Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emp...Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.展开更多
App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While t...App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.展开更多
BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features ...BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.展开更多
Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NP...Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.展开更多
The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of cha...The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of characteristics,appearing both elegant and noble on the outside,while concealing a deep inner loneliness and conflict.His attitude toward love and his dissatisfaction with society make him a dramatic and profound character in the story.By analyzing the character of Lensky,we can explore his role in the novel and his relationships with other characters.Lensky’s presence not only enriches the plot but also presents a figure filled with inner contradictions and emotional struggles.His friendship and rivalry with Eugene Onegin,as well as his admiration and helplessness in regard to Olga,showcase his complex inner world and reflections on life.Furthermore,the character of Lensky carries a certain symbolic significance.He can be seen as a metaphor for Russian society and culture at the time.His loneliness and inner conflict symbolize the limitations of Russian society and culture,while also reflecting Pushkin’s idealized pursuit of love and friendship,as well as his critical view of reality.In conclusion,through a deep analysis of Lensky’s character,we can better understand the portrayal of characters and the development of the plot in Eugene Onegin.It also provides readers with a perspective on Pushkin’s thoughts and observations on human nature,society,and culture.展开更多
The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of int...The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of interlayer barriers affecting the formation of oil and gas reservoirs and controlling oil-water distribution, this study proposes precise classification and quantitative identification of interlayer barriers in the study area based on a fully connected neural network combined with grey relational analysis. Taking the second member of the Sangonghe Formation (J1S22) in the Moxizhuang Oilfield as an example, combined with previous research, this study statistically analyzes the lithology and logging response characteristics of three types of interlayer barriers in the study area. Based on differences in composition, lithology, and genesis, interlayer barrier types are classified. Sensitive logging data such as natural gamma, acoustic time difference, and resistivity are selected through crossover plots. Grey relational analysis is used to calculate comprehensive discrimination indicators for interlayer barriers. Combined with the fully connected neural network method, an interlayer barrier identification model is established, and model training is conducted to verify the accuracy of interlayer barrier identification. The results indicate that the interlayer barrier identification model based on a fully connected neural network can rapidly and accurately identify interlayer barriers and their types. Its application in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin has proven that the identification results of this method for interlayer barriers have a conformity rate exceeding 90% with core data, demonstrating excellent performance in interlayer barrier identification and proving the effectiveness of the model for interlayer barrier identification and prediction in this area. The research conclusions can provide theoretical guidance and technical reference for the identification and evaluation of interlayer barriers in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin.展开更多
While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensificati...While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.展开更多
Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to...Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing literature.The shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the pipeline.In this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a clamp.While the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively captured.Then,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy equation.Based on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)algorithm.This study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.展开更多
In order to analysis the oxygen distribution in the adsorption bed during the hydrogen purification process from oxygen-containing feed gas and the safety of device operation, this article established a non-isothermal...In order to analysis the oxygen distribution in the adsorption bed during the hydrogen purification process from oxygen-containing feed gas and the safety of device operation, this article established a non-isothermal model for the pressure swing adsorption (PSA) separation process of 4-component (H_(2)/O_(2)/N_(2)/CH_(4)), and adopted a composite adsorption bed of activated carbon and molecular sieve. In this article, the oxygen distribution in the adsorption bed under different feed gas oxygen contents, different adsorption pressures, and different product hydrogen purity was studied for both vacuuming process and purging process. The study shows that during the process from the end of adsorption to the end of providing purging, the peak value of oxygen concentration in the adsorption bed gradually increases, with the highest value exceeding 30 times the oxygen content of the feed gas. Moreover, the concentration multiplier of oxygen in the adsorption bed increases with the increase of the adsorption pressure, decreases with the increase of the oxygen content in the feed gas, and increases with the decrease of the hydrogen product purity. When the oxygen content in the feed gas reaches 0.3% (vol), the peak value of oxygen concentration in the adsorption bed exceeds 10% (vol), which will make the front part of the oxygen concentration peak fall in an explosion limit range. As the decrease of product hydrogen content, the oxygen concentration peak in the adsorption bed will gradually move forward to the adsorption bed outlet, and even penetrate through the adsorption bed. And during the process of the oxygen concentration peak moving forward, the oxygen will enter the pipeline at the outlet of the adsorption bed, which will make the pipeline space of high-speed gas flow into an explosion range, bringing great risk to the device. The preferred option for safe operation of PSA for hydrogen purification from oxygen-containing feed gas is to deoxygenate the feed gas. When deoxygenation is not available, a lower adsorption pressure and a higher product hydrogen purity (greater than or equal to 99.9% (vol)) can be used to avoid the gas in the adsorption bed outlet pipeline being in the explosion range.展开更多
Derris fordii and Derris elliptica belong to the Derris genus of the Fabaceae family, distinguished by their high isoflavonoid content, particularly rotenoids, which hold significance in pharmaceuticals and agricultur...Derris fordii and Derris elliptica belong to the Derris genus of the Fabaceae family, distinguished by their high isoflavonoid content, particularly rotenoids, which hold significance in pharmaceuticals and agriculture. Rotenone, as a prominent rotenoid, has a longstanding history of use in pesticides, veterinary applications, medicine, and medical research. The accumulation of rotenoids within Derris plants adheres to species-specific and tissue-specific patterns and is also influenced by environmental factors. Current research predominantly addresses extraction techniques, pharmacological applications, and pesticide formulations, whereas investigations into the biosynthesis pathway and regulatory mechanism of rotenoids remain relatively scarce. In this study, we observed notable differences in rotenone content across the roots, stems, and leaves of D. fordii, as well as within the roots of D. elliptica. Utilizing RNA sequencing (RNA-seq), we analyzed the transcriptomes and expression profiles of unigenes from these four tissues, identifying a total of 121,576 unigenes. Differentially expressed genes (DEGs) across four comparison groups demonstrated significant enrichment in the phenylpropanoid and flavonoid biosynthesis pathways. Key unigenes implicated in the rotenoid biosynthesis pathway were identified, with PAL, C4H, CHS, CHI, IFS, and HI4OMT playing critical roles in D. fordii, while IFS and HI4OMT were determined to be essential for rotenoid biosynthesis in D. elliptica. These findings enhance our understanding of the biosynthesis mechanism of rotenoids in Derris species. The unigenes identified in this study represent promising candidates for future investigations aimed at validating their roles in rotenoid biosynthesis.展开更多
In the context of the continuous advancement of teaching reform,the optimization of the curriculum evaluation system has become a key issue in the field of education.This study focuses on the course of educational psy...In the context of the continuous advancement of teaching reform,the optimization of the curriculum evaluation system has become a key issue in the field of education.This study focuses on the course of educational psychology,using the final examination papers and scores of the 2022 Physical Education Major and 2024 Early Childhood Education Major undergraduate students at Yunnan Technology and Business University as samples.Basic statistical analysis methods are employed to conduct an in-depth investigation.The results show that the overall difficulty of the exam papers is moderate(0.7),with acceptable reliability(0.78)and good validity(0.7-0.8).However,the failure rate among students reaches 21.3%,reflecting learning difficulties.There is no significant difference in scores between students from different majors,attributed to the same teaching conditions and equal emphasis on the course by both majors.This study provides data support for the teaching of educational psychology courses,assisting teachers in improving their teaching based on the results,meeting the demands of teaching reform for precise teaching evaluation and quality enhancement,and promoting the development of educational psychology course teaching.展开更多
Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.Th...Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.展开更多
The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for...The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.展开更多
The longitudinal cracks distributed along the dam axis in the corridor of a dam may have potential safety hazards.According to the detection results of crack depth and width and the analysis of monitoring data,a three...The longitudinal cracks distributed along the dam axis in the corridor of a dam may have potential safety hazards.According to the detection results of crack depth and width and the analysis of monitoring data,a three-dimensional finite element model is established for numerical simulation calculation and the influence of cracks on the safety of dam structure is analyzed from different aspects such as deformation,stress value,and distribution range.The calculation results show that the maximum principal tensile stress value and the location of the dam body are basically independent of the change of crack depth(within 1.0 m).Regarding local stress around the corridor,the high upstream water level causes cracks to deepen,resulting in an increase in the maximum tensile stress near the crack tip and an expansion of the tensile stress region.展开更多
By analyzing the successful case of meteorological support services for the navigation ceremony of Langzhong Airport,the practice experience,existing problems and future improvement directions of aviation meteorologic...By analyzing the successful case of meteorological support services for the navigation ceremony of Langzhong Airport,the practice experience,existing problems and future improvement directions of aviation meteorological support services were analyzed and summarized to provide reference for the airport and its subsequent aviation meteorological support services in the future.展开更多
Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to p...Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.展开更多
Biomedical big data,characterized by its massive scale,multi-dimensionality,and heterogeneity,offers novel perspectives for disease research,elucidates biological principles,and simultaneously prompts changes in relat...Biomedical big data,characterized by its massive scale,multi-dimensionality,and heterogeneity,offers novel perspectives for disease research,elucidates biological principles,and simultaneously prompts changes in related research methodologies.Biomedical ontology,as a shared formal conceptual system,not only offers standardized terms for multi-source biomedical data but also provides a solid data foundation and framework for biomedical research.In this review,we summarize enrichment analysis and deep learning for biomedical ontology based on its structure and semantic annotation properties,highlighting how technological advancements are enabling the more comprehensive use of ontology information.Enrichment analysis represents an important application of ontology to elucidate the potential biological significance for a particular molecular list.Deep learning,on the other hand,represents an increasingly powerful analytical tool that can be more widely combined with ontology for analysis and prediction.With the continuous evolution of big data technologies,the integration of these technologies with biomedical ontologies is opening up exciting new possibilities for advancing biomedical research.展开更多
[Objectives]This study was conducted to analyze the medication laws of traditional Chinese medicine prescriptions for the treatment of spleen-deficiency irritable bowel syndrome in Guanling Autonomous County Hospital ...[Objectives]This study was conducted to analyze the medication laws of traditional Chinese medicine prescriptions for the treatment of spleen-deficiency irritable bowel syndrome in Guanling Autonomous County Hospital of Traditional Chinese Medicine.[Methods]Prescriptions for the treatment of spleen-deficiency irritable bowel syndrome(IBS)were retrieved from the TCM family of the hospital,traditional Chinese medical doctor Wu Zhongli,in the period from November 2023 to April 2024.Microsoft Excel 2007 was employed to set up an information table of TCM prescriptions,and the age,gender,herbal properties,efficacy categories and the frequency of use were analyzed to explore the medication laws of TCM in the hospital for the treatment of spleen-deficiency irritable bowel syndrome.[Results]Among the 259 TCM prescriptions included,152 kinds of TCM decoction pieces were used.The decoction pieces were mainly warm in nature,and decoction pieces cold in nature took the second place.The flavors of the herbs were mostly sweet,bitter and pungent.Most of them were attributive to the spleen,stomach meridian and lung meridians,and the herbs were mainly used for tonifying deficiency and regulating qi.The herbs with higher frequency of use included Radix Glycyrrhiza,Pericarpium Citri Reticulatae,poria,and Angelicae Sinensis Radix,the main effects of which are replenishing qi to invigorate the spleen,activating qi and eliminating phlegm,clearing damp and promoting diuresis,and relaxing bowel.[Conclusions]Chinese medicine treatment of IBS with spleen deficiency in hospitals is mainly based on replenishing qi to invigorate the spleen,activating qi and eliminating phlegm,clearing damp and promoting diuresis,and relaxing bowel,and Xiangsha Liujunzi Decoction is commonly used in clinical treatment based on syndrome differentiation with modifications.展开更多
The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates...The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates its importance as a statistical method that helps researchers understand relationships between variables and make predictions based on data. The inclusion of multiple disciplines, such as health sciences, social sciences, environmental studies, economics, engineering, clinical psychology, social psychology, developmental psychology, cognitive psychology, and education highlights the interdisciplinary relevance of regression analysis. This breadth suggests that the findings and methodologies discussed in the paper may have wide applications, benefiting various sectors by enhancing the quality of research outcomes. The mention of “methodologies and data analysis techniques” indicates that the paper will likely delve into specific statistical approaches, offering a comprehensive examination of how regression analysis is applied in real-world scenarios. This nuance is essential, as it demonstrates the research’s commitment to not only presenting theoretical insights but also practical applications. Furthermore, the abstract states that regression analysis “enhances the validity of findings” and “informs data-driven decision-making.” This assertion underlines the critical role that robust statistical methods play in ensuring that research conclusions are reliable and applicable. The ability of regression analysis to provide clarity and support informed decisions makes it a valuable tool in both academic and professional settings. The abstract effectively outlines the paper’s exploration of regression analysis in various fields, underscoring its importance in enhancing research validity and facilitating informed decision-making. The interdisciplinary nature of the research broadens its appeal and emphasizes the need for rigorous statistical approaches in addressing complex issues across different domains.展开更多
Reconfigurable intelligent surface(RIS)is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic waves.In the prior literature,the...Reconfigurable intelligent surface(RIS)is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic waves.In the prior literature,the inter-RIS links which also contribute to the performance of the whole system are usually neglected when multiple RISs are deployed.In this paper we investigate a general double-RIS assisted multiple-input multiple-output(MIMO)wireless communication system under spatially correlated non line-of-sight propagation channels,where the cooperation of the double RISs is also considered.The design objective is to maximize the achievable ergodic rate based on full statistical channel state information(CSI).Specifically,we firstly present a closedform asymptotic expression for the achievable ergodic rate by utilizing replica method from statistical physics.Then a full statistical CSI-enabled optimal design is proposed which avoids high pilot training overhead compared to instantaneous CSI-enabled design.To further reduce the signal processing overhead and lower the complexity for practical realization,a common-phase scheme is proposed to design the double RISs.Simulation results show that the derived asymptotic ergodic rate is quite accurate even for small-sized antenna arrays.And the proposed optimization algorithm can achieve substantial gain at the expense of a low overhead and complexity.Furthermore,the cooperative double-RIS assisted MIMO framework is proven to achieve superior ergodic rate performance and high communication reliability under harsh propagation environment.展开更多
文摘Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.
基金supported by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant no.(GPIP:13-612-2024).
文摘App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.
文摘BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.
基金National Natural Science Foundation of China under Grant Nos.52208191 and 51908397Shanxi Province Science Foundation for Youths under Grant No.201901D211025China Postdoctoral Science Foundation under Grant No.2020M670695。
文摘Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.
文摘The character of Lensky in Eugene Onegin is one of the most discussed figures in the novel.He is the friend of Eugene Onegin and represents a contradictory personality.In the novel,Lensky displays a complex set of characteristics,appearing both elegant and noble on the outside,while concealing a deep inner loneliness and conflict.His attitude toward love and his dissatisfaction with society make him a dramatic and profound character in the story.By analyzing the character of Lensky,we can explore his role in the novel and his relationships with other characters.Lensky’s presence not only enriches the plot but also presents a figure filled with inner contradictions and emotional struggles.His friendship and rivalry with Eugene Onegin,as well as his admiration and helplessness in regard to Olga,showcase his complex inner world and reflections on life.Furthermore,the character of Lensky carries a certain symbolic significance.He can be seen as a metaphor for Russian society and culture at the time.His loneliness and inner conflict symbolize the limitations of Russian society and culture,while also reflecting Pushkin’s idealized pursuit of love and friendship,as well as his critical view of reality.In conclusion,through a deep analysis of Lensky’s character,we can better understand the portrayal of characters and the development of the plot in Eugene Onegin.It also provides readers with a perspective on Pushkin’s thoughts and observations on human nature,society,and culture.
文摘The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of interlayer barriers affecting the formation of oil and gas reservoirs and controlling oil-water distribution, this study proposes precise classification and quantitative identification of interlayer barriers in the study area based on a fully connected neural network combined with grey relational analysis. Taking the second member of the Sangonghe Formation (J1S22) in the Moxizhuang Oilfield as an example, combined with previous research, this study statistically analyzes the lithology and logging response characteristics of three types of interlayer barriers in the study area. Based on differences in composition, lithology, and genesis, interlayer barrier types are classified. Sensitive logging data such as natural gamma, acoustic time difference, and resistivity are selected through crossover plots. Grey relational analysis is used to calculate comprehensive discrimination indicators for interlayer barriers. Combined with the fully connected neural network method, an interlayer barrier identification model is established, and model training is conducted to verify the accuracy of interlayer barrier identification. The results indicate that the interlayer barrier identification model based on a fully connected neural network can rapidly and accurately identify interlayer barriers and their types. Its application in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin has proven that the identification results of this method for interlayer barriers have a conformity rate exceeding 90% with core data, demonstrating excellent performance in interlayer barrier identification and proving the effectiveness of the model for interlayer barrier identification and prediction in this area. The research conclusions can provide theoretical guidance and technical reference for the identification and evaluation of interlayer barriers in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin.
基金supported by the National Natural Science Foundation of China[grant numbers 42192553 and 41922036]the Fundamental Research Funds for the Central Universities–Cemac“GeoX”Interdisciplinary Program[grant number 020714380207]。
文摘While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.
基金Project supported by the National Science and Technology Major Project(No.J2019-I-0008-0008)the National Natural Science Foundation of China(No.52305096)the Chinese Postdoctoral Science Foundation(No.GZB20230117)。
文摘Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing literature.The shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the pipeline.In this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a clamp.While the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively captured.Then,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy equation.Based on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)algorithm.This study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.
基金support provided by the Sichuan Province Science and Technology Achievement Transformation Project(2023ZHCG0063)which was essential for the successful completion of this research。
文摘In order to analysis the oxygen distribution in the adsorption bed during the hydrogen purification process from oxygen-containing feed gas and the safety of device operation, this article established a non-isothermal model for the pressure swing adsorption (PSA) separation process of 4-component (H_(2)/O_(2)/N_(2)/CH_(4)), and adopted a composite adsorption bed of activated carbon and molecular sieve. In this article, the oxygen distribution in the adsorption bed under different feed gas oxygen contents, different adsorption pressures, and different product hydrogen purity was studied for both vacuuming process and purging process. The study shows that during the process from the end of adsorption to the end of providing purging, the peak value of oxygen concentration in the adsorption bed gradually increases, with the highest value exceeding 30 times the oxygen content of the feed gas. Moreover, the concentration multiplier of oxygen in the adsorption bed increases with the increase of the adsorption pressure, decreases with the increase of the oxygen content in the feed gas, and increases with the decrease of the hydrogen product purity. When the oxygen content in the feed gas reaches 0.3% (vol), the peak value of oxygen concentration in the adsorption bed exceeds 10% (vol), which will make the front part of the oxygen concentration peak fall in an explosion limit range. As the decrease of product hydrogen content, the oxygen concentration peak in the adsorption bed will gradually move forward to the adsorption bed outlet, and even penetrate through the adsorption bed. And during the process of the oxygen concentration peak moving forward, the oxygen will enter the pipeline at the outlet of the adsorption bed, which will make the pipeline space of high-speed gas flow into an explosion range, bringing great risk to the device. The preferred option for safe operation of PSA for hydrogen purification from oxygen-containing feed gas is to deoxygenate the feed gas. When deoxygenation is not available, a lower adsorption pressure and a higher product hydrogen purity (greater than or equal to 99.9% (vol)) can be used to avoid the gas in the adsorption bed outlet pipeline being in the explosion range.
基金Guangxi Science and Technology Base and Talent Special Fund,Project No.AD21220130Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain,Project No.20-065-7Guangxi Institute of Botany Fund,Project No.21014.
文摘Derris fordii and Derris elliptica belong to the Derris genus of the Fabaceae family, distinguished by their high isoflavonoid content, particularly rotenoids, which hold significance in pharmaceuticals and agriculture. Rotenone, as a prominent rotenoid, has a longstanding history of use in pesticides, veterinary applications, medicine, and medical research. The accumulation of rotenoids within Derris plants adheres to species-specific and tissue-specific patterns and is also influenced by environmental factors. Current research predominantly addresses extraction techniques, pharmacological applications, and pesticide formulations, whereas investigations into the biosynthesis pathway and regulatory mechanism of rotenoids remain relatively scarce. In this study, we observed notable differences in rotenone content across the roots, stems, and leaves of D. fordii, as well as within the roots of D. elliptica. Utilizing RNA sequencing (RNA-seq), we analyzed the transcriptomes and expression profiles of unigenes from these four tissues, identifying a total of 121,576 unigenes. Differentially expressed genes (DEGs) across four comparison groups demonstrated significant enrichment in the phenylpropanoid and flavonoid biosynthesis pathways. Key unigenes implicated in the rotenoid biosynthesis pathway were identified, with PAL, C4H, CHS, CHI, IFS, and HI4OMT playing critical roles in D. fordii, while IFS and HI4OMT were determined to be essential for rotenoid biosynthesis in D. elliptica. These findings enhance our understanding of the biosynthesis mechanism of rotenoids in Derris species. The unigenes identified in this study represent promising candidates for future investigations aimed at validating their roles in rotenoid biosynthesis.
文摘In the context of the continuous advancement of teaching reform,the optimization of the curriculum evaluation system has become a key issue in the field of education.This study focuses on the course of educational psychology,using the final examination papers and scores of the 2022 Physical Education Major and 2024 Early Childhood Education Major undergraduate students at Yunnan Technology and Business University as samples.Basic statistical analysis methods are employed to conduct an in-depth investigation.The results show that the overall difficulty of the exam papers is moderate(0.7),with acceptable reliability(0.78)and good validity(0.7-0.8).However,the failure rate among students reaches 21.3%,reflecting learning difficulties.There is no significant difference in scores between students from different majors,attributed to the same teaching conditions and equal emphasis on the course by both majors.This study provides data support for the teaching of educational psychology courses,assisting teachers in improving their teaching based on the results,meeting the demands of teaching reform for precise teaching evaluation and quality enhancement,and promoting the development of educational psychology course teaching.
基金financially supported by National Natural Science Foundation of China (Nos.62305392 and 62305123)Independent Research and Development Project of Naval Engineering University (No.2023504050)the Nursery Plan Project of Navel University of Engineering (2022)。
文摘Optimization and simplification of optical systems represent a milestone in advancing the development of handheld and portable laser-induced breakdown spectroscopy(LIBS)systems towards smaller,more integrated forms.This research,for the first time,conducted a comprehensive optimization design and comparative analysis of three compact LIBS system optical paths:the paraxial optical path(OP),the off-axis OP,and the reflective OP.The differences in spectral intensity and stability among these paths were revealed,providing a scientific basis for selecting the optimal OP for LIBS systems.The research found that the paraxial OP excels in spectral performance and quantitative analysis accuracy,making it the preferred choice for compact LIBS systems.Specifically,the paraxial OP significantly enhances spectral intensity,achieving a 6 times improvement over the off-axis OP and an even more remarkable 150 times increase compared to the reflective OP,greatly enhancing detection sensitivity.Additionally,the relative standard deviation,spectral stability index,maintains a consistently low level,ranging from 10.9%to 13.4%,significantly outperforming the other two OPs and ensuring the reliability of analytical results.In the field of quantitative analysis,the paraxial OP also demonstrates higher accuracy,precision,and sensitivity,comparing to other OPs.The quantitative analysis models for Si,Cu,and Ti elements exhibit excellent fitting,providing users with high-quality quantitative analysis results that are of great significance for applications in material science,environmental monitoring,industrial inspection,and other fields.In summary,this study not only confirms the enormous application potential of the paraxial OP in compact LIBS systems but also provides valuable practical experience and theoretical support for the miniaturization and integration of LIBS systems.Looking ahead,with continuous technological advancements,the design of the paraxial OP is expected to further propel the widespread adoption of LIBS technology in portable,on-site detection applications.
基金funded by the INTER program and cofunded by the Fond National de la Recherche,Luxembourg(FNR)and the Fund for Scientific Research-FNRS,Belgium(F.R.S-FNRS),T.0233.20-‘Sustainable Residential Densification’project(SusDens,2020–2024).
文摘The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.
基金Zhejiang Provincial Natural Science Foundation of China for Young Scholars(Project No.:LQ20A020009)National College Students’Innovation and Entrepreneurship Training Program(Project No.:202311842014X)。
文摘The longitudinal cracks distributed along the dam axis in the corridor of a dam may have potential safety hazards.According to the detection results of crack depth and width and the analysis of monitoring data,a three-dimensional finite element model is established for numerical simulation calculation and the influence of cracks on the safety of dam structure is analyzed from different aspects such as deformation,stress value,and distribution range.The calculation results show that the maximum principal tensile stress value and the location of the dam body are basically independent of the change of crack depth(within 1.0 m).Regarding local stress around the corridor,the high upstream water level causes cracks to deepen,resulting in an increase in the maximum tensile stress near the crack tip and an expansion of the tensile stress region.
文摘By analyzing the successful case of meteorological support services for the navigation ceremony of Langzhong Airport,the practice experience,existing problems and future improvement directions of aviation meteorological support services were analyzed and summarized to provide reference for the airport and its subsequent aviation meteorological support services in the future.
基金supported by the Specific Research Fund for Top-notch Talents of Guangdong Provincial Hospital of Chinese Medicine(No.2022KT1188).
文摘Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.
基金supported by the National Natural Science Foundation of China(61902095).
文摘Biomedical big data,characterized by its massive scale,multi-dimensionality,and heterogeneity,offers novel perspectives for disease research,elucidates biological principles,and simultaneously prompts changes in related research methodologies.Biomedical ontology,as a shared formal conceptual system,not only offers standardized terms for multi-source biomedical data but also provides a solid data foundation and framework for biomedical research.In this review,we summarize enrichment analysis and deep learning for biomedical ontology based on its structure and semantic annotation properties,highlighting how technological advancements are enabling the more comprehensive use of ontology information.Enrichment analysis represents an important application of ontology to elucidate the potential biological significance for a particular molecular list.Deep learning,on the other hand,represents an increasingly powerful analytical tool that can be more widely combined with ontology for analysis and prediction.With the continuous evolution of big data technologies,the integration of these technologies with biomedical ontologies is opening up exciting new possibilities for advancing biomedical research.
文摘[Objectives]This study was conducted to analyze the medication laws of traditional Chinese medicine prescriptions for the treatment of spleen-deficiency irritable bowel syndrome in Guanling Autonomous County Hospital of Traditional Chinese Medicine.[Methods]Prescriptions for the treatment of spleen-deficiency irritable bowel syndrome(IBS)were retrieved from the TCM family of the hospital,traditional Chinese medical doctor Wu Zhongli,in the period from November 2023 to April 2024.Microsoft Excel 2007 was employed to set up an information table of TCM prescriptions,and the age,gender,herbal properties,efficacy categories and the frequency of use were analyzed to explore the medication laws of TCM in the hospital for the treatment of spleen-deficiency irritable bowel syndrome.[Results]Among the 259 TCM prescriptions included,152 kinds of TCM decoction pieces were used.The decoction pieces were mainly warm in nature,and decoction pieces cold in nature took the second place.The flavors of the herbs were mostly sweet,bitter and pungent.Most of them were attributive to the spleen,stomach meridian and lung meridians,and the herbs were mainly used for tonifying deficiency and regulating qi.The herbs with higher frequency of use included Radix Glycyrrhiza,Pericarpium Citri Reticulatae,poria,and Angelicae Sinensis Radix,the main effects of which are replenishing qi to invigorate the spleen,activating qi and eliminating phlegm,clearing damp and promoting diuresis,and relaxing bowel.[Conclusions]Chinese medicine treatment of IBS with spleen deficiency in hospitals is mainly based on replenishing qi to invigorate the spleen,activating qi and eliminating phlegm,clearing damp and promoting diuresis,and relaxing bowel,and Xiangsha Liujunzi Decoction is commonly used in clinical treatment based on syndrome differentiation with modifications.
文摘The abstract provided offers a succinct overview of the research paper’s focus on the significance of statistics, specifically regression analysis, across diverse fields. The emphasis on regression analysis indicates its importance as a statistical method that helps researchers understand relationships between variables and make predictions based on data. The inclusion of multiple disciplines, such as health sciences, social sciences, environmental studies, economics, engineering, clinical psychology, social psychology, developmental psychology, cognitive psychology, and education highlights the interdisciplinary relevance of regression analysis. This breadth suggests that the findings and methodologies discussed in the paper may have wide applications, benefiting various sectors by enhancing the quality of research outcomes. The mention of “methodologies and data analysis techniques” indicates that the paper will likely delve into specific statistical approaches, offering a comprehensive examination of how regression analysis is applied in real-world scenarios. This nuance is essential, as it demonstrates the research’s commitment to not only presenting theoretical insights but also practical applications. Furthermore, the abstract states that regression analysis “enhances the validity of findings” and “informs data-driven decision-making.” This assertion underlines the critical role that robust statistical methods play in ensuring that research conclusions are reliable and applicable. The ability of regression analysis to provide clarity and support informed decisions makes it a valuable tool in both academic and professional settings. The abstract effectively outlines the paper’s exploration of regression analysis in various fields, underscoring its importance in enhancing research validity and facilitating informed decision-making. The interdisciplinary nature of the research broadens its appeal and emphasizes the need for rigorous statistical approaches in addressing complex issues across different domains.
基金supported in part by the Xi’an Jiaotong-Liverpool University(XJTLU)Research Development Fund(2024–2027)under Grant RDF-23-02-010supported in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515110732+5 种基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62071247supported in part by the Science and Technology Development Fund,Macao,China SAR under Grants 0087/2022/AFJ and 001/2024/SKLin part by the National Natural Science Foundation of China under Grant 62261160650in part by the Research Committee of University of Macao,Macao SAR,China under Grants MYRG-GRG2023-00116-FST-UMDF and MYRG2020-00095-FSTsupported in part by the NSFC under Grant 62261160576 and 62301148in part by the Fundamental Research Funds for the Central Universities under Grant 2242023K5003.
文摘Reconfigurable intelligent surface(RIS)is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic waves.In the prior literature,the inter-RIS links which also contribute to the performance of the whole system are usually neglected when multiple RISs are deployed.In this paper we investigate a general double-RIS assisted multiple-input multiple-output(MIMO)wireless communication system under spatially correlated non line-of-sight propagation channels,where the cooperation of the double RISs is also considered.The design objective is to maximize the achievable ergodic rate based on full statistical channel state information(CSI).Specifically,we firstly present a closedform asymptotic expression for the achievable ergodic rate by utilizing replica method from statistical physics.Then a full statistical CSI-enabled optimal design is proposed which avoids high pilot training overhead compared to instantaneous CSI-enabled design.To further reduce the signal processing overhead and lower the complexity for practical realization,a common-phase scheme is proposed to design the double RISs.Simulation results show that the derived asymptotic ergodic rate is quite accurate even for small-sized antenna arrays.And the proposed optimization algorithm can achieve substantial gain at the expense of a low overhead and complexity.Furthermore,the cooperative double-RIS assisted MIMO framework is proven to achieve superior ergodic rate performance and high communication reliability under harsh propagation environment.
