A conventional lens has well-defined transfer function with which we can form an image of a target object. On the contrary, scattering media such as biological tissues, multimode optical fibers and ...layers of disordered nanoparticles have highly complex transfer function, which makes them impractical for the general imaging purpose. In recent studies, we presented a method of experimentally recording the transmission matrix of such media, which is a measure of the transfer function. In this review paper, we introduce two major applications of the transmission matrix: enhancing light energy delivery and imaging through scattering media. For the former, we identified the eigenchannels of the transmission matrix with large eigenvalues and then coupled light to those channels in order to enhance light energy delivery through the media. For the latter, we solved matrix inversion problem to reconstruct an object image from the distorted image by the scattering media. We showed the enlargement of the numerical aperture of imaging systems with the use of scattering media and demonstrated endoscopic imaging through a single multimode optical fiber working in both reflectance and fluorescence modes. Our approach will pave the way of using scattering media as unique optical elements for various biophotonics applications.
Understanding the role of genes in human disease is of high importance. However, identifying genes associated with human diseases requires laborious experiments that involve considerable effort and ...time. Therefore, a computational approach to predict candidate genes related to complex diseases including cancer has been extensively studied. In this study, we propose a convolutional neural network-based knowledge graph-embedding model (KGED), which is based on a biological knowledge graph with entity descriptions to infer relationships between biological entities. As an application demonstration, we generated gene-interaction networks for each cancer type using gene-gene relationships inferred by KGED. We then analyzed the constructed gene networks using network centrality measures, including betweenness, closeness, degree, and eigenvector centrality metrics, to rank the central genes of the network and identify highly correlated cancer genes. Furthermore, we evaluated our proposed approach for prostate, breast, and lung cancers by comparing the performance with that of existing approaches. The KGED model showed improved performance in predicting cancer-related genes using the inferred gene-gene interactions. Thus, we conclude that gene-gene interactions inferred by KGED can be helpful for future research, such as that aimed at future research on pathogenic mechanisms of human diseases, and contribute to the field of disease treatment discovery.
Thermal response tests (TRTs) have been conducted to evaluate two design parameters of borehole heat exchangers (BHEs): effective thermal conductivity and borehole thermal resistance. The effect of ...natural convection on groundwater-filled BHE performance has been reported mainly from northern Europe. Even in a backfilled or grouted BHE, if the formation is saturated and composed of porous medium, the estimation may depend on the heat injection rate. In this study, we experimentally examined the effect of natural convection on TRTs conducted in saturated porous formation. TRTs were conducted with two BHEs having the same geometry but different backfill materials: one was cement-grouted and the other was gravel-backfilled. TRTs were conducted for each BHE at two different heat injection rates (approximately 45 W/m and 90 W/m). The TRT data were analyzed by a parameter estimation method using a temporal superposition-applied infinite line source model. The results show that when the heat rate was almost doubled, the borehole thermal resistances of the gravel-backfilled and cement-grouted BHEs decreased by 9.8% and 8.7%, respectively. Based on the results, discussions on existing design methods related to typical practices in TRTs and advantages of backfilled BHEs from the perspectives of performance and constructability are presented.
•Performance dependence of BHEs on heat injection rate was studied.•Gravel-backfilled and cement-grouted BHEs were installed for TRT.•Doubling the heat rate reduced borehole thermal resistance of gravel-BHE by 9.8%.•For cement-grouted BHE, the corresponding reduction was 8.7%.•Current design methods of typical practices in thermal response test are discussed.
•Bayesian inference for TRT parameters and uncertainty assessment was proposed.•Not only point estimates of parameters but also credible intervals can be extracted.•Numerical TRT and sandbox TRT data ...were used to verify the proposed method.•Our method was used to examine the relationship between uncertainty and TRT time.•Estimation uncertainty decreased exponentially with increasing time: <10% for 50 h.
The effective ground thermal conductivity and borehole thermal resistance constitute information needed to design a ground-source heat pump (GSHP). In situ thermal response tests (TRTs) are considered reliable to obtain these parameters, but interpreting TRT data by a deterministic approach may result in significant uncertainties in the estimates. In light of the impact of the two parameters on GSHP applications, the quantification of uncertainties is necessary. For this purpose, in this study, we develop a stochastic method based on Bayesian inference to estimate the two parameters and associated uncertainties. Numerically generated noisy TRT data and reference sandbox TRT data were used to verify the proposed method. The posterior probability density functions obtained were used to extract the point estimates of the parameters and their credible intervals. Following its verification, the proposed method was applied to in situ TRT data, and the relationship between test time and estimation accuracy was examined. The minimum TRT time of 36 h recommended by ASHRAE produced an uncertainty of ∼±21% for effective thermal conductivity. However, the uncertainty of estimation decreased exponentially with increasing TRT time, and was ±8.3% after a TRT time of 54 h, lower than the generally acceptable range of uncertainty of ±10%. Based on the obtained results, a minimum TRT time of 50 h is suggested and that of 72 h is expected to produce sufficiently accurate estimates for most cases.
The approximated infinite line source (ILS) model is widely used to interpret thermal response tests (TRTs). It assumes a constant heat flux from the source. However, this assumption is violated in ...real field conditions by the heat exchange between the circulating fluid and the outdoor environment in an above-ground TRT setup. This results in a fluctuating behavior of sequential estimation and estimation error. In this study, we quantitatively examined the effect of disturbance from outdoor environment on TRTs, especially when TRTs are interpreted by the ILS model, using numerical methods. An analytical model that takes disturbance into account was incorporated as the boundary condition of a numerical model. Using typical synthetic weather data of different seasons and 36 cases of measured weather data, numerical TRTs were conducted and interpreted. Some characteristic behavior of interpretation related to weather conditions was explained and changes in error range with testing duration were analyzed to clarify the applicability and limitation of the interpretation using the ILS model. The results showed that at least 60 h of TRT is required to obtain results within the error range of ±5% compared with the reference case. Additionally, some practical suggestions regarding conducting and interpreting TRTs are provided.
•Numerical model considering disturbance in an above-ground TRT setup was developed.•The developed numerical model is validated against in situ TRT data.•Numerical TRTs using 36 cases of weather data were conducted.•Applicability and limitation of the ILS model for the interpretation are described.•Based on the results, suggestions on conducting and interpreting TRTs are provided.
In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles. After NER is ...applied to articles, the next step is to normalize the identified names into standard concepts (i.e., disease names are mapped to the National Library of Medicine's Medical Subject Headings disease terms). In biomedical articles, many entity normalization methods rely on domain-specific dictionaries for resolving synonyms and abbreviations. However, the dictionaries are not comprehensive except for some entities such as genes. In recent years, biomedical articles have accumulated rapidly, and neural network-based algorithms that incorporate a large amount of unlabeled data have shown considerable success in several natural language processing problems.
In this study, we propose an approach for normalizing biological entities, such as disease names and plant names, by using word embeddings to represent semantic spaces. For diseases, training data from the National Center for Biotechnology Information (NCBI) disease corpus and unlabeled data from PubMed abstracts were used to construct word representations. For plants, a training corpus that we manually constructed and unlabeled PubMed abstracts were used to represent word vectors. We showed that the proposed approach performed better than the use of only the training corpus or only the unlabeled data and showed that the normalization accuracy was improved by using our model even when the dictionaries were not comprehensive. We obtained F-scores of 0.808 and 0.690 for normalizing the NCBI disease corpus and manually constructed plant corpus, respectively. We further evaluated our approach using a data set in the disease normalization task of the BioCreative V challenge. When only the disease corpus was used as a dictionary, our approach significantly outperformed the best system of the task.
The proposed approach shows robust performance for normalizing biological entities. The manually constructed plant corpus and the proposed model are available at http://gcancer.org/plant and http://gcancer.org/normalization , respectively.
Mineralized eggshell is a unique and protective structure in an avian egg. Among different eggshell layers, the cuticle layer is an outermost layer and plays a critical role in protection against ...bacterial infection. Although the importance of nanosphere in the cuticle layer on the antimicrobial function has been widely accepted, the detailed nanostructure of the cuticle layer in the major poultry species has not been investigated. In the current study, eggs from Japanese quail, commercial layer chickens, mixed breed turkeys, and White Pekin ducks were collected. To investigate the nanostructure throughout the cuticle layer, images of the cross-sectional cuticle layer were taken using a scanning electron microscope (SEM). Unlike the cuticle layer in ducks showing deformed bunched nanospheres, clearly separated nanospheres were present throughout the cuticle layer in quail, chickens, and turkeys. The average size of the nanosphere was the biggest in turkeys and similar between quail and chickens. Most importantly, the size of nanospheres was increased as they ascended from the bottom of the cuticle layer in quail, showing a positive correlation between the size and distance of the nanospheres. However, different sizes of nanospheres were randomly distributed throughout the cuticle layer in chickens and turkeys, showing a weak correlation in chickens and no correlation in turkeys between the size and distance of nanospheres. These new findings in different nanostructures of the cuticle layers in quail, chickens, turkeys, and ducks will serve as a new foundation to better relate their structures with functions.
Abstract
Ultrathin lensless fibre endoscopes offer minimally invasive investigation, but they mostly operate as a rigid type due to the need for prior calibration of a fibre probe. Furthermore, most ...implementations work in fluorescence mode rather than label-free imaging mode, making them unsuitable for general medical diagnosis. Herein, we report a fully flexible ultrathin fibre endoscope taking 3D holographic images of unstained tissues with 0.85-μm spatial resolution. Using a bare fibre bundle as thin as 200-μm diameter, we design a lensless Fourier holographic imaging configuration to selectively detect weak reflections from biological tissues, a critical step for label-free endoscopic reflectance imaging. A unique algorithm is developed for calibration-free holographic image reconstruction, allowing us to image through a narrow and curved passage regardless of fibre bending. We demonstrate endoscopic reflectance imaging of unstained rat intestine tissues that are completely invisible to conventional endoscopes. The proposed endoscope will expedite a more accurate and earlier diagnosis than before with minimal complications.
To interpret thermal response tests (TRTs), analytical models that assume constant heat flux from the source are widely used because of their simplicity. However, in actual field conditions, the ...constant heat flux assumption is violated by the heat exchange between the above-ground TRT setup and outdoor environment. This results in perturbations in the temperature response and causes fluctuations in estimation and consequent estimation errors in the interpretation of TRTs. For a better design of experiments and obtaining quality data from a TRT, a systematic analysis of the disturbance factors is important. In this study, we developed an analytical model that describes the heat exchange in an above-ground TRT setup. On the basis of this model, a parametric study and sensitivity analysis were conducted in a systematic manner using disturbance-related parameters, such as test settings (heat injection rate and flow rate), above-ground connecting circuit parameters (insulation thickness, length, and radiation absorptivity), temperature of fluid, and weather conditions (solar irradiation, environmental temperature, and wind velocity). The above-ground circuit length and parameters related to radiative heat transfer showed the highest sensitivity coefficients. Based on the results, some suggestions are provided for experimenters on designing TRT setups and conducting TRTs to obtain quality data.
•Analytical model with disturbance effect in above-ground TRT setup was developed.•Using the developed model, parametric study and sensitivity analysis were conducted.•Relative impact of each parameter on disturbance in TRT were provided and compared.•Parameters of radiative heat transfer showed the largest sensitivity coefficient.•Suggestions for design and conducting of TRT are provided.
PDF
