Marco Longfils - Academia.edu (original) (raw)
Papers by Marco Longfils
Image Analysis & Stereology, 2015
How to measure the incremental Return On Ad Spend (iROAS) is a fundamental problem for the online... more How to measure the incremental Return On Ad Spend (iROAS) is a fundamental problem for the online advertising industry. A standard modern tool is to run randomized geo experiments, where experimental units are non-overlapping ad-targetable geographical areas [ Vaver and Koehler , 2011 ]. However, how to design a reliable and cost-effective geo experiment can be complicated, for example: 1) the number of geos is often small, 2) the response metric (e.g. revenue) across geos can be very heavy-tailed due to geo heterogeneity, and furthermore 3) the response metric can vary dramatically over time. To address these issues, we propose a robust nonparametric method for the design, called Trimmed Match Design (TMD), which extends the idea of Trimmed Match [ Chen and Au , 2019 ] and furthermore integrates the techniques of optimal subset pairing and sample splitting in a novel and systematic manner. Some simulation and real case studies are presented. We also point out a few open problems fo...
Soft biomaterials are widely used in many application areas, spanning from packaging materials to... more Soft biomaterials are widely used in many application areas, spanning from packaging materials to pharmaceuticals. To enhance their functionalities, understanding the interplay between microstructure and mass transport properties in these materials is fundamental. Consequently, there is a growing need to introduce new and improve existing methods for estimating mass transport heterogeneity in materials with high spatial resolution. In this work, statistical methods are developed for mapping mass transport locally based on raster images collected using a confocal laser scanning microscope.The methods introduced resemble single particle tracking methods, where molecules are identified using image analysis techniques and followed in successive frames of a video to measure their diffusive mobility. Both a maximum likelihood and a centroid-based method have been applied to locate particles and hence to estimate the diffusion coefficient. The method has been generalized to analyse mixture...
Journal of Neurology
Previous studies have shown that the risk of multiple sclerosis (MS) is associated with season of... more Previous studies have shown that the risk of multiple sclerosis (MS) is associated with season of birth with a higher proportion of MS patients being born in spring. However, this relationship has recently been questioned and may be due to confounding factors. Our aim was to assess the influence from season or month of birth on the risk of developing MS in Sweden and Iceland. Information about month of birth, gender, and phenotype of MS for patients born 1940-1996 was retrieved from the Swedish MS registry (SMSR), and their place of birth was retrieved from the Swedish Total Population Registry (TPR). The corresponding information was retrieved from medical journals of Icelandic MS patients born 1981-1996. The control groups consisted of every person born in Sweden 1940-1996, their gender and county of birth (TPR), and in Iceland all persons born between 1981 and 1996 and their gender (Statistics Iceland). We calculated the expected number of MS patients born during each season and in every month and compared it with the observed number. Adjustments were made for gender, birth year, and county of birth. We included 12,020 Swedish and 108 Icelandic MS patients in the analyses. There was no significant difference between expected and observed MS births related to season or month of birth in Sweden or Iceland. This was even the results before adjustments were made for birth year and birth place. No significant differences were found in subgroup analyses including data of latitude of birth, gender, clinical phenotype, and MS onset of 30 years or less. Our results do not support the previously reported association between season or month of birth and MS risk. Analysis of birth place and birth year as possible confounding factors showed no major influence of them on the seasonal MS risk in Sweden and Iceland.
Biophysical Journal
Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracti... more Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 μm2 s-1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (<<50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM-μM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient.
In this work, statistical methods are developed for mapping mass transport locally based on image... more In this work, statistical methods are developed for mapping mass transport locally based on images collected using a confocal laser scanning microscope. Besides presenting raster image correlation spectroscopy as an established method in fluorescence microscopy, we introduce a single particle tracking method which takes advantage of the raster scanning of the image in a confocal microscope. In single particle tracking, particles are identified and followed in consecutive frames of a video to measure their diffusive mobility. Both a maximum likelihood and a centroid-based method have been developed to locate the particles and hence to estimate the diffusion coefficient. The method is generalized to analyse mixtures of particles having different diffusion coefficients. The proposed method allows us to study the entire distribution of diffusion coefficients, enabling the characterization of heterogeneous systems. Motivated by experiments with particle mixtures, we investigate the use o...
Image Analysis & Stereology, 2015
How to measure the incremental Return On Ad Spend (iROAS) is a fundamental problem for the online... more How to measure the incremental Return On Ad Spend (iROAS) is a fundamental problem for the online advertising industry. A standard modern tool is to run randomized geo experiments, where experimental units are non-overlapping ad-targetable geographical areas [ Vaver and Koehler , 2011 ]. However, how to design a reliable and cost-effective geo experiment can be complicated, for example: 1) the number of geos is often small, 2) the response metric (e.g. revenue) across geos can be very heavy-tailed due to geo heterogeneity, and furthermore 3) the response metric can vary dramatically over time. To address these issues, we propose a robust nonparametric method for the design, called Trimmed Match Design (TMD), which extends the idea of Trimmed Match [ Chen and Au , 2019 ] and furthermore integrates the techniques of optimal subset pairing and sample splitting in a novel and systematic manner. Some simulation and real case studies are presented. We also point out a few open problems fo...
Soft biomaterials are widely used in many application areas, spanning from packaging materials to... more Soft biomaterials are widely used in many application areas, spanning from packaging materials to pharmaceuticals. To enhance their functionalities, understanding the interplay between microstructure and mass transport properties in these materials is fundamental. Consequently, there is a growing need to introduce new and improve existing methods for estimating mass transport heterogeneity in materials with high spatial resolution. In this work, statistical methods are developed for mapping mass transport locally based on raster images collected using a confocal laser scanning microscope.The methods introduced resemble single particle tracking methods, where molecules are identified using image analysis techniques and followed in successive frames of a video to measure their diffusive mobility. Both a maximum likelihood and a centroid-based method have been applied to locate particles and hence to estimate the diffusion coefficient. The method has been generalized to analyse mixture...
Journal of Neurology
Previous studies have shown that the risk of multiple sclerosis (MS) is associated with season of... more Previous studies have shown that the risk of multiple sclerosis (MS) is associated with season of birth with a higher proportion of MS patients being born in spring. However, this relationship has recently been questioned and may be due to confounding factors. Our aim was to assess the influence from season or month of birth on the risk of developing MS in Sweden and Iceland. Information about month of birth, gender, and phenotype of MS for patients born 1940-1996 was retrieved from the Swedish MS registry (SMSR), and their place of birth was retrieved from the Swedish Total Population Registry (TPR). The corresponding information was retrieved from medical journals of Icelandic MS patients born 1981-1996. The control groups consisted of every person born in Sweden 1940-1996, their gender and county of birth (TPR), and in Iceland all persons born between 1981 and 1996 and their gender (Statistics Iceland). We calculated the expected number of MS patients born during each season and in every month and compared it with the observed number. Adjustments were made for gender, birth year, and county of birth. We included 12,020 Swedish and 108 Icelandic MS patients in the analyses. There was no significant difference between expected and observed MS births related to season or month of birth in Sweden or Iceland. This was even the results before adjustments were made for birth year and birth place. No significant differences were found in subgroup analyses including data of latitude of birth, gender, clinical phenotype, and MS onset of 30 years or less. Our results do not support the previously reported association between season or month of birth and MS risk. Analysis of birth place and birth year as possible confounding factors showed no major influence of them on the seasonal MS risk in Sweden and Iceland.
Biophysical Journal
Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracti... more Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 μm2 s-1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (<<50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM-μM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient.
In this work, statistical methods are developed for mapping mass transport locally based on image... more In this work, statistical methods are developed for mapping mass transport locally based on images collected using a confocal laser scanning microscope. Besides presenting raster image correlation spectroscopy as an established method in fluorescence microscopy, we introduce a single particle tracking method which takes advantage of the raster scanning of the image in a confocal microscope. In single particle tracking, particles are identified and followed in consecutive frames of a video to measure their diffusive mobility. Both a maximum likelihood and a centroid-based method have been developed to locate the particles and hence to estimate the diffusion coefficient. The method is generalized to analyse mixtures of particles having different diffusion coefficients. The proposed method allows us to study the entire distribution of diffusion coefficients, enabling the characterization of heterogeneous systems. Motivated by experiments with particle mixtures, we investigate the use o...