1. |
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2. |
- Luo, Yifei, et al.
(author)
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Technology Roadmap for Flexible Sensors
- 2023
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In: ACS Nano. - : American Chemical Society. - 1936-0851 .- 1936-086X. ; 17:6, s. 5211-5295
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Research review (peer-reviewed)abstract
- Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.
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3. |
- Kreiberg, David, 1971-
(author)
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A covariance structure analysis approach to the errors-in-variables estimation problem
- 2022
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Doctoral thesis (other academic/artistic)abstract
- It is a well-known fact that standard regression techniques, when applied to errors-in-variables (EIV) models, lead to biased and inconsistent parameter estimation. The work presented in this thesis address the EIV estimation problem using covariance structure analysis (CSA). When performing CSA, the standard implementation of the minimum distance (MD) estimator is to apply computationally demanding nonlinear least squares (NLLS). This thesis provides a solution to this problem by proposing a computationally less demanding separable nonlinear least squares (SNLLS) implementation of the estimator.The thesis consists of four papers. The first paper presents a covariance matching (CM) approach for identifying the single-input single-output (SISO) EIV model. The outlined approach extends previous known results by deriving an asymptotic covariance matrix of the jointly estimated system parameters, noise variances and auxiliary parameters. The second paper introduces two formulations of the SISO EIV model using structural equation modeling (SEM). The two formulations allow for quick implementation using standard SEM-based software. The third paper propose a numerically more efficient implementation of the MD estimator for estimating confirmatory factor analysis (CFA) models. The implementation uses an SNLLS approach, which allows part of the parameter vector to be estimated using numerically efficient linear techniques. The fourth and final paper presents a CFA-EIV modeling approach that allows for colored output noise. The presentation extends previous work by including a detailed treatment of the theoretical aspects of the MD estimator. All four papers use simulation examples to illustrate the outlined procedures.
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4. |
- Luo, Hao, 1984-
(author)
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Some Aspects on Confirmatory Factor Analysis of Ordinal Variables and Generating Non-normal Data
- 2011
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Doctoral thesis (other academic/artistic)abstract
- This thesis, which consists of five papers, is concerned with various aspects of confirmatory factor analysis (CFA) of ordinal variables and the generation of non-normal data. The first paper studies the performances of different estimation methods used in CFA when ordinal data are encountered. To take ordinality into account the four estimation methods, i.e., maximum likelihood (ML), unweighted least squares, diagonally weighted least squares, and weighted least squares (WLS), are used in combination with polychoric correlations. The effect of model sizes and number of categories on the parameter estimates, their standard errors, and the common chi-square measure of fit when the models are both correct and misspecified are examined. The second paper focuses on the appropriate estimator of the polychoric correlation when fitting a CFA model. A non-parametric polychoric correlation coefficient based on the discrete version of Spearman's rank correlation is proposed to contend with the situation of non-normal underlying distributions. The simulation study shows the benefits of using the non-parametric polychoric correlation under conditions of non-normality. The third paper raises the issue of simultaneous factor analysis. We study the effect of pooling multi-group data on the estimation of factor loadings. Given the same factor loadings but different factor means and correlations, we investigate how much information is lost by pooling the groups together and only estimating the combined data set using the WLS method. The parameter estimates and their standard errors are compared with results obtained by multi-group analysis using ML. The fourth paper uses a Monte Carlo simulation to assess the reliability of the Fleishman's power method under various conditions of skewness, kurtosis, and sample size. Based on the generated non-normal samples, the power of D'Agostino's (1986) normality test is studied. The fifth paper extends the evaluation of algorithms to the generation of multivariate non-normal data. Apart from the requirement of generating reliable skewness and kurtosis, the generated data also need to possess the desired correlation matrices. Four algorithms are investigated in terms of simplicity, generality, and reliability of the technique.
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5. |
- Vegelius, Johan, 1981-
(author)
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Estimation of Nonlinear Latent Variable and Mixture Models
- 2022
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Doctoral thesis (other academic/artistic)abstract
- In this thesis methods are developed for estimation of latent variable models. In particular nonlinear structural equation models are estimated in the presence of ordinal data and mixture models for count data. Paper I introduces an extended nonlinear structural model which allows for interactions between exogenous and endogenous latent variables in the presence of ordinal data. The adaptive Gauss-Hermite quadrature (AGHQ) and Laplace approximations are used to approximate intractable integrals.Paper II introduces a semiparametric approach for modeling a flexible nonlinear structural model in the presence of ordinal data. Intractable integrals are approximated by the AGHQ approximation.Paper III investigates and compares the error rates of three versions of the AGHQ approximation.Paper IV develops an extreme value and zero inflated regression model for modeling of count data which includes a proportion of excess zeroes and extreme values. This is a typical situation when modeling the number of fatalities in armed conflicts.
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6. |
- Yang, Fan, 1988-
(author)
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Biophysical chemistry of the ALS-associated protein SOD1 : Implications for folding, aggregation and in-cell behaviour
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Biophysical chemistry deals with the structural behavior, properties and molecular function of biological macromolecules. A long-standing challenge is here to establish how these macromolecular features change upon transfer from simplified conditions in vitro to the crowded and molecularly complex environment of live cells. This thesis focuses on establishing a general overview of the structural behavior and interaction properties of the ALS-associated protein superoxide dismutase 1 (SOD1) in its natural cellular environment. Importantly, SOD1 constitutes also a multifaceted model system for the yet poorly understood mechanism of protein-aggregation disease, since it is readily amenable to protein-engineering analysis. The focus is on (i) SOD1 folding, (ii) the modulation of the SOD1 properties induced by intracellular interactions and (iii) the process of SOD1 fibrillation, all of which central to the understanding of the ALS disease mechanism. First, we investigate the biophysical role of the disordered catalytic loops in the apoSOD1 monomer, what is identified as the primary aggregation precursor. The results show that these loops play a pivotal role in modulation the apoSOD1 stability due to the generic Flory-entropy penalty, shedding new light to why this species is biased to be aggregation prone. Second, we target the diffusive interactions between SOD1 and the crowded intracellular environment by in-cell NMR. Our findings are that both the rotational tumbling and in-cell stability are controlled by basic physicochemical rules relating to the SOD1 surface properties. Finally, we analyze the kinetics of the SOD1-aggregation behavior in vitro. The observations confirm that the disordered SOD1 loops indeed accelerate the aggregation process because of their penalty to the apo state stability and show, additionally, that they influence the fibril stability.The physicochemical cues exposed by this thesis work provide not only fundamental clues to our understanding of protein properties, but shed also new light on disease-promoting properties ALS-associated protein SOD1.
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7. |
- Andersson, Björn, 1984-
(author)
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Contributions to Kernel Equating
- 2014
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Doctoral thesis (other academic/artistic)abstract
- The statistical practice of equating is needed when scores on different versions of the same standardized test are to be compared. This thesis constitutes four contributions to the observed-score equating framework kernel equating.Paper I introduces the open source R package kequate which enables the equating of observed scores using the kernel method of test equating in all common equating designs. The package is designed for ease of use and integrates well with other packages. The equating methods non-equivalent groups with covariates and item response theory observed-score kernel equating are currently not available in any other software package.In paper II an alternative bandwidth selection method for the kernel method of test equating is proposed. The new method is designed for usage with non-smooth data such as when using the observed data directly, without pre-smoothing. In previously used bandwidth selection methods, the variability from the bandwidth selection was disregarded when calculating the asymptotic standard errors. Here, the bandwidth selection is accounted for and updated asymptotic standard error derivations are provided.Item response theory observed-score kernel equating for the non-equivalent groups with anchor test design is introduced in paper III. Multivariate observed-score kernel equating functions are defined and their asymptotic covariance matrices are derived. An empirical example in the form of a standardized achievement test is used and the item response theory methods are compared to previously used log-linear methods.In paper IV, Wald tests for equating differences in item response theory observed-score kernel equating are conducted using the results from paper III. Simulations are performed to evaluate the empirical significance level and power under different settings, showing that the Wald test is more powerful than the Hommel multiple hypothesis testing method. Data from a psychometric licensure test and a standardized achievement test are used to exemplify the hypothesis testing procedure. The results show that using the Wald test can provide different conclusions to using the Hommel procedure.
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8. |
- Andersson, Gustaf, et al.
(author)
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Generalized Linear Factor Score Regression : A Comparison of Four Methods
- 2021
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In: Educational and Psychological Measurement. - : Sage Publications. - 0013-1644 .- 1552-3888. ; 81:4, s. 617-643
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Journal article (peer-reviewed)abstract
- Factor score regression has recently received growing interest as an alternative for structural equation modeling. However, many applications are left without guidance because of the focus on normally distributed outcomes in the literature. We perform a simulation study to examine how a selection of factor scoring methods compare when estimating regression coefficients in generalized linear factor score regression. The current study evaluates the regression method and the correlation-preserving method as well as two sum score methods in ordinary, logistic, and Poisson factor score regression. Our results show that scoring method performance can differ notably across the considered regression models. In addition, the results indicate that the choice of scoring method can substantially influence research conclusions. The regression method generally performs the best in terms of coefficient and standard error bias, accuracy, and empirical Type I error rates. Moreover, the regression method and the correlation-preserving method mostly outperform the sum score methods.
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9. |
- Bali Swain, Ranjula, 1968-, et al.
(author)
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Does Foreign Aid Improve Gender Performance In Recipient Countries?
- 2020
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In: Journal of International Development. - : Wiley. - 0954-1748 .- 1099-1328. ; 32:7, s. 1171-1193
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Journal article (peer-reviewed)abstract
- An explicit goal of foreign aid is to promote female empowerment and gender equality in developing countries. We investigate if foreign aid achieves this intended goal by examining its impact on the gender performance of recipient countries at the country level. Employing structural equation models, our results suggest that aid alone, even when targeted to directly improve gender outcomes, is unlikely to shift systemic inequalities. Aid will need to bolster civil society efforts that challenge institutional structures and norms in order to impact gender outcomes at the country level.
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10. |
- Bali Swain, Ranjula, et al.
(author)
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The impact of microfinance on factors empowering women : Differences in regional and delivery mechanisms in India’s SHG programme
- 2017
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In: Journal of Development Studies. - : Routledge. - 0022-0388 .- 1743-9140. ; 53:5, s. 684-699
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Journal article (peer-reviewed)abstract
- We examine how the impact on women empowerment varies with respect to the location and type of group linkage of the respondent. Using household survey data from five states in India, we correct for selection bias to estimate a structural equation model. Our results reveal that in the southern states of India empowerment of women takes place through economic factors. For the other states, we find a significant correlation between women empowerment and autonomy in women’s decision-making and network, communication and political participation respectively. We do not however find any differential causal impact of different delivery methods (linkage models).
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11. |
- Fan, Xuelong, et al.
(author)
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Ergonomics and performance of using prismatic loupes in simulated surgical tasks among surgeons – a randomized controlled, cross-over trial
- 2023
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In: Frontiers in Public Health. - : Frontiers Media SA. - 2296-2565. ; 11
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Journal article (peer-reviewed)abstract
- Introduction: Recently developed prismatic loupes may mitigate the high physical workload and risk of neck disorders associated with traditional surgical loupes among surgeons. However, research in this area, particularly among surgeons, is sparse. This study examines the impact of prismatic loupes on surgeons’ physical workload, musculoskeletal discomfort, and performance during simulated surgical tasks. Materials and methods: Nineteen out of twenty recruited surgeons performed three tasks in a fixed-order with their own loupes and both low-tilt (LT) and high-tilt (HT) prismatic loupes, in a randomized order. The primary outcomes were the median inclination angles and velocities of the head, trunk, and upper arms, along with the median muscle activity of the cervical erector spinae (CES), upper trapezius (UT), and lumbar erector spinae (LES) for each pair of loupes. The secondary outcomes included performance (completion time and errors), perceived body-part discomfort, and subjective evaluation of the three pairs of loupes. Results: Using prismatic loupes, either LT or HT, compared with the surgeons’ own loupes yielded lower head inclinations (all p < 0.001), lower neck muscle activity (all p < 0.05), and lower neck discomfort in indirect comparisons (p < 0.01) with no significant difference in surgical errors (p = 0.628). However, HT loupes resulted in a longer task completion time in two tasks (p < 0.001). Most surgeons preferred LT loupes (N = 12) for their comfort and visual functions. Discussion: The results indicate that prismatic loupes can reduce physical workload in the neck during simulated surgical task, with no significant difference in surgical errors. Future studies are needed to investigate the long-term effects of prismatic loupes among surgeons.
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12. |
- Fan, X., et al.
(author)
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Surgeons’ physical workload in open surgery versus robot-assisted surgery and nonsurgical tasks
- 2022
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In: Surgical Endoscopy. - : Springer Nature. - 0930-2794 .- 1432-2218. ; 36:11, s. 8178-8194
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Journal article (peer-reviewed)abstract
- Background: Musculoskeletal disorders (MSDs) are common among surgeons, and its prevalence varies among surgical modalities. There are conflicting results concerning the correlation between adverse work exposures and MSD prevalence in different surgical modalities. The progress of rationalization in health care may lead to job intensification for surgeons, but the literature is scarce regarding to what extent such intensification influences the physical workload in surgery. The objectives of this study were to quantify the physical workload in open surgery and compare it to that in (1) nonsurgical tasks and (2) two surgeon roles in robot-assisted surgery (RAS). Methods: The physical workload of 22 surgeons (12 performing open surgery and 10 RAS) was measured during surgical workdays, which includes trapezius muscle activity from electromyography, and posture and movement of the head, upper arms and trunk from inertial measurement units. The physical workload of surgeons in open surgery was compared to that in nonsurgical tasks, and to the chief and assistant surgeons in RAS, and to the corresponding proposed action levels. Mixed-effects models were used to analyze the differences. Results: Open surgery constituted more than half of a surgical workday. It was associated with more awkward postures of the head and trunk than nonsurgical tasks. It was also associated with higher trapezius muscle activity levels, less muscle rest time and a higher proportion of sustained low muscle activity than nonsurgical tasks and the two roles in RAS. The head inclination and trapezius activity in open surgery exceeded the proposed action levels. Conclusions: The physical workload of surgeons in open surgery, which exceeded the proposed action levels, was higher than that in RAS and that in nonsurgical tasks. Demands of increased operation time may result in higher physical workload for open surgeons, which poses an increased risk of MSDs. Risk-reducing measures are, therefore, needed.
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13. |
- Hao, Wende, et al.
(author)
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Vitronectin : a promising breast cancer serum biomarker for early diagnosis of breast cancer in patients
- 2016
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In: Tumor Biology. - : Springer. - 1010-4283 .- 1423-0380. ; 37:7, s. 8909-8916
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Journal article (peer-reviewed)abstract
- Breast cancer is the most common cancer in women worldwide, identification of new biomarkers for early diagnosis and detection will improve the clinical outcome of breast cancer patients. In the present study, we determined serum levels of vitronectin (VN) in 93 breast cancer patients, 30 benign breast lesions, 9 precancerous lesions, and 30 healthy individuals by enzyme-linked immunosorbent assays. Serum VN level was significantly higher in patients with stage 0-I primary breast cancer than in healthy individuals, patients with benign breast lesion or precancerous lesions, as well as those with breast cancer of higher stages. Serum VN level was significantly and negatively correlated with tumor size, lymph node status, and clinical stage (p < 0.05 in all cases). In addition, VN displayed higher area under curve (AUC) value (0.73, 95 % confidence interval (CI) [0.62-0.84]) than carcinoembryonic antigen (CEA) (0.64, 95 % CI [0.52-0.77]) and cancer antigen 15-3 (CA 15-3) (0.69, 95 % CI [0.58-0.81]) when used to distinguish stage 0-I cancer and normal control. Importantly, the combined use of three biomarkers yielded an improvement in receiver operating characteristic curve with an AUC of 0.83, 95 % CI [0.74-0.92]. Taken together, our current study showed for the first time that serum VN is a promising biomarker for early diagnosis of breast cancer when combined with CEA and CA15-3.
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14. |
- Jin, Shaobo, 1987-, et al.
(author)
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A unified model-implied instrumental variable approach for structural equation modeling with mixed variables
- 2021
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In: Psychometrika. - : Springer Nature. - 0033-3123 .- 1860-0980. ; 86:2, s. 564-594
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Journal article (peer-reviewed)abstract
- The model-implied instrumental variable (MIIV) estimator is an equation-by-equation estimator of structural equation models that is more robust to structural misspecifications than full information estimators. Previous studies have concentrated on endogenous variables that are all continuous (MIIV-2SLS) or all ordinal . We develop a unified MIIV approach that applies to a mixture of binary, ordinal, censored, or continuous endogenous observed variables. We include estimates of factor loadings, regression coefficients, variances, and covariances along with their asymptotic standard errors. In addition, we create new goodness of fit tests of the model and overidentification tests of single equations. Our simulation study shows that the proposed MIIV approach is more robust to structural misspecifications than diagonally weighted least squares (DWLS) and that both the goodness of fit model tests and the overidentification equations tests can detect structural misspecifications. We also find that the bias in asymptotic standard errors for the MIIV estimators of factor loadings and regression coefficients are often lower than the DWLS ones, though the differences are small in large samples. Our analysis shows that scaling indicators with low reliability can adversely affect the MIIV estimators. Also, using a small subset of MIIVs reduces small sample bias of coefficient estimates, but can lower the power of overidentification tests of equations.
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15. |
- Jin, Shaobo, 1987-, et al.
(author)
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Robust nonlinear structural equation modeling with interaction between exogenous and endogenous latent variables
- 2021
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In: Structural Equation Modeling. - : Taylor & Francis Group. - 1070-5511 .- 1532-8007. ; 28:4, s. 547-556
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Journal article (peer-reviewed)abstract
- A handful of studies have been devoted to nonlinear structural equation modeling (SEM) in the literature. However, they generally overlooked the interactions among exogenous and endogenous latent variables and the interactions among endogenous latent variables. In this study, we propose a maximum likelihood approach for a nonlinear SEM model that incorporates such overlooked interactions. We also propose a two-stage pseudo maximum likelihood approach under the assumption of a normal mixture, being computationally efficient and robust against distributional misspecification. The simulation study shows that both approaches accurately estimate the unknown parameters if the distribution is correctly specified. However, only the pseudo maximum likelihood approach is robust against distributional misspecification.
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16. |
- Persson, Inger, et al.
(author)
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Confirming the Structure of the Survey of Attitudes Toward Statistics (SATS-36) by Swedish Students
- 2019
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In: Statistics Education Research Journal. - : International Association for Statistical Education. - 1570-1824. ; 18:1, s. 83-93
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Journal article (peer-reviewed)abstract
- Research on students’ attitudes toward statistics has attracted many statistics instructors and statistics education researchers. In this study, we use confirmatory factor analysis to analyze data collected from an introductory statistics course using the Survey of Attitudes toward Statistics. Theresults suggest that the items and six factors are conceptually relevant, confirming the six-factor structure of the pretest version of SATS-36 on this sample of Swedish students, with a few suggested modifications of the original model structure. Two items are excluded from the Difficulty component, two items on the Affect component are allowed to correlate, and two items on the Cognitive competence component are also allowed to correlate.
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17. |
- Wang, Xiaoqin, Docent, 1963-, et al.
(author)
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The statistical evidence missing from the Swedish decision-making of COVID-19 strategy during the early period : A longitudinal observational analysis
- 2022
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In: SSM - Population Health. - : Elsevier. - 2352-8273. ; 18
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Journal article (peer-reviewed)abstract
- A controversy about the Swedish strategy of dealing with COVID-19 during the early period is how decision making was based on evidence, which refers to data and data analysis. During the earliest period of the pandemic, the Swedish decision-making was based on subjective perspective. However, when more data became available, the decision-making stood on mathematical and descriptive analyses. The mathematical analysis aimed to model the condition for herd immunity while the descriptive analysis compared different measures without adjustment of population differences and updating pandemic situations. Due to the dubious interpretations of these analyses, a mild measure was adopted in Sweden upon the arrival of the second wave, leading to a surge of poor public health outcomes compared to the other Nordic countries (Denmark, Norway, and Finland). In this article, using data available during the first wave, we conduct longitudinal analysis to investigate the consequence of the shred of evidence in the Swedish decision-making for the first wave, where the study period is between January 2020 and August 2020. The design is longitudinal observational study. The linear regressions based on the Poisson distribution and the binomial distribution are employed for the analysis. We found that the early Swedish measure had a long-term and significant effect on general mortality and COVID19 mortality and a certain mitigating effect on unemployment in Sweden during the first wave; here, the effect was measured by an increase of general deaths, COVID-19 deaths or unemployed persons under Swedish measure relative to the measures adopted by the other Nordic countries. These pieces of statistical evidence were not studied in the mathematical and descriptive analyses but could play an important role in the decision-making at the second wave. In conclusion, a timely longitudinal analysis should be part of the decision-making process for containing the current pandemic or a future one.
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18. |
- Xie, Yuan, et al.
(author)
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Wnt signaling regulates MFSD2A-dependent drug delivery through endothelial transcytosis in glioma
- 2023
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In: Neuro-Oncology. - : Oxford University Press. - 1522-8517 .- 1523-5866. ; 25:6, s. 1073-1084
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Journal article (peer-reviewed)abstract
- Background: Systemic delivery of anti-tumor therapeutic agents to brain tumors is thwarted by the blood-brain barrier (BBB), an organotypic specialization of brain endothelial cells (ECs). A failure of pharmacological compounds to cross BBB is one culprit for the dismal prognosis of glioblastoma (GBM) patients. Identification of novel vascular targets to overcome the challenges posed by the BBB in tumors for GBM treatment is urgently needed.Methods: Temozolomide (TMZ) delivery was investigated in CT2A and PDGFB-driven RCAS/tv-a orthotopic glioma models. Transcriptome analysis was performed on ECs from murine gliomas. Mfsd2a deficient, Cav1 deficient, and Mfsd2a EC-specific inducible mice were developed to study the underlying molecular mechanisms.Results: We demonstrated that inhibiting Wnt signaling by LGK974 could increase TMZ delivery and sensitize glioma to chemotherapy in both murine glioma models. Transcriptome analysis of ECs from murine gliomas revealed that Wnt signaling inhibition enhanced vascular transcytosis as indicated by the upregulation of PLVAP and downregulation of MFSD2A. Mfsd2a deficiency in mice enhances TMZ delivery in tumors, whereas constitutive expression of Mfsd2a in ECs suppresses the enhanced TMZ delivery induced by Wnt pathway inhibition in murine glioma. In addition, Wnt signaling inhibition enhanced caveolin-1 (Cav1)-positive caveolae-mediated transcytosis in tumor ECs. Moreover, Wnt signaling inhibitor or Mfsd2a deficiency fails to enhance TMZ penetration in tumors from Cav1-deficient mice.Conclusions: These results demonstrated that Wnt signaling regulates MFSD2A-dependent TMZ delivery through a caveolae-mediated EC transcytosis pathway. Our findings identify Wnt signaling as a promising therapeutic target to improve drug delivery for GBM treatment.
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19. |
- Yang, Fan, et al.
(author)
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Dissipative boundary state preparation
- 2023
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In: Physical Review Research. - 2643-1564. ; 5:4
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Journal article (peer-reviewed)abstract
- We devise a generic and experimentally accessible recipe to prepare boundary states of topological or nontopological quantum systems through an interplay between coherent Hamiltonian dynamics and local dissipation. Intuitively, our recipe harnesses the spatial structure of boundary states which vanish on sublattices where losses are suitably engineered. This yields unique nontrivial steady states that populate the targeted boundary states with infinite lifetimes while all other states are exponentially damped in time. Remarkably, applying loss only at one boundary can yield a unique steady state localized at the very same boundary. We detail our construction and rigorously derive full Liouvillian spectra and dissipative gaps in the presence of a spectral mirror symmetry for a one-dimensional Su-Schrieffer-Heeger model and a two-dimensional Chern insulator. We outline how our recipe extends to generic noninteracting systems.
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20. |
- Yang, Fan, 1988-, et al.
(author)
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Liouvillian skin effect in an exactly solvable model
- 2022
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In: Physical Review Research. - 2643-1564. ; 4:2
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Journal article (peer-reviewed)abstract
- The interplay between dissipation, topology, and sensitivity to boundary conditions has recently attracted tremendous amounts of attention at the level of effective non-Hermitian descriptions. Here we exactly solve a quantum mechanical Lindblad master equation describing a dissipative topological Su-Schrieffer-Heeger (SSH) chain of fermions for both open boundary condition (OBC) and periodic boundary condition (PBC). We find that the extreme sensitivity on the boundary conditions associated with the non-Hermitian skin effect is directly reflected in the rapidities governing the time evolution of the density matrix giving rise to a Liouvillian skin effect. This leads to several intriguing phenomena including boundary sensitive damping behavior, steady state currents in finite periodic systems, and diverging relaxation times in the limit of large systems. We illuminate how the role of topology in these systems differs in the effective non-Hermitian Hamiltonian limit and the full master equation framework.
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21. |
- Yang, Zhikai, et al.
(author)
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3D Breast Ultrasound Image Classification Using 2.5D Deep learning
- 2024
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In: 17th International Workshop on Breast Imaging, IWBI 2024. - : SPIE.
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Conference paper (peer-reviewed)abstract
- The 3D breast ultrasound is a radiation-free and effective imaging technology for breast tumor diagnosis. However, checking the 3D breast ultrasound is time-consuming compared to mammograms. To reduce the workload of radiologists, we proposed a 2.5D deep learning-based breast ultrasound tumor classification system. First, we used the pre-trained STU-Net to finetune and segment the tumor in 3D. Then, we fine-tuned the DenseNet-121 for classification using the 10 slices with the biggest tumoral area and their adjacent slices. The Tumor Detection, Segmentation, and Classification on Automated 3D Breast Ultrasound (TDSC-ABUS) MICCAI Challenge 2023 dataset was used to train and validate the performance of the proposed method. Compared to a 3D convolutional neural network model and radiomics, our proposed method has better performance.
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22. |
- Yang, Zhikai, et al.
(author)
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Lesion Localization in Digital Breast Tomosynthesis with Deformable Transformers by Using 2.5D Information
- 2024
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In: Medical Imaging 2024: Computer-Aided Diagnosis. - : SPIE-Intl Soc Optical Eng.
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Conference paper (peer-reviewed)abstract
- In this study, we adapted a transformer-based method to localize lesions in digital breast tomosynthesis (DBT) images. Compared with convolutional neural network-based object detection methods, the transformer-based method does not require non-maximum suppression postprocessing. Integrated deformable convolution detection transformers can better capture small-size lesions. We added transfer learning to tackle the issue of the lack of annotated data from DBT. To validate the superiority of the transformer-based detection method, we compared the results with deep-learning object detection methods. The experimental results demonstrated that the proposed method performs better than all comparison methods.
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