Quantitative Visualization Research Articles

A colorimetric method for quantitative visualization of diffusion and internal circulation in liquid–liquid two-phase flow

Herein, we propose a new method for the quantitative evaluation of mass-transfer characteristics in liquid–liquid two-phase flow during the formation of slug and its progression in a microchannel. The experimental setup included a 0.3-mm square microchannel with a Y junction. Distilled water with pH indicator and cyclohexane containing acetic acid were selected as the probe fluids. The acetic-acid concentrations were 0.05 and 0.1 vol%, while the volumetric velocity of the aqueous and organic phases was 0.03 mL/min. Acetic-acid diffusion and its internal circulation in the aqueous slug were visualized by color changes and recorded as microscopically magnified video images. By adopting a deep-learning algorithm, the aqueous slugs were segmented, and a calibration method converted color information to acetic-acid concentration values. The experimental results were comparable with those of previous studies. The presented method also revealed several new features that could not have been observed quantitatively by established experimental methods.

Transnacionalismo Desmantelando o Cânon: Uma leitura próxima e distante de várias redes literárias transatlânticas na tradução

This essay argues that random acts of poetry translation in transnational context play a significant role in turning any apparently homogenous literary system into a network with many access points. In doing so, they overtly or covertly undermine the idea of a literary canon, since they position, more or less explicitly, such canon against their own literary taste and network of acquaintances. In addition, the lack of financial conditioning makes this kind of translation barters reach literary audiences more easily. Since these exchanges are more commonly initiated by translators working in lesser-known languages, it follows that transnational translation barters level out cultural imbalances by having the translator-poets’ work translated into languages of wider circulation. This contribution presents four kinds of transnational exchanges in Romanian context and argues that more complex translation mechanisms result into a more open, more diverse, and a more dynamic literary scene, in which translators play a prominent role. From a methodological point of view, this essay combines the traditional close reading of the texts and paratexts with quantitative analysis and network visualization to lay out the blueprint of Romanian translations of US and Canadian poetry in periodicals between 2007 and 2017 and quantify the number of random exchanges against a transnational backdrop.

Identification of inducer cavitation instabilities using high-speed visualization

This paper presents a new inducer cavitation instability detection method based directly on quantitative high-speed visualization. The new method uses the grayscale values of pixels, representing fluctuations in the cavity structure, to identify cavitation instability. The method is validated against unsteady pressure measurements in two- and three-bladed inducers. Both unsteady pressure measurements and grayscale fluctuations have been analyzed in the frequency domain via Fourier transformation and traveling wave energy analysis to establish the correspondence between the two types of data. Finally, the new method is applied to demonstrate its capability to detect alternate blade cavitation in a 2-bladed inducer and super-synchronous rotating cavitation in a 3-bladed inducer.

Constructing a Rigid-and-Flexible Twin-Stage Gradient Interphase through Starlike Copolymer Coating on Carbon Fibers: A Route for Enhancing Interfacial Properties of Composites.

A rigid-and-flexible interphase was established by a starlike copolymer (Pc-PGMA/Pc) consisting of one tetraaminophthalocyanine (TAPc) core with four TAPc-difunctionalized poly(glycidyl methacrylate) (PGMA) arms through the surface modification of carbon fibers (CFs) and compared with various interphases constructed by TAPc and TAPc-connected PGMA (Pc-PGMA). The increase in the content of N-C═O showed that PGMA/Pc branches were successfully attached onto the CF-(Pc-PGMA/Pc) surface, exhibiting concavo-convex microstructures with the highest roughness. Through adhesive force spectroscopy by atomic force microscopy (AFM) with peak force quantitative nanomechanical mapping (PF-QNM) mode and visualization of the relative distribution of TAPc/PGMA via a Raman spectrometer, a rigid interphase with highly cross-linked TAPc and a flexible layer from PGMA arms as the soft segment were separately detected in CF-TAPc/EP and CF-(Pc-PGMA)/EP composites. The rigid-and-flexible interphase in the CF-(Pc-PGMA/Pc)/EP composite provided excellent stress-transfer capability by the rigid inner modulus intermediate layer and energy absorption efficiency from the flexible outer layer, which contributed to 64.6 and 61.8% increment of transverse fiber bundle test (TFBT) strength, and 33.8 and 40.6% enhancement in interfacial shear strength (IFSS) in comparison with those of CF-TAPc/EP and CF-(Pc-PGMA)/EP composites. Accordingly, schematic models of the interphase reinforcing mechanism were proposed. The interfacial failures in CF-TAPc/EP and CF-(Pc-PGMA)/EP composites were derived from the rigid interphase without effective relaxation of interfacial stress and soft interphase with excessive fiber-matrix interface slippage, respectively. The cohesive failure in the CF-(Pc-PGMA/Pc)/EP composite was attributed to the crack deflection through the balance of the modulus and deformability from the twin-stage gradient intermediate layer.

Integration and Quantitative Visualization of 3,3',5,5'-Tetramethylbenzidine-Probed Enzyme-Linked Immunosorbent Assay-like Signals in a Photothermal Bar-Chart Microfluidic Chip for Multiplexed Immunosensing.

The photothermal effect shows significant promise for various biomedical applications but is rarely exploited for microfluidic lab-on-a-chip bioassays. Herein, a photothermal bar-chart microfluidic immunosensing chip, with the integration of the conventional 3,3',5,5'-tetramethylbenzidine (TMB)-probed enzyme-linked immunosorbent assay (ELISA)-like system, was developed based on exploiting the photothermal pumping technique for visual bar-chart microfluidic immunosensing. Both the sandwich ELISA-like system and the photothermal pumping protocol were integrated into a single photothermal bar-chart chip. On-chip immunocaptured iron oxide nanoparticles catalyzed the oxidation of the chromogenic substrate, TMB, to produce a sensitive photothermal and chromogenic dual-functional probe, oxidized TMB. As the result of heat generation and the subsequent production of elevating vapor pressure in the sealed microfluidic environment, the on-chip near-infrared laser-driven photothermal effect of the probe served as a dose-dependent pumping force to drive the multiplexed quantitative display of the immunosensing signals as visual dye bar charts. Prostate-specific antigen as a model analyte was tested at a limit of detection of 1.9 ng·mL-1, lower than the clinical diagnostic threshold of prostate cancer. This work presents a new perspective for microfluidic integration and multiplexed quantitative bar-chart visualization of the conventional TMB-probed ELISA signals possibly by means of an affordable handheld laser pointer in a lab-on-a-chip format.

Entrance flow of unfoamed and foamed Herschel–Bulkley fluids

The present study investigates extrusion processing of unfoamed and foamed cocoa butter (CB) crystal-melt suspensions (CMSs) with varying crystal volume fraction ΦSFC. Capillary rheometry derived flow curves were fitted with the Herschel–Bulkley–Papanastasiou (HBP) model, and the derived yield stress to wall shear stress ratio τ0/τw of CB CMSs was compared for the various ΦSFC. Foamed CB CMSs behaved fluidlike for ΦSFC≤11.9% and according to a brittle porous solid for ΦSFC>11.9%. The dimensionless entrance pressure loss nen/α as a function of dimensionless shear stress τ∗ was higher for foamed compared to unfoamed CB CMSs at ΦSFC≤11.9% and lower for foamed compared to unfoamed CB CMSs at ΦSFC>11.9%. The ΦSFC dependent difference in nen/α was attributed to the crystal confinement in the die entrance flow, which is increased in the case of elastic gas bubble deformation and decreased in the case of plastic gas pore collapse. The computational fluid dynamics simulated flow of unfoamed and foamed CB CMSs through an abrupt circular 20:1 contraction with the HBP model was compared with the experimental results from quantitative entrance flow visualization (QEFV). Furthermore, the QEFV derived half center incidence angle θ as well as the entrance flow shear and elongational rates γ˙ef and ϵ˙ef were derived and used to establish a model predicting the Bagley entrance pressure loss ΔPBag and calculate an entrance flow characteristic shear and elongational viscosities ηefs and ηefe.

Machine Learning based Classification of Local Robotic Surgical Skills in a Training Tasks Set.

During surgical training, it is important for the surgeon develops good motor skills throughout his training. For this reason, various surgical training systems have been developed to enhance these skills. However, one of the great challenges in these training systems is being able to objectively measure the ability and performance of the main surgical tasks, where currently only a global measurement is obtained once the task is completed. In this work, a temporal evaluation scheme is proposed, that is, an evaluation of local surgical performance at different time intervals during the training of typical tasks (knot-tying, needle-passing and suturing). The goal is to automatically classify expert (experience >100 hrs) and non-expert (experience <10 hrs) surgeons according to their performance during training, based on three classifiers: K-Nearest Neighborhood, Random Forest, and Support Vector Machine Unlike other previously reported methods, this work proposes a new evaluation scheme based on segments or time intervals, which can be an indicator of the surgeon's local performance during a robotic surgical task, without the need for direct labeling of the data at the segment level. The classification performance from obtained results was in accuracy 83% to 100%, 88% to 100% of AUC-ROC, and 88% to 100% of F1-Score in the final test between experts and non-experts surgeons, where the Support Vector Machine classifier presented the best performance. These results suggest that this proposed method by time intervals could be used in various surgical trainers to evaluate the local performance of a surgeon during trainingand thus be able to provide a tool for the quantitative visualization of opportunities to improve surgical skills.Clinical relevance- We consider that the proposed method to carry out a local performance evaluation during surgical training can provide useful information in the learning and improvement of surgical skills.

Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly.

Background Imaging assessment for hepatomegaly is not well defined and currently uses suboptimal, unidimensional measures. Liver volume provides a more direct measure for organ enlargement. Purpose To determine organ volume and to establish thresholds for hepatomegaly with use of a validated deep learning artificial intelligence tool that automatically segments the liver. Materials and Methods In this retrospective study, liver volumes were successfully derived with use of a deep learning tool for asymptomatic outpatient adults who underwent multidetector CT for colorectal cancer screening (unenhanced) or renal donor evaluation (contrast-enhanced) at a single medical center between April 2004 and December 2016. The performance of the craniocaudal and maximal three-dimensional (3D) linear measures was assessed. The manual liver volume results were compared with the automated results in a subset of renal donors in which the entire liver was included at both precontrast and postcontrast CT. Unenhanced liver volumes were standardized to a postcontrast equivalent, reflecting a correction of 3.6%. Linear regression analysis was performed to assess the major patient-specific determinant or determinants of liver volume among age, sex, height, weight, and body surface area. Results A total of 3065 patients (mean age ± standard deviation, 54 years ± 12; 1639 women) underwent multidetector CT for colorectal screening (n = 1960) or renal donor evaluation (n = 1105). The mean standardized automated liver volume ± standard deviation was 1533 mL ± 375 and demonstrated a normal distribution. Patient weight was the major determinant of liver volume and demonstrated a linear relationship. From this result, a linear weight-based upper limit of normal hepatomegaly threshold volume was derived: hepatomegaly (mL) = 14.0 × (weight [kg]) + 979. A craniocaudal threshold of 19 cm was 71% sensitive (49 of 69 patients) and 86% specific (887 of 1030 patients) for hepatomegaly, and a maximal 3D linear threshold of 24 cm was 78% sensitive (54 of 69) and 66% specific (678 of 1030). In the subset of 189 patients, the median difference in hepatic volume between the deep learning tool and the semiautomated or manual method was 2.3% (38 mL). Conclusion A simple weight-based threshold for hepatomegaly derived by using a fully automated CT-based liver volume segmentation based on deep learning provided an objective and more accurate assessment of liver size than linear measures. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Sosna in this issue.

Conceptual design and preliminary experiment of icing risk management and protection system

Icing is one of the main external environmental factors that causes aircraft to lose control. The flight safety assurance system under icing condition is particularly important. However, most of the systems do not consider the coupling characteristics of aerodynamics and flight dynamics of icing aircraft. This will affect the accuracy of the calculation results. Besides, the icing risk management system helps the pilot to realize the possible dangers in advance and perform correct maneuvers, based on quantitative assessment and visualization methods of flight risk. The envelope protection system realizes flight safety guarantee based on the real-time boundary protection method of key flight parameters. Finally, based on distributed simulation technology, a flight simulator was used as a platform to integrate the icing risk management system and envelope protection system to realize man-in-the-loop simulation. Two fictional but historically motivated icing scenarios are designed to test the system, and the results demonstrate that the icing risk management and protection system would be useful for aviation safety and can also be used for pilot training and reproducing flight accidents to find the causes.

Study of concrete de-bonding assessment technique for containment liner plates in nuclear power plants using ultrasonic guided wave approach

In this work, the guided wave de-bonding area-detecting technique was studied for application to containment liner plates in nuclear power plant areas. To apply this technique, an appropriate Lamb wave mode, symmetric and longitudinal dominance, was verified by the frequency shifting technique. The S0 2.7 MHz mm Lamb wave mode was chosen to realize quantitative experimental results and their visualization. Results of the bulk wave, longitudinal wave mode, and comparison experiments indicate that the wave mode was able to distinguish between the de-bonded and bonded areas. Similar to the bulk wave cases, the bonded region could be distinguished from the de-bonded region using the Lamb wave approach. The Lamb wave technique results showed significant correlation to the de-bonding area. As the de-bonding area increased, the Lamb wave energy attenuation effect decreased, which was a prominent factor in the realization of quantitative tomographic visualization. The feasibility of tomographic visualization was studied via the application of Lamb waves. The reconstruction algorithm for the probabilistic inspection of damage (RAPID) technique was applied to the containment liner plate to verify and visualize the de-bonding condition. The results obtained using the tomography image indicated that the Lamb wave-based RAPID algorithm was capable of delineating debonding areas.

Quantitative Visualization Analysis in the Field of Sports Dance Based on CiteSpace

Taking 266 CSSCI records of sports dance from CNKI database as the research object, the relevant data were analyzed by CiteSpace software. By means of knowledge map, this paper combs the number of papers, high-yield institutions, high-yield authors, cooperation and research hotspots. This study draws the following conclusions, which are divided into three time periods according to the amount of documents issued; The cooperation between the authors is scattered, and the representatives are mainly concentrated in Beijing Sports University; The distribution of research institutions is scattered and the cluster scale is small; The keywords are clustered into nine cluster labels. Through sorting and summarizing, the nine clusters are summarized into six aspects: the development of sports dance, the development of sports dance in China’s mass sports, sports dance teaching, the cultural integration of national standard dance and Chinese classical dance, the aesthetic value of sports dance, and the impact of sports dance on College Students’ physical and mental health.

Software engineering and 12 prominent sub‐areas: Comprehensive bibliometric assessment on 13 years (2007–2019)

Software Engineering (SE) as a field has grown significantly in terms of the research publications in the last few years. Criterion-based assessment of research performance of scholars, countries along with collaboration networks and links among articles are better judged using bibliometric analysis. The results proposed in this work are based on quantitative analysis and data visualisation of 150,087 scholarly articles published in last 13 years (2007–2019) across 85 research areas based on seven categories by providing a detailed and distinctive time-frame-based comparison to observe a shift in research trend in SE and its 12 distinguished sub-areas. The results of the observations proposed in this work include analysis on types of documents, yearly publication trends with results suggesting a prominent increment for the period (2015–2017) in terms of research publications, languages of research publications with findings indicating that there are articles published in languages other than English language, also, publication count-based rankings of authors, collaboration networks of countries with findings showing the supremacy of USA and China and keyword statistics.

Quantitative description of publications (1986-2020) related to Alzheimer disease and oxidative stress: A bibliometric study

While the pathological mechanism of Alzheimer’s Disease (AD) is unclear, oxidative stress has been proposed to be one of its related theories, which can help to uncover the disease’s pathological factors. This review aims to provide a quantitative description and data visualisation of oxidative stress and AD research from the literature obtained from the Scopus database. Based on the keywords used, which are related to oxidative stress and AD in the article title, 996 documents were retrieved for further analysis. Microsoft Excel, VOSviewer, and Harzing’s Publish or Perish were used to conduct the frequency analysis, data visualization, and citation analysis. There is a continuous growth in the number of publications on research in oxidative stress and AD, starting from 1986 and spanning 35 years. The most cited article was “Oxidative stress hypothesis in Alzheimer's disease”. The Journal of Alzheimer's Disease published the most number of publications related to oxidative stress and AD, while the United States and its institutions were the main contributors. Our findings suggest that research on aetiopathology, biomarkers, and neuroprotective agents for AD dominated this research field.&#x0D; Our bibliometric analysis provides distinct trends in oxidative stress and AD research in the last 35 years. Our findings highlight current hot topics related to biomarkers for screening and diagnosis of AD as well as neuroprotective agents used as disease-modifying therapies of AD.

On the Origin of Sinter‐Resistance and Catalyst Accessibility in Raspberry‐Colloid‐Templated Catalyst Design

AbstractNanoparticle (NP) sintering is a major cause of the deactivation of supported catalysts. Raspberry‐colloid‐templated (RCT) catalysts are an emerging class of materials that show an unprecedented level of sinter‐resistance and exhibit high catalytic activity. Here a comprehensive study of the origin of NP stability and accessibility in RCT catalysts using theoretical modeling, 3D electron microscopy, and epitaxial overgrowth is reported. The approach is showcased for silica‐based RCT catalysts containing dilute Pd‐in‐Au NPs previously used in hydrogenation and oxidation catalysis. Modeling of the contact line of the silica precursor infiltrating into the assembled raspberry colloids suggests that a large part of the particles must be embedded into silica, which is confirmed by quantitative visualization of &gt;200 individual NPs by dual‐axis electron tomography. The RCT catalysts have a unique structure in which all NPs reside at the pore wall but have &gt;50% of their surface embedded in the matrix, giving rise to the strongly enhanced thermal and mechanical stability. Importantly, epitaxial overgrowth of Ag on the supported NPs reveals that not only the NP surface exposed to the pore but the embedded interface as well remained chemically accessible. This mechanistic understanding provides valuable guidance in the design of stable catalytic materials.

Determination of the stress and strain fields in porous structures by photoelasticity and digital image correlation techniques

Quantitative visualization of the full-field stress and strain in porous structures is of significance to reveal the mechanism of the damage and failure of engineering materials. To quantitatively characterize the full-field stresses and strains, optical measurement methods, such as photoelasticity for determining the stress fields, moiré and digital image correlation (DIC) methods for measuring the strain fields, have been developed in previous works. However, it is challenging to combine these methods to measure stress and strain fields simultaneously because the speckles and gratings for strain measurement will disturb the interference fringes in the photoelasticity. In this study, a method incorporating photoelasticity and DIC techniques was developed to determine the stress and strain fields simultaneously in different porous structures which were fabricated by three-dimensional (3D) printed technique. The tested models were printed with a highly transparent, colourless material and the speckles on the front surface of the tested models were printed with a translucent, magenta material. Under compressive loads, the stress fields in these models were obtained based on the photoelastic patterns and the strain fields were determined by DIC method. The results indicate the proposed method can simultaneously determine the full-field stresses and strains and the comparison of the distribution of the principal stress and strain difference and the distribution of the shear stress and strain verified its good accuracy. In addition, the stress and strain distribution in different pore structures were compared and found that the optimal design of the pore distribution can greatly change the concentration of the stress and strain fields.

Research status and development trends in the field of marine environment corrosion: a new perspective.

Corrosion had aroused extensive concern and attention because it was an unavoidable problem for marine equipment and facilities in service. However, the current status and development trend of marine environment corrosion research had seldom been systematically studied. Therefore, it was encouraged to use bibliometrics and information visualization analysis methods to conduct bibliometric analysis of related publications in the field of marine environment corrosion based on HistCite, CiteSpace, and VOSviewer software programs. Compared with the traditional comments of researchers in this field, this research provided a direction for the development of quantitative analysis and visualization of marine environment corrosion on a large scale. The results showed that the overall focus of research in the field of marine environment corrosion continued to increase from 1900 to 2019. China had the highest publication productivity, the USA had the highest h-index value and the second highest average citations per item value, Materials Science was the most popular subject category, Corrosion Science was the main journal and Melchers RE was the author with the most output contributions. This research also exhibited four hot spots in this field. In addition, this work could help new researchers to find research directions and identify research trends and frontiers in the field of marine environment corrosion by tracing the research hotspots of topic categories, countries, institutions, journals, authors, and publications in recent years.

Trends in the development of regional trust management markets

The article discusses the features of the development of the trust management services market. The purpose of the article is to determine the regional features of the development of the trust management services market. The article uses the methods of quantitative empirical research, statistical analysis and visualization, analysis and assessment of the regional dynamics of the main instruments of trust management. The formation of the trust management market takes into account the peculiarities of the development and economies of individual countries, regional regulatory characteristics. Trust management is widespread in advanced countries, while in other countries this market is just emerging. In general, the trust management market in the countries of Eastern Europe and Russia in particular is only in the process of formation, although the services themselves have a long history of development. They are most often viewed as part of the overall market for banking or insurance services. At the present stage, there is a selection of a separate market segment, determination of the place of trust services in the structure of banking services, identification of regional characteristics in the structure of the global market. The peculiarities of the Russian securities market are: active participation of the state in the processes of market trading, a large number of government securities on the market and a relatively low level of involvement in global processes. The market is relatively small, but its development is quite dynamic. The key prerequisites for the development of the market are: the relative closeness of the market, government regulation, a decrease in the attractiveness of other banking or financial instruments, and an increase in the general welfare of investors.

Ivan Turgenev als Netzwerker: Digitale Kuratierung seiner europäischen, insbesondere deutschen literarischen Kontakte (am Beispiel seines Briefwechsels vom Juni 1868 bis Mai 1869)

The Russian writer Ivan Sergeevič Turgenev (1818–83), who lived in Western Europe (Germany, England, and France) during the second half of his life, is considered the most important mediator between Russia and Europe in the nineteenth century due to his wide and intensive contacts in East and West. The paper aims to trace Turgenev’s literary and cultural contacts using the epistemological model of the net and current methods of analyzing social networks on a quantitative and qualitative level. In concrete terms, Turgenev’s postal relations from a single year (from June 1868 to May 1869) are presented and evaluated in tabular form and as GEPHI graphs. Beyond the purely quantitative network visualization and viewing, the attempt is made to provide a cultural weighting of the exchange, especially of Turgenev’s German contacts. The network-specific weighting of these contacts results in a different emphasis than usual in Turgenev research, which focuses on Turgenev’s contacts with important German writers. The qualitative analysis carried out on the basis of the visualization shows that Turgenev’s contacts with literary celebrities such as Theodor Storm, Berthold Auerbach, and Paul Heyse proved to be weak ties. In contrast, his relationship with the little-known literary figure Ludwig Pietsch deserves to be called a strong tie. Turgenev’s position and agency in the network can be described with Burt as a “broker” attitude.

Numerical Simulation and Non-Destructive Characterization of Material Property and Defect Analysis of Cortical Bone Using Laser Ultrasound Techniques.

The application of bone quality assessment has received extensive attention, and a large number of researchers continue to invest in related research activities. To get closer to the real situation, this study intends to investigate the long bones of cattle. A quantitative laser ultrasound visualization (QLUV) system was used to measure the images transmitted by the guided waves on the long bones, and the internal defects of the long bones were detected using wave propagation behavior. Then, linear scanning was performed through a laser ultrasound technique (LUT) to measure the dispersion curve of the cortical bone, and the results were compared with finite element simulations. Further, LUT was used to measure the material properties of the cortical bone in all directions. Finally, the long bones were scanned by computerized tomography to analyze the pore direction and distribution. Further, the relationship between pore direction and material properties was studied. The results showed that the obtained wave propagation image was consistent with the time-domain waveform signal and the finite element analysis results. The experimental and simulation results of wave velocity showed an error of 0.26 to 1.56% compared with the literature. The plate-shaped cortical bone showed that the phase velocity of the guided wave is higher than the circumferential direction. The defect location was identified through wave propagation behavior using the QLUV system. The elastic constant of the cortical bone was measured, and it showed the same trend as the results obtained from the tensile test in the literature. Also, the pore distribution indicated that the cortical bone porosity has the same trend as elastic constants. The elastic constants along the longitudinal direction were greater than the transversal direction. This laser ultrasound technique has been developed with an aim of having a better resolution and also as a potential application in osteoporosis conditions.

ScAdapt: virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species.

In single cell analyses, cell types are conventionally identified based on expressions of known marker genes, whose identifications are time-consuming and irreproducible. To solve this issue, many supervised approaches have been developed to identify cell types based on the rapid accumulation of public datasets. However, these approaches are sensitive to batch effects or biological variations since the data distributions are different in cross-platforms or species predictions. In this study, we developed scAdapt, a virtual adversarial domain adaptation network, to transfer cell labels between datasets with batch effects. scAdapt used both the labeled source and unlabeled target data to train an enhanced classifier and aligned the labeled source centroids and pseudo-labeled target centroids to generate a joint embedding. The scAdapt was demonstrated to outperform existing methods for classification in simulated, cross-platforms, cross-species, spatial transcriptomic and COVID-19 immune datasets. Further quantitative evaluations and visualizations for the aligned embeddings confirm the superiority in cell mixing and the ability to preserve discriminative cluster structure present in the original datasets.