Visualization Software Research Articles

Substandard and falsified antimicrobials in selected east African countries: A systematic review.

Globally, millions of people have been affected by fraudulent pharmaceutical products, particularly those in developing countries. Although the problem of falsified and substandard drugs is acknowledged, the extent of the issue is ever-changing, has a dynamic nature, and should be quantified and captured in a recent snapshot. This systematic review seeks to examine the data that can quantify and provide a current snapshot of the prevalence of SF antimicrobials in selected east Africa countries. Scientific studies on antimicrobial quality were searched in PubMed, Embase, Scopus, and Google Scholar from 2017 to February 2023. The search strategy focused on scientific articles published in peer-reviewed scientific journals written in English and the studies exclusively done in any of the selected countries of east Africa. The articles were carefully reviewed by two individuals for inclusion independently, first by title followed by abstract and the full-text retrieval. To minimize bias associated with the methodology used for data collection, the quality of the studies was assessed for quality according to the Medicine Quality Assessment Reporting Guidelines (MEDQUARG). The reporting of this systematic review was done following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). Fifteen studies that estimated the prevalence of poor-quality antimicrobial medicines in selected four east African countries were included. The overall percentage of samples of antimicrobials that failed at least one quality test was 22.6% (151/669) with each class's prevalence of 17% in antibiotics (73/432), 24% in antimalarial (41/171), and 56% in anthelmintics (37/66). Quality control parameters of API content were the most commonly examined in the included studies, accounting for 14/15 (93%) studies. Fifty (33.1%) of the failing samples failed assay API- content determination, while 26.5% (n = 40) failed the visual inspection and packaging analysis; 19.2% (29) failed dissolution; 14% (n = 21) flawed hardness or friability; 4%(n = 6) failed uniformity, as well as 3.2% (n = 5) failed disintegration test of the quality control parameter. It was found that this review was general in these selected east African countries and was a catalyst for combating the menace of poor-quality medications that affect millions of lives.

Integrated Visual Software Analytics on the GitHub Platform

Readily available software analysis and analytics tools are often operated within external services, where the measured software analysis data are kept internally and no external access to the data is available. We propose an approach to integrate visual software analysis on the GitHub platform by leveraging GitHub Actions and the GitHub API, covering both analysis and visualization. The process is to perform software analysis for each commit, e.g., static source code complexity metrics, and augment the commit using the resulting data, stored as git objects within the same repository. We show that this approach is feasible by integrating it into 64 open source TypeScript projects. Furthermore, we analyze the impact on Continuous Integration (CI) run time and repository storage. The stored software analysis data are externally accessible to allow for visualization tools, such as software maps. The effort to integrate our approach is limited to enabling the analysis component within a project’s CI on GitHub and embed an HTML snippet into the project’s website for visualization. This enables a large amount of projects to have access to software analysis as well as provide means to communicate the current status of a project.

Akulturasi Budaya dalam Desain Kemasan “Alingbao Bakpao Kekinian“

Alingbao is a food and beverage business in the city of Padang. The concept of cultural acculturation combines the traditional food of a race, namely Minangkabau and Chinese. This design aims to optimize the function and structure of Alingbao packaging, maximize the shape and visuals of the packaging so that information and brand awareness of the product is conveyed to consumers and potential consumers. This design uses the 4D method which consists of Define, Design, Develop and Disseminate with the development results in the form of pop-ups. The analysis method used is SWOT analysis (strengths, weaknesses, opportunities, threats). The main media in this design are three packages consisting of primary and secondary packaging. The supporting media for this design are social media, menu price lists, cups, hanging banners, aprons and tape. The main and supporting media in the design have also gone through a feasibility test in the form of a prototype. Meanwhile, the feasibility test indicators themselves consist of packaging layout, packaging visual elements, structure, function and packaging materials. This aims to ensure that the packaging is suitable and suitable for use.

Solving traffic data occlusion problems in computer vision algorithms using DeepSORT and quantum computing

Inaccuracies of traffic sensors during traffic counting and vehicle classification have persisted as transportation agencies have been prompted to calibrate sensors periodically. Detection of multiple objects, heavy occlusions, and similar appearances in congested places are some causes of computer vision model inaccuracies. This paper used the YOLOv5 model for detection and the DeepSORT model for tracking objects. Due to the nature of the reported problem caused by many misses and mismatches, the power of quantum computing with the alternating direction method of multipliers (ADMM) optimizer was leveraged. A basic Kalman filter and the Hungarian algorithm features were used in combination with a quantum optimizer to present robust multiple object tracking (MOT) algorithms. This hybrid combination of the classical and quantum model has fastened learning the occludes during frame matching of tracks and detections by generating minimum quantum cost function value. Comparisons with the existing models indicated a significant increase in the primary MOT metric multiple object tracking accuracy (MOTA) by 16% more than the regular YOLOv5-DeepSORT model when using a quantum optimizer. Also, a 6% multiple object tracking precision (MOTP) increases and a 6% identification metrics (F1) score increase were observed using the quantum optimizer with identity switching reduced from 6 to 4. This model is expected to assist transportation officials in improving the accuracy of traffic counts and vehicle classification and reduce the need for regular computer vision software calibration.

Current status of global colorectal cancer prevalence, prevention and control

Objective: This paper provides a brief overview of the epidemiology of colorectal cancer in China and around the world, and discusses how to prevent colorectal cancer to reduce its disease burden. Method: Using the official database of GLOBOCAN 2020, the China Cancer Registry Annual Report compiled by the National Cancer Center, and data from CONCORD-3.Data management was performed by Microsoft Excel 2016 and R 4.2.1 Relevant graphs were generated using the ggplot2 package for result visualization. Result: An estimated 1 931 590 people were diagnosed with colorectal cancer worldwide in 2020 with an age-standardized incidence rate of 19.5 per 100 000. There were about 935 173 deaths caused by colorectal cancer internationally, with an age-standardized mortality rate of 9.0 per 100 000. Overall, colorectal cancer was the fourth most commonly diagnosed cancer and the third leading cause of cancer-related death worldwide in 2020. In China, the age-standardized incidence rate and mortality rate of colorectal cancer was 17.3 per 100 000 and 7.8 per 100 000, respectively. Gender differences in trends were observed, with a decreasing trend in incidence and mortality among females and an increasing trend in incidence and mortality among males. The primary risk factors for colorectal cancer include age, genetic factors, gastrointestinal disorders, dietary habits, and lifestyle et al. Conclusions: Colorectal cancer poses a significant burden globally and in China. The occurrence of colorectal cancer is closely related to physiology, genetics, behavioral habits, lifestyle, and disease factors. To better control the colorectal cancer burden with the lowest cost, specific measures should be taken to reduce exposure to established risk factors. By combining the disease prevention and control strategies of tertiary prevention in China with the characteristic factors of colorectal cancer, the incidence and mortality of colorectal cancer may be effectively controlled.

Research Hotspots on Fresh Cold Chain Logistics Based on CiteSpace

With the rapid development of today's logistics industry, fresh cold chain logistics, as one of the important branches of the logistics industry, is an important means to ensure the quality and safety of fresh products, and its development has attracted more and more attention. In this paper, 181 papers related to fresh cold chain in Chinese core journals and CSSCI journals from 1998 to 2023 in CNKI database were taken as research objects, and the methods of keyword co-occurrence map, cluster map, and emergent word detection provided by visualization software CiteSpace were used to sort out and summarize the collected data, and explore the research hotspots and frontiers in the field of logistics process of fresh cold chain products. At the same time, China's agricultural product cold chain logistics research groups are in a fragmented state, and distribution mode and fresh e-commerce are the current hot spots of agricultural product cold chain logistics research; At present, there are still problems such as long supply chain, many circulation links, high cost and loss in the cold chain logistics of agricultural products, and in-depth discussions should be carried out from the aspects of intelligent logistics and cold chain logistics in the future.

Institutional theory and multinational corporation internationalization strategy: a systematic review and future research agenda

PurposeThis study reviews the literature on institutional theory in international business and examines the institutional factors behind the success or failure of multinational corporations (MNCs) in emerging markets.Design/methodology/approachThis systematic literature review analysed 116 peer-reviewed articles published in leading journals between 2005 and 2022. The R package Bibliometrix and VOSviewer visualization software were used for analysis. A hybrid methodology combining bibliometric and content analyses was utilized to obtain a descriptive evaluation of the publication impact along with a keyword co-occurrence map, context-specific institutional effects and subsidiary strategies.FindingsThe Journal of International Business Studies, along with influential authors such as Mike W. Peng, Klaus Meyer, and Mehmet Demirbag, have taken the lead in advancing institutional theories for MNC internationalization in emerging markets. The clusters from the co-word analysis revealed dominant MNC entry modes, institutional distances and MNC localization strategies. The content analysis highlights how the institutional environment is operationalized across the macro-, micro- and meso-institutional contexts and how the MNC subsidiary responds in emerging markets. Meso-level interactions emphasize the relational aspects of business strategies in emerging markets.Practical implicationsContextualizing subsidiary strategies and institutional forms can help managers align their strategic responses to the dynamic relationship between subsidiaries and the institutional environment. The review findings will enable policymakers to simplify regulatory policies and encourage MNC subsidiary networks with local stakeholders in emerging markets.Social implicationsLegitimacy strategies such as corporate community involvement in emerging markets are crucial for enhancing societal support and removing stakeholders' scepticism for MNC business operations in emerging markets. Moral legitimacy should be implemented by managers, such as lending support to disaster management efforts and humanitarian crises, as they expand to new business environments of emerging markets.Originality/valueThis study is the first to explore institutional diversity and subsidiary strategic responses in a three-layered institutional context. The findings highlight the relevance of contextualizing institutional perspectives for international business scholars and practitioners as they help build context-specific theoretical frameworks and business strategies. Future research recommendations are suggested in the macro-, micro- and meso-institutional contexts.

MyoV: a deep learning-based tool for the automated quantification of muscle fibers.

Accurate approaches for quantifying muscle fibers are essential in biomedical research and meat production. In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatically labeling over 660000 muscle fibers to create a large dataset. Subsequently, an automated image segmentation and quantification tool named MyoV is designed using mask regions with convolutional neural networks and a residual network and feature pyramid network as the backbone network. This design enables the tool to allow muscle fiber processing with different sizes and ages. MyoV, which achieves impressive detection rates of 0.93-0.96 and precision levels of 0.91-0.97, exhibits a superior performance in quantification, surpassing both manual methods and commonly employed algorithms and software, particularly for whole slide images (WSIs). Moreover, MyoV is proven as a powerful and suitable tool for various species with different muscle development, including mice, which are a crucial model for muscle disease diagnosis, and agricultural animals, which are a significant meat source for humans. Finally, we integrate this tool into visualization software with functions, such as segmentation, area determination and automatic labeling, allowing seamless processing for over 400000 muscle fibers within a WSI, eliminating the model adjustment and providing researchers with an easy-to-use visual interface to browse functional options and realize muscle fiber quantification from WSIs.

Structural and accessibility studies highlight the differential binding of clemizole to TRPC5 and TRPC6

Transient Receptor Potential Canonical 5 (T RP C5) and T RP C6 channels play critical physiological roles in various cell types. Their involvement in numerous disease progression mechanisms has led to extensive searches for their inhibitors. Although several potent T RP C inhibitors have been developed and the structure of their binding sites were mapped using cryo electron microscopy, a comprehensive understanding of the molecular interactions within the inhibitor binding site of T RP Cs remains elusive. This study aimed to decipher the structural determinants and molecular mechanisms contributing to the differential binding of clemizole to T RP C5 and T RP C6, with a particular focus on the accessibility of binding site residues. This information can help better understand what molecular features allow for selective binding, which is a key characteristic of clinically effective pharmacological agents. Using computational methodologies, we conducted an in-depth molecular docking analysis of clemizole with T RP C5 and T RP C6 channels. The protein structures were retrieved from publicly accessible protein databases. Discovery Studio 2020 Client Visualizer and Chimera software facilitated our in-silico mutation experiments and enabled us to identify the critical structural elements influencing clemizole binding. Our study reveals key molecular determinants at the clemizole binding site, specifically outlining the role of residues' Accessible Surface Area (ASA) and Relative Accessible Surface Area (RASA) in differential binding. We found that lower accessibility of T RP C6 binding site residues, compared to those in T RP C5, could account for the lower affinity binding of clemizole to T RP C6. This work illuminates the pivotal role of binding site residue accessibility in determining the affinity of clemizole to T RP C5 and T RP C6. A nuanced understanding of the distinct binding properties between these homologous proteins may pave the way for the development of more selective inhibitors, promising improved therapeutic efficacy and fewer off-target effects. By demystifying the structural and molecular subtleties of T RP C inhibitors, this research could significantly accelerate the drug discovery process, offering hope to patients afflicted with T RP C-related diseases.

Artificial Intelligence (AI) Application in Process Safety Cumulative Risk Visualization for Petroleum Operations: Conceptual Framework

One of the key challenges in preventing major process safety accidents in an operating plant is the lack of an integrated system/model that brings together the risks posed by the deficiencies / deviations on the safety critical barriers, for operational decision making. Based on this context, a model/framework was developed for assessing and visualizing the accumulation of process safety risks arising from safety critical barriers impairments in petroleum facilities in Niger-Delta Nigeria. Based on the review of the model, the need for an intelligent web-based software was identified. An exploratory study was therefore undertaken through extensive literature review and focused group participants, to develop a conceptual framework for an intelligent web-based software for process safety cumulative risk visualization. The results from the study make it evident that the conceptual framework provides a novel approach in developing an intelligent web-based software using artificial intelligence (AI) techniques, for real time visualization of process safety cumulative risk picture.

Exploring the linkage between business incubation and entrepreneurship: understanding trends, themes and future research agenda

PurposeThis article aims to conduct a bibliometric study using structural and relational approaches amongst the extracted documents and investigates the connections between business incubation and entrepreneurship-related papers to describe the field comprehensively.Design/methodology/approachA total of 259 articles have been retrieved from Scopus database in order to conduct the bibliometric analysis. Performance analysis and science mapping techniques of bibliometrics have been used along with data visualisation software, i.e. VOSviewer and RStudio. The network collaboration and intellectual structures, i.e. bibliographic coupling, co-occurrence analysis, word cloud and trending topics, have been presented to identify the field’s latest trends, themes and development.FindingsThe findings highlight annual publication trends, including the most frequently cited articles, the most productive authors, countries and highly influential journals that contribute the most to the said field. The intellectual structures have been developed to identify research themes and trends by running co-occurrence analysis and bibliographic coupling. The findings of this study emphasize the value of technology transfer, mentorship programmes, entrepreneurship education and an emphasis on innovation and creativity through entrepreneurial universities and academia. These findings provide policymakers and administrative officials with crucial guidance for fortifying the pillars of entrepreneurship and education for the comprehensive development of the economy. Further, this article attempts to identify the most influential and relevant publications as well as the newest trends in the area of business incubation in combination with entrepreneurship.Research limitations/implicationsThe article contributes not only to broaden the scope of knowledge on the said research discipline but also to comprehend how the field has evolved over a period of time. This study also attracts the interest of scholars/academicians, leading to the significant production of scholarly documents in business incubation and entrepreneurship.Practical implicationsThe field of entrepreneurship and business incubation is one of the important pillars for the growth and development of the economy. This piece contributes to this arena by focusing on the areas that must be taken care of by developing the entrepreneurial ecosystem and fostering the progress of startups. The fundamentals of this research highlight the importance of mentorship programs, entrepreneurship education, technology transfer and a focus on innovation and creativity through entrepreneurial education and efforts by universities/academia, giving an important direction to the policymakers and administration for strengthening the pillar of entrepreneurship and education for the holistic development of the economy.Originality/valueBusiness incubation is an emerging field of academic research connected to startups, venture formation and entrepreneurship ecosystems, making it a potential scholarly discipline. This study presents a thorough bibliometric analysis over the last three decades, offering comprehensive details on the most significant developments in the field of business incubation. Moreover, the various analytical methods applied to this study make it more attractive.

Knowledge Graph Analysis of Science and Technology and Children's Education

In this study, 1700 articles related to children and science and technology education published on CNKI) were taken as the research objects, and the visualization software CiteSpace was used to draw the keyword knowledge map, so as to explore the hot research issues of children and science and technology education in China. The results show that the research of children and science and technology education in China basically focuses on the core issues of child education, and the main topics include the relationship between child education and science education, science museum and science and technology, early childhood education and child education. This study will focus on the following aspects, The relationship between science and technology and children's education policies: to explore the government's policy measures in promoting the integration of science and technology and children's education, and the impact of these policies on educational practice. Development and application of science and technology education products: analyze the design concept and functional characteristics of science and technology education products, as well as their application effect in educational practice. Development and innovation of science and technology education enterprises: to study the business model, market competition strategy of science and technology education enterprises, and their exploration in technology innovation and education practice. The knowledge graph analysis of this study will provide a visual tool for understanding the relationship between technology and child education, and will help to provide a useful reference for educational researchers, policy makers and practitioners.

Roboto su tiesiaeigio judėjimo/pozicionavimo įrenginiu automatinės sistemos efektyvumo tyrimas

The work presents an assessment of the efficiency and operational costs of modernized manufacturing process. The process consists of turning operations on two CNC lathe machines. Two options for modernization are proposed: installation of 2 robots automated system and installation of an automated system of one robot on a linear motion track for positioning. The purpose of the study is to prove the advantage of option with one robot on a linear motion track device. The process modelling is performed in Visual Components software. ABB 6-axis robot IRB 4600 and the linear motion track device ABB IRBT 4004 of the same manufacturer were chosen for the research. Keywords: robot, linear motion track, Visual Components software.

Knowledge domain and emerging trends of autophagy in cardiovascular research: A bibliometric analysis.

Autophagy is essential for the homeostasis and function of the cardiovascular system. Citespace is a visual analysis software developed in the context of scientometrics and data visualization. The purpose of this study is to use Citespace software to conduct bibliometric and visual analysis of the research on autophagy in cardiovascular diseases, identify the current status, hot spots and trends in this field, help researchers clarify the future research focus and direction of autophagy in cardiovascular diseases, and provide more positive and broader ideas for the treatment and drug development of cardiovascular diseases. In the Web of Science Core Collection database to download the data from 2004 to 2022 regarding autophagy in cardiovascular research. CitespaceV was used to collect the research status, hotspots and development trends for visual analysis. The 3568 articles were published by 547 authors from 397 institutions in 75 countries. From 2004 to 2021, the annual publications increased over time. The top 3 productive nations were China, the United States, and Germany. The leading institution was China's Fudan University. The most cited paper is Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition). The research hotpots include monitoring methods for autophagy activity, changes in autophagy levels in different types of cardiovascular diseases, autophagy signal transduction mechanism in cardiovascular diseases, etc. Bibliometric analysis provided valuable information for autophagy research in cardiovascular disease, which is full of opportunities and challenges. The research of autophagy in the field of cardiovascular diseases is still worthy of in-depth exploration. A challenge with autophagy-targeted therapies is their dichotomy in which the goal is to target maladaptive autophagy while maintaining a baseline level of cell survival to optimize a beneficial outcome. It is necessary for scientists to develop new methods to evaluate the level of autophagy from basic application to human body and reveal the signaling mechanism of autophagy in different types of cardiovascular diseases.

MOLECULAR DOCKING STUDY OF EPIGALLOCATECHIN GALLATE ON FLT3 IN COMPLEX WITH GILTERITINIB FOR ANTICANCER ACTIVITY

Objective: The aim of the study was to predict the binding affinity and interaction patterns between EGCG and FLT3 in complex with gilteritinib using molecular docking simulations. stabilization of the EGCG-FLT3-gilteritinib complex. Methods: The crystal structure of FLT3 in complex with gilteritinib was downloaded from the Protein Data Bank (PDB) database. Epigallocatechin gallate (EGCG) was obtained from the PubChem database. Auto Dock 8 software was utilized for the molecular docking study. The docking results are analyzed to identify the best pose based on binding affinity, hydrogen bonding, and other favorable interactions. The Discovery Studio Visualizer or other suitable software was used to visualize the protein-ligand interactions and analyze the binding mode of EGCG within the FLT3-gilteritinib complex. Results: The best ranking for ligands binding was at run 7 with the estimated free energy of binding −7.87 kcal/mol the estimated inhibition constant (ki) was 1.69 μm. The final intermolecular energy was −11.45 kcal/mol. kcal/mol It had 12 active torsions. The redocking score using gilteritinib was used as a control for the validation of the study. The estimated free energy of binding was −7.91 kcal/mol. The estimated inhibition constant ki is 1.60 μm. It had nine active torsions. Conclusion: Comparing the various binding energies and torsions of the test compound and the control revealed that the test epigallocatechin had a perfect docking score, and it was predicted to possess comparable anti-tumor and anticancer activity.

Bibliometric and visualized analysis of resveratrol in anticancer investigations.

A growing number of publications have shown that resveratrol has anticancer effects and has become a hotspot in cancer research. The purpose of this study is to analyze the academic results and research trends in resveratrol within the field of anticancer and to predict the future trends in this field. We conducted a literature search for resveratrol in anticancer research from 2003 to 2022 using the Science Citation Index Expanded of the Web of Science Core Collection. The visualization software was used to perform the bibliometric analysis. A total of 1463 publications from 2003 to 2022 were retrieved. China had the highest number of publications. Taipei Medical University became the research institution with the largest number of publications worldwide. The journals with the highest output and co-citation frequency were Molecules and Cancer Research. Levenson, Anait S and Jaeger, Walter published the largest number of papers. Jang, MS was the most co-cited author. Timeline View shows trends and relationship between research topics over time and suggests that the emerging frontier of resveratrol in anticancer may be "resveratrol induces apoptosis." As more and more evidence shows the important role of resveratrol in anticancer, further research on its mechanisms and target discovery may become a major direction for future research. The bibliometric analysis findings of this study will significantly contribute to scholars' comprehensive understanding of the anticancer effects and mechanisms of action of resveratrol, aiding in delineating research hotspots and frontier directions within this field, thereby providing guidance for future investigations.

The combined focal loss and dice loss function improves the segmentation of beta-sheets in medium-resolution cryo-electron-microscopy density maps.

Although multiple neural networks have been proposed for detecting secondary structures from medium-resolution (5-10 Å) cryo-electron microscopy (cryo-EM) maps, the loss functions used in the existing deep learning networks are primarily based on cross-entropy loss, which is known to be sensitive to class imbalances. We investigated five loss functions: cross-entropy, Focal loss, Dice loss, and two combined loss functions. Using a U-Net architecture in our DeepSSETracer method and a dataset composed of 1355 box-cropped atomic-structure/density-map pairs, we found that a newly designed loss function that combines Focal loss and Dice loss provides the best overall detection accuracy for secondary structures. For β-sheet voxels, which are generally much harder to detect than helix voxels, the combined loss function achieved a significant improvement (an 8.8% increase in the F1 score) compared to the cross-entropy loss function and a noticeable improvement from the Dice loss function. This study demonstrates the potential for designing more effective loss functions for hard cases in the segmentation of secondary structures. The newly trained model was incorporated into DeepSSETracer 1.1 for the segmentation of protein secondary structures in medium-resolution cryo-EM map components. DeepSSETracer can be integrated into ChimeraX, a popular molecular visualization software. https://www.cs.odu.edu/∼bioinfo/B2I_Tools/.

Predicting photosynthetic pathway from anatomy using machine learning.

Plants with Crassulacean acid metabolism (CAM) have long been associated with a specialized anatomy, including succulence and thick photosynthetic tissues. Firm, quantitative boundaries between non-CAM and CAM plants have yet to be established - if they indeed exist. Using novel computer vision software to measure anatomy, we combined new measurements with published data across flowering plants. We then used machine learning and phylogenetic comparative methods to investigate relationships between CAM and anatomy. We found significant differences in photosynthetic tissue anatomy between plants with differing CAM phenotypes. Machine learning-based classification was over 95% accurate in differentiating CAM from non-CAM anatomy, and had over 70% recall of distinct CAM phenotypes. Phylogenetic least squares regression and threshold analyses revealed that CAM evolution was significantly correlated with increased mesophyll cell size, thicker leaves, and decreased intercellular airspace. Our findings suggest that machine learning may be used to aid the discovery of new CAM species and that the evolutionary trajectory from non-CAM to strong, obligate CAM requires continual anatomical specialization.

Cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data

BackgroundHighly multiplexed imaging enables single-cell-resolved detection of numerous biological molecules in their spatial tissue context. Interactive visualization of multiplexed imaging data is crucial at any step of data analysis to facilitate quality control and the spatial exploration of single cell features. However, tools for interactive visualization of multiplexed imaging data are not available in the statistical programming language R.ResultsHere, we describe cytoviewer, an R/Bioconductor package for interactive visualization and exploration of multi-channel images and segmentation masks. The cytoviewer package supports flexible generation of image composites, allows side-by-side visualization of single channels, and facilitates the spatial visualization of single-cell data in the form of segmentation masks. As such, cytoviewer improves image and segmentation quality control, the visualization of cell phenotyping results and qualitative validation of hypothesis at any step of data analysis. The package operates on standard data classes of the Bioconductor project and therefore integrates with an extensive framework for single-cell and image analysis. The graphical user interface allows intuitive navigation and little coding experience is required to use the package. We showcase the functionality and biological application of cytoviewer by analysis of an imaging mass cytometry dataset acquired from cancer samples.ConclusionsThe cytoviewer package offers a rich set of features for highly multiplexed imaging data visualization in R that seamlessly integrates with the workflow for image and single-cell data analysis.It can be installed from Bioconductor via https://www.bioconductor.org/packages/release/bioc/html/cytoviewer.html. The development version and further instructions can be found on GitHub at https://github.com/BodenmillerGroup/cytoviewer.

Integrating visual language with architecture: Using VAS software to measure the coherence of pre-attentive vision

Visual language has evolved as a result of technological development over ages. The pre-attentive visual software (VAS) is a biometric technique that is used to simulate human eye movement, gaze sequence, and visual appeal at the first (3-5) seconds of responding. Hence, the pre-attentive response is the first objective phase that is shared by all. The second phase of human responses is related to the perception stage depending upon personal and subjective preferences. Post-perception represents the third phase of responding after evaluation and judgment. While the Gestalt theory focuses on the perception phase, we find that the (15) properties of wholeness for Christopher Alexander deal with the post-perception phase. It is claimed that pre-attentive vision, produced by (VAS), is the actual way to perceive the coherent whole. The experimental approach of testifying different, but unified and neutralized, images of residential facades by (VAS) shows that architectural elements and their visual relations act as a coherent whole that attract our attention. The research goals are: promote the idea of objective pre-attentive vision and its attractiveness. also It is a trail to predict the coherence of designs. Accordingly, it is suggested to use (VAS) as a sensitive, detective and reliable tool in architectural design, artificial intelligence, neurosciences technology, plastic surgeries… Further investigations in the field of architecture are recommended to develop a new language of visual structures.