulation of the above neurotransmitters resulting in their calming down, decrease of hypervigilance, stress resilience increase, improvements in behavioral and emotional regulation, positive emotions, and cognitive processes control. Conclusion: The application of the Masgutova Neurosensorimotor Reflex Method as a therapy modality offers a novelty paradigm for the treatment using neuro- and immune-modulation technologies presenting a non-pharmaceutical approach, based on use of neurosensorimotor reflex circuit concept.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金Supported by Xuhui District Health Commission,No.SHXH202214.
文摘Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.
基金supported by the Graduate Student Scientific Research Innovation Project through Research Innovation Fund for Graduate Students in Shanxi Province(Project No.2024KY648).
文摘In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least squares(IMLS)method,which enhances the efficiency and stability of the numerical solution.The numerical solution formulas are derived using the improved element-free Galerkin(IEFG)method.We introduce the solid isotropic microstructures with penalization(SIMP)model to formulate a mathematical model for topology opti-mization,which effectively penalizes intermediate densities.The optimization problem is defined with the numerical solution formula and volume fraction as constraints.The objective function,which is the minimum value of flexibility,is optimized iteratively using the optimization criterion method to update the design variables efficiently and converge to an optimal solution.Sensitivity analysis is performed using the adjoint method,which provides accurate and efficient gradient information for the optimization algorithm.We validate the proposed framework through a series of numerical examples,including clamped beam,cantilever beam,and simply supported beam made of orthotropic materials.The convergence of the objective function is demonstrated by increasing the number of iterations.Additionally,the stability of the iterative process is analyzed by examining the fluctuation law of the volume fraction.By adjusting the parameters to an appropriate range,we achieve the final optimization results of the IEFG method without the checkerboard phenomenon.Comparative studies between the Element-Free Galerkin(EFG)and IEFG methods reveal that both methods yield consistent optimization results under identical parameter settings.However,the IEFG method significantly reduces computational time,highlighting its efficiency and suitability for orthotropic materials.
基金Supported by the National Natural Science Foundation of China under Grant No.51975138the High-Tech Ship Scientific Research Project from the Ministry of Industry and Information Technology under Grant No.CJ05N20the National Defense Basic Research Project under Grant No.JCKY2023604C006.
文摘Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金supported by grants from the National Science Foundation of China(Grant Nos.12375038 and 12075171 to ZJT,and 12205223 to YLT).
文摘RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.
基金supported by grants from the National Natural Science Foundation of China(No.U20B2006)the Guangdong Basic and Applied Basic Research Foundation(No.2022A1515110145)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2022QNRC001).
文摘The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) method to address these limitations. In the vLEC method, the waverider is directly designed from the preassigned leading edge and the variable shock angle distribution based on the Leading-Edge Cone (LEC) concept. Since the vLEC method is an approximate method, two test waveriders are designed and evaluated using numerical simulations to validate the shock design accuracy and the effectiveness of the vLEC method. The results show that the shocks of the test waveriders coincide well with the preassigned positions. Furthermore, four specifically designed application cases are conducted to analyze the performance benefits of the vLEC waveriders. The results of these cases indicate that, due to their variable shock angle distributions, the vLEC waveriders exhibit higher lift-to-drag ratios and better longitudinal static stability than conventional waveriders. Additionally, the vLEC waveriders demonstrate superior volumetric capacities near the symmetry plane, albeit with a minor decrease in volumetric efficiency.
