基于Visual MODFLOW的某加油站苯系物迁移预测

加油站作为石油气等燃料的重要储存场所,开展其地下水污染预测报告,对水环境污染防治具有重要意义。本文利用多元综合数据,建立目标加油站的Visual MODFLOW地下水数值模型,通过设置污染物泄露情景,对模型进行数值模拟和溶质运移模拟。结果表明:瞬时泄露第100天时,形成影响面积28484.9m^(2),最远迁移距离为114.4m,模型区中心最大污染物浓度为0.008mg/L;瞬时泄露第1000天时,形成影响面积35123.3m^(2),最远迁移距离为186.2m,模型区的最大污染浓度为0.005mg/L。持续泄露第100天时,模型区附近部分区域地下水中苯浓度超过Ⅲ类水限制浓度,形成超标区域17208.3m^(2),形成影响面积48035.2m^(2),污染晕最远边界距离模型区中心位置为183.1m,污染羽最远边界距离中心位置为91.2m;持续泄露第1000天时,污染晕最远边界距离模型区中心位置为291.7m,污染羽最远边界距离中心位置为210.3m,形成超标区域21686.8m^(2),形成影响面积74610.2m^(2)。泄露物中的苯系物对地下水体的污染较难恢复,通过模型的模拟预测,可为加油站站点及周边范围的水污染防治问题提供参考。

Women in visual neural regeneration research

The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).

A Concise and Varied Visual Features-Based Image Captioning Model with Visual Selection

Image captioning has gained increasing attention in recent years.Visual characteristics found in input images play a crucial role in generating high-quality captions.Prior studies have used visual attention mechanisms to dynamically focus on localized regions of the input image,improving the effectiveness of identifying relevant image regions at each step of caption generation.However,providing image captioning models with the capability of selecting the most relevant visual features from the input image and attending to them can significantly improve the utilization of these features.Consequently,this leads to enhanced captioning network performance.In light of this,we present an image captioning framework that efficiently exploits the extracted representations of the image.Our framework comprises three key components:the Visual Feature Detector module(VFD),the Visual Feature Visual Attention module(VFVA),and the language model.The VFD module is responsible for detecting a subset of the most pertinent features from the local visual features,creating an updated visual features matrix.Subsequently,the VFVA directs its attention to the visual features matrix generated by the VFD,resulting in an updated context vector employed by the language model to generate an informative description.Integrating the VFD and VFVA modules introduces an additional layer of processing for the visual features,thereby contributing to enhancing the image captioning model’s performance.Using the MS-COCO dataset,our experiments show that the proposed framework competes well with state-of-the-art methods,effectively leveraging visual representations to improve performance.The implementation code can be found here:https://github.com/althobhani/VFDICM(accessed on 30 July 2024).

Effect of capsule treatment on visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataract

BACKGROUND Cataracts pose a significant clinical burden due to their complex pathogenesis.In recent years,an increase in cataracts coexisting with myopia has heightened the incidence of retinopathy and posterior vitreous detachment.Additionally,symptoms of ocular axis elongation,lens nucleus hardening,and vitreous liquefaction have become more prevalent.While conventional extracapsular cataract extraction is commonly employed,it often yields suboptimal visual outcomes.Subsequent advancements in cataract phacoemulsification and lens implantation surgeries have gained widespread acceptance for their ability to improve refraction and significantly improve uncorrected visual acuity.AIM To investigate the effect of capsular treatment after phacoemulsification lens implantation in myopic patients with cataract.METHODS We selected 110 patients(with 134 eyes)with myopia and cataracts treated.These patients were categorized into two groups:an observation group(57 patients with 70 eyes)and a control group(53 patients with 64 eyes).The control group underwent cataract phacoemulsification and lens implantation,while the observation group received a refined capsular treatment based on the control group’s procedure.We assessed the differences in visual acuity and quality between the two groups before and after surgery.RESULTS At six months post-operation,the observation group exhibited significantly improved far vision,intermediate vision,near vision,lower objective scattering index,higher Modulation transfer function cut-off frequency,and overall vision metrics at different contrast levels(100%,20%and 9%)compared to the control group(P<0.05).The total score of the National Eye Institute Visual Function Questionnaire in the observation group at 6 months after operation was significantly higher than that in the control group(P<0.05).No significant difference in the incidence of adverse reactions was observed between the observation group and control group(P>0.05).CONCLUSION Capsular treatment demonstrates efficacy in improving visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataracts,warranting its clinical application.

Application of Landscape Engineering based on BIM Visualization Technology

The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and management tool that integrates digitization and visualization,has demonstrated considerable advantages in enhancing project quality,reducing costs,and improving collaborative efficiency.This study aims to systematically investigate the application and developmental trends of BIM visualization technology within the field of landscape engineering.Through an analysis of technological advancements and industry dynamics over the past decade,it has been observed that BIM visualization technology is intricately linked with green building practices,sustainable construction methods,and the development of smart cities within the context of landscape engineering projects.The technology also possesses significant potential for application in the planning and design of landscape engineering,construction management,and project maintenance.The convenience of visualization enhances the expressive capacity of the design scheme,improves communication efficiency between the involved parties,and mitigates the costs and time inefficiencies associated with design modifications.By drawing on the successful experiences of other industries and integrating them with the unique characteristics of landscape engineering,BIM visualization technology is poised to assume a more significant role within this field.This integration is expected to advance the entire industry towards greater intelligence and informatization,while simultaneously enhancing the efficiency and quality of design,construction,and maintenance processes.

A survey of fine-grained visual categorization based on deep learning

Deep learning has achieved excellent results in various tasks in the field of computer vision,especially in fine-grained visual categorization.It aims to distinguish the subordinate categories of the label-level categories.Due to high intra-class variances and high inter-class similarity,the fine-grained visual categorization is extremely challenging.This paper first briefly introduces and analyzes the related public datasets.After that,some of the latest methods are reviewed.Based on the feature types,the feature processing methods,and the overall structure used in the model,we divide them into three types of methods:methods based on general convolutional neural network(CNN)and strong supervision of parts,methods based on single feature processing,and meth-ods based on multiple feature processing.Most methods of the first type have a relatively simple structure,which is the result of the initial research.The methods of the other two types include models that have special structures and training processes,which are helpful to obtain discriminative features.We conduct a specific analysis on several methods with high accuracy on pub-lic datasets.In addition,we support that the focus of the future research is to solve the demand of existing methods for the large amount of the data and the computing power.In terms of tech-nology,the extraction of the subtle feature information with the burgeoning vision transformer(ViT)network is also an important research direction.

集成PHAST-Visual Studio的岩溶区燃气管道灾害后果定量分析及应用

为科学评估岩溶区燃气管道灾害的后果影响程度,基于管道失效特征确定喷射火和蒸气云爆炸两种典型后果模式,研判适用于岩溶区燃气管道灾害的热辐射和冲击波超压危害准则,从危害面积、伤亡人数、经济损失、环境破坏4个维度提出岩溶区燃气管道灾害后果严重程度的评估模型体系,并结合Visual Studio平台开发“岩溶区燃气管道灾害后果分析软件”。立足岩溶区实际工程案例,结合区域经济社会发展、岩溶自然地质以及燃气管道工程特征,基于PHAST软件仿真分析灾害后果的影响范围,结合危害准则对区内人员、物体提出针对性灾害风险管控措施,并通过引入政府、行业、企业等颁布的标准条例,量化得出灾害后果的影响程度。结果表明:提出的PHAST-Visual Studio集成方法能够弥补以往研究的评估主观性问题,将社会科学思想带入工程风险评价研究,并通过计算机软件编程提高灾害后果分析效率,从而有助于显著控制岩溶区燃气管道灾害后果水平。

Data Visualization in Big Data Analysis: Applications and Future Trends

The advent of the big data era has made data visualization a crucial tool for enhancing the efficiency and insights of data analysis. This theoretical research delves into the current applications and potential future trends of data visualization in big data analysis. The article first systematically reviews the theoretical foundations and technological evolution of data visualization, and thoroughly analyzes the challenges faced by visualization in the big data environment, such as massive data processing, real-time visualization requirements, and multi-dimensional data display. Through extensive literature research, it explores innovative application cases and theoretical models of data visualization in multiple fields including business intelligence, scientific research, and public decision-making. The study reveals that interactive visualization, real-time visualization, and immersive visualization technologies may become the main directions for future development and analyzes the potential of these technologies in enhancing user experience and data comprehension. The paper also delves into the theoretical potential of artificial intelligence technology in enhancing data visualization capabilities, such as automated chart generation, intelligent recommendation of visualization schemes, and adaptive visualization interfaces. The research also focuses on the role of data visualization in promoting interdisciplinary collaboration and data democratization. Finally, the paper proposes theoretical suggestions for promoting data visualization technology innovation and application popularization, including strengthening visualization literacy education, developing standardized visualization frameworks, and promoting open-source sharing of visualization tools. This study provides a comprehensive theoretical perspective for understanding the importance of data visualization in the big data era and its future development directions.

Visual Representation and Cognitive Models in Information Visualization

As a branch of computer science,information visualization aims to help users understand and analyze complex data through graphical interfaces and interactive technologies.Information visualization primarily includes various visual structures such as time-series structures,spatial relationship structures,statistical distribution structures,and geographic map structures,each with unique functions and application scenarios.To better explain the cognitive process of visualization,researchers have proposed various cognitive models based on interaction mechanisms,visual perception steps,and novice use of visualization.These models help understand user cognition in information visualization,enhancing the effectiveness of data analysis and decision-making.

Visual Fortran基于Win32 DLL的混合编程技术

VisualFortran与VisualC++、VisualBasic、Delphi的混合编程,可将Fortran编制的数学模型融入到各种辅助决策综合信息系统中.其混合编程实现的途径为:在VisualFortran中,将执行计算的各种过程集成Win32DLL;在其它基于对象的语言中导入DLL,并对FortranDLL输出的过程实施调用.实现的关键是:在调用约定匹配的前提下,使VisualC++、VisualBasic、Delphi程序中声明的外部过程原型,与FortranDLL中的导出过程在目标过程名、参数类型及参数传递上保持一致.

Visual Modflow在和田县农业经济新区地下水资源评价中的应用

为全面了解地下水系统受各种激励因素影响后的水动力场和地下水量变化规律,以及为当地地下水资源开发与利用提供科学的指导意见,本次在和田县农业经济新区地下水资源评价中采用可视化标准软件Visnal Modflow实现地下水资源的模拟与预报,通过构建三维非稳定流数值模型,使用迭代方法求解,并根据设计开采量对地下水水位变动做出预测,再基于建模预测结果,结合经济新区地下水资源量确定合理的地下水开采量。

Visual Semantic Segmentation Based on Few/Zero-Shot Learning:An Overview

Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception.Conventional learning-based visual semantic segmentation approaches count heavily on largescale training data with dense annotations and consistently fail to estimate accurate semantic labels for unseen categories.This obstruction spurs a craze for studying visual semantic segmentation with the assistance of few/zero-shot learning.The emergence and rapid progress of few/zero-shot visual semantic segmentation make it possible to learn unseen categories from a few labeled or even zero-labeled samples,which advances the extension to practical applications.Therefore,this paper focuses on the recently published few/zero-shot visual semantic segmentation methods varying from 2D to 3D space and explores the commonalities and discrepancies of technical settlements under different segmentation circumstances.Specifically,the preliminaries on few/zeroshot visual semantic segmentation,including the problem definitions,typical datasets,and technical remedies,are briefly reviewed and discussed.Moreover,three typical instantiations are involved to uncover the interactions of few/zero-shot learning with visual semantic segmentation,including image semantic segmentation,video object segmentation,and 3D segmentation.Finally,the future challenges of few/zero-shot visual semantic segmentation are discussed.

Three-dimensional visualization technology for guiding one-step percutaneous transhepatic cholangioscopic lithotripsy for the treatment of complex hepatolithiasis

BACKGROUND Biliary stone disease is a highly prevalent condition and a leading cause of hospitalization worldwide.Hepatolithiasis with associated strictures has high residual and recurrence rates after traditional multisession percutaneous transhepatic cholangioscopic lithotripsy(PTCSL).AIM To study one-step PTCSL using the percutaneous transhepatic one-step biliary fistulation(PTOBF)technique guided by three-dimensional(3D)visualization.METHODS This was a retrospective,single-center study analyzing,140 patients who,between October 2016 and October 2023,underwent one-step PTCSL for hepatolithiasis.The patients were divided into two groups:The 3D-PTOBF group and the PTOBF group.Stone clearance on choledochoscopy,complications,and long-term clearance and recurrence rates were assessed.RESULTS Age,total bilirubin,direct bilirubin,Child-Pugh class,and stone location were similar between the 2 groups,but there was a significant difference in bile duct strictures,with biliary strictures more common in the 3D-PTOBF group(P=0.001).The median follow-up time was 55.0(55.0,512.0)days.The immediate stone clearance ratio(88.6%vs 27.1%,P=0.000)and stricture resolution ratio(97.1%vs 78.6%,P=0.001)in the 3D-PTOBF group were significantly greater than those in the PTOBF group.Postoperative complication(8.6%vs 41.4%,P=0.000)and stone recurrence rates(7.1%vs 38.6%,P=0.000)were significantly lower in the 3D-PTOBF group.CONCLUSION Three-dimensional visualization helps make one-step PTCSL a safe,effective,and promising treatment for patients with complicated primary hepatolithiasis.The perioperative and long-term outcomes are satisfactory for patients with complicated primary hepatolithiasis.This minimally invasive method has the potential to be used as a substitute for hepatobiliary surgery.

基于Visual MODFLOW模型的LID设施对地下水调蓄关系研究

海绵城市建设能够增加自然降水对地下水的回补,减少城市开发对自然环境的破坏。然而,现有研究多集中于单一或典型LID设施,缺乏对大尺度和长周期海绵城市建设对整体地下水水位变化影响的探讨。论文基于Visual MODFLOW模型模拟了LID设施建设前后的研究区地下水水位动态。结果显示,LID建设典型区埋深上升0~2 m,降水对潜水的补给量增加了1.83%。这表明LID设施在局部区域能够显著增强降水对地下水的回补,但对整体地下水位的动态影响不明显。

Recent progress in visualization and digitization of coherent transformation structures and application in high-strength steel

High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.

基于Visual MODFLOW大水矿山深部开采矿坑涌水量预测

矿产资源的不断开发导致矿坑涌、突水现象愈加频繁,此类问题多发生于大水矿山,为更好指导大水矿山深部开采工作,准确预测矿山深部开采矿坑涌水量至关重要。结合某矿区勘察资料、水文地质条件和观测井实测水位数据,利用Visual MODFLOW软件建立矿区水文地质数值模型,进行稳态与非稳态校正以及相关参数敏感性分析;根据该矿区-150 m水平矿坑真实涌水量拟合分析Drain模块水力传导系数值,运用识别后模型对矿山深部开采矿坑涌水量预测,结果表明-200、-250、-300、-350 m等不同水平矿坑正常涌水量为17209.82、18896.20、21299.31、23494.10 m^(3)/d,预测结果可为矿山防治水工作提供依据,以及为工程安全开挖提供保障。

Heterogeneous Image Knowledge Driven Visual Perception

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous images.Facing the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

The cardiovascular system at high altitude:A bibliometric and visualization analysis

BACKGROUND When exposed to high-altitude environments,the cardiovascular system undergoes various changes,the performance and mechanisms of which remain controversial.AIM To summarize the latest research advancements and hot research points in the cardiovascular system at high altitude by conducting a bibliometric and visualization analysis.METHODS The literature was systematically retrieved and filtered using the Web of Science Core Collection of Science Citation Index Expanded.A visualization analysis of the identified publications was conducted employing CiteSpace and VOSviewer.RESULTS A total of 1674 publications were included in the study,with an observed annual increase in the number of publications spanning from 1990 to 2022.The United States of America emerged as the predominant contributor,while Universidad Peruana Cayetano Heredia stood out as the institution with the highest publication output.Notably,Jean-Paul Richalet demonstrated the highest productivity among researchers focusing on the cardiovascular system at high altitude.Furthermore,Peter Bärtsch emerged as the author with the highest number of cited articles.Keyword analysis identified hypoxia,exercise,acclimatization,acute and chronic mountain sickness,pulmonary hypertension,metabolism,and echocardiography as the primary research hot research points and emerging directions in the study of the cardiovascular system at high altitude.CONCLUSION Over the past 32 years,research on the cardiovascular system in high-altitude regions has been steadily increasing.Future research in this field may focus on areas such as hypoxia adaptation,metabolism,and cardiopulmonary exercise.Strengthening interdisciplinary and multi-team collaborations will facilitate further exploration of the pathophysiological mechanisms underlying cardiovascular changes in high-altitude environments and provide a theoretical basis for standardized disease diagnosis and treatment.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.