ABSTRACT
Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. But PET suffers from a low signal-to-noise ratio, while MRI are time-consuming. To address time-consuming, an effective strategy involves reducing k-space data collection, albeit at the cost of lowering image quality. This study aims to leverage the inherent complementarity within PET-MRI data to enhance the image quality of PET-MRI.Approach. A novel PET-MRI joint reconstruction model, termed MC-Diffusion, is proposed in the Bayesian framework. The joint reconstruction problem is transformed into a joint regularization problem, where data fidelity terms of PET and MRI are expressed independently. The regular term, the derivative of the logarithm of the joint probability distribution of PET and MRI, employs a joint score-based diffusion model for learning. The diffusion model involves the forward diffusion process and the reverse diffusion process. The forward diffusion process adds noise to transform a complex joint data distribution into a known joint prior distribution for PET and MRI simultaneously, resembling a denoiser. The reverse diffusion process removes noise using a denoiser to revert the joint prior distribution to the original joint data distribution, effectively utilizing joint probability distribution to describe the correlations of PET and MRI for improved quality of joint reconstruction.Main results. Qualitative and quantitative improvements are observed with the MC-Diffusion model. Comparative analysis against LPLS and Joint ISAT-net on the ADNI dataset demonstrates superior performance by exploiting complementary information between PET and MRI. The MC-Diffusion model effectively enhances the quality of PET and MRI images.Significance. This study employs the MC-Diffusion model to enhance the quality of PET-MRI images by integrating the fundamental principles of PET and MRI modalities and leveraging their inherent complementarity. Furthermore, utilizing the diffusion model to learn the joint probability distribution of PET and MRI, thereby elucidating their latent correlation, facilitates a more profound comprehension of the priors obtained through deep learning, contrasting with black-box prior or artificially constructed structural similarities.
Subject(s)
Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Positron-Emission Tomography , Image Processing, Computer-Assisted/methods , Humans , Diffusion , Multimodal Imaging , Signal-To-Noise Ratio , Bayes Theorem , Brain/diagnostic imagingABSTRACT
The peripheral retinal refractive state plays an important role in eye growth and development and is closely related to the development of myopia. Existing methods for measuring the peripheral retinal refractive state are cumbersome and can only detect in a limited range. To address the above shortcomings, this paper proposes a retinal refractive state detection method using optical refractive compensation imaging. First, a series of defocus images is captured using an optical system, and then the images are enhanced and filtered. Subsequently, the Sobel function is applied to calculate sharpness, and the asymmetric Gaussian (AG) model is employed for peak fitting, allowing for the determination of the fundus retina's overall refractive compensation value. We performed consistency analysis on the central and peripheral diopters with autorefractor KR-8900 (Topcon, Japan) and WAM-5500 (Grand Seiko, Japan), respectively. The intraclass correlation coefficients (ICCs) are all greater than 0.9, showing good consistency. This is a promising alternative to the current techniques for assessing the refraction of the peripheral retina.
ABSTRACT
There is an urgent need for a mass population screening tool for diabetes. Skin tissue contains a large number of endogenous fluorophores and physiological parameter markers related to diabetes. We built an excitation-emission spectrum measurement system with the excited light sources of 365, 395, 415, 430, and 455 nm to extract skin characteristics. The modeling experiment was carried out to design and verify the accuracy of the recovery of tissue intrinsic discrete three-dimensional fluorescence spectrum. Blood oxygen modeling experiment results indicated the accuracy of the physiological parameter extraction algorithm based on the diffuse reflectance spectrum. A community population cohort study was carried out. The tissue-reduced scattering coefficient and scattering power of the diabetes were significantly higher than normal control groups. The Gaussian multi-peak fitting was performed on each excitation-emission spectrum of the subject. A total of 63 fluorescence features containing information such as Gaussian spectral curve intensity, central wavelength position, and variance were obtained from each person. Logistic regression was used to construct the diabetes screening model. The results showed that the area under the receiver operating characteristic curve of the model for predicting diabetes was 0.816, indicating a high diagnostic value. As a rapid and non-invasive detection method, it is expected to have high clinical value.
Subject(s)
Diabetes Mellitus , Mass Screening , Humans , Cohort Studies , Spectrum Analysis , Skin/diagnostic imaging , Diabetes Mellitus/diagnostic imaging , Spectrometry, Fluorescence/methodsABSTRACT
Pelvic fractures mostly result from high-energy injuries in life; the longitudinal fracture of the sacrum is the most common type of sacrum fracture. This study was designed to evaluate the accuracy, safety, and efficacy of percutaneous sacroiliac joint screw placement in the treatment of longitudinal sacrum fractures with the assistance of unobstructed orthopaedic surgery robots. According to different surgical methods, 32 patients were divided into robot group and free hand group, with 16 patients in each group. The operation time, intra-operative blood loss, intra-operative fluoroscopy times, screw placement angle deviation were collected. There were statistically significant differences in terms of angle deviation of screw placement (1.96 ± 0.75° vs. 2.87 ± 1.03°; p = 0.0145), deviation of the guide needle (1.92 ± 0.93 mm vs. 2.91 ± 1.22 mm; p = 0.0209), intra-operative fluoroscopy time (7.25 ± 1.72 s vs. 20.93 ± 5.64 s; p = 0.0000), insertion time of each sacroiliac joint screw (14.72 ± 2.66 min vs. 29.21 ± 5.18 min; p = 0.0000). There was no statistically significant difference in terms of blood loss (100.21 ± 7.37 mL vs. 102.52 ± 8.15 mL; p = 0.4136). These results suggest that orthopaedic surgery robot for the treatment of longitudinal sacrum fracture is safer and provides less irradiation than the traditional freehand methods.
ABSTRACT
Injectable self-healing hydrogels with antioxidation are required in wound dressings. Because oxidative damage caused by excessive reactive oxygen species (ROS) is a common issue associated with chronic non-healing wounds. Here, collagen (COL) - and hyaluronic acid (HA)-based hydrogel with antioxidant and injectable self-healing mediated with gallic acid (GA) and dopamine (DA) offers unique advantages for wound repair. The hydrogel is constructed by COL-grafted GA (CG), HA-grafted DA (HD) and γ-poly(glutamic acid) (γ-PGA) coupled with 3-aminophenylboric acid (APBA) via the dynamic boronic ester bonds. Rheological measurements and direct visual observation demonstrated the hydrogel's desirable injectability and self-healing properties. Additionally, the hydrogel exhibits tissue adhesion properties. Biocompatibility and cell migration tests showed that the hydrogel promotes cell proliferation and migration. In vitro, antioxidant and intracellular free radical scavenging assays confirmed the hydrogel's antioxidant property and ability to scavenge excess ROS. In vivo wound healing studies have demonstrated that hydrogel can promote angiogenesis, inhibit inflammation, and promote collagen fiber deposition to accelerate wound healing.
Subject(s)
Antioxidants , Prunella , Antioxidants/pharmacology , Gallic Acid/pharmacology , Hyaluronic Acid/pharmacology , Dopamine/pharmacology , Hydrogels/pharmacology , Reactive Oxygen Species , Collagen , Wound HealingABSTRACT
OBJECTIVE: Nanosilver-alginate dressing can effectively promote the healing of diabetic wounds in rats. However, due to the potential toxicity of nanosilver, its widespread application in hard-to-heal wound healing is limited. In the present study, the role and potential mechanism of nanosilver-free alginate gel (NSFAG) in the healing process of diabetic wounds were explored. METHOD: A diabetic rat skin wound model was established, and wounds were treated with saline (NC group), nanosilver gel (NSG group) or nanosilver-free alginate gel (NSFAG group) for seven consecutive days. RESULTS: NSFAG significantly promoted wound healing and increased the content of protein and hydroxyproline in granulation tissues, and was superior to NSG (p<0.05). Immunohistochemical analyses revealed that the skin wound tissue structure of the NSFAG group was intact, and the number of skin appendages in the dermis layer was significantly higher compared with the NC group and the NSG group (p<0.05). Western blot analysis found that the protein expression of the epidermal stem cell marker molecules CK19 and CK14 as well the proliferation marker of keratinocytes Ki67 in the NSFAG group was significantly higher compared with the NC group or NSG group (p<0.05). Additionally, the proliferation marker of keratinocytes Ki67 in the NSFAG group was significantly higher compared with the NC or NSG group (p<0.05). Immunofluorescence staining analyses indicated that the CK19- and CK14-positive cells were mainly distributed around the epidermis and the newly formed appendages in the NSFAG group, and this result was not observed in the NC or NSG groups. CONCLUSION: The present findings demonstrate that NSFAG can effectively accelerate wound healing in diabetic rats by promoting epidermal stem cell proliferation and differentiation into skin cells, as well as formation of granulation tissue, suggesting that it can be a potential dressing for diabetic wounds.
Subject(s)
Diabetes Mellitus, Experimental , Rats , Animals , Alginates/pharmacology , Ki-67 Antigen , Wound Healing , BandagesABSTRACT
Medical image alignment is an important tool for tracking patient conditions, but the quality of alignment is influenced by the effectiveness of low-dose Cone-beam CT (CBCT) imaging and patient characteristics. To address these two issues, we propose an unsupervised alignment method that incorporates a preprocessing super-resolution process. We constructed the model based on a private clinical dataset and validated the enhancement of the super-resolution on alignment using clinical and public data. Through all three experiments, we demonstrate that higher resolution data yields better results in the alignment process. To fully constrain similarity and structure, a new loss function is proposed; Pearson correlation coefficient combined with regional mutual information. In all test samples, the newly proposed loss function obtains higher results than the common loss function and improve alignment accuracy. Subsequent experiments verified that, combined with the newly proposed loss function, the super-resolution processed data boosts alignment, can reaching up to 9.58%. Moreover, this boost is not limited to a single model, but is effective in different alignment models. These experiments demonstrate that the unsupervised alignment method with super-resolution preprocessing proposed in this study effectively improved alignment and plays an important role in tracking different patient conditions over time.
ABSTRACT
Collagen and multifunctional epoxides, which are respectively the common constituents of natural and polymer interfaces, were combined to fabricate integrative biointerfaces with device/tissue heterogeneous affinity. Further, the traditional 2D and advanced 2.5D conformational designs were achieved on collagen-based biointerfaces. The 2D conformational biointerfaces were formed by the self-entanglement of collagen molecules based on extensive hydrogen bonds among molecules, and the lamellar structures of 2D conformational biointerfaces could act as barriers to protect both biointerfaces and substrates from enzymes and corrosion. The unique stacking structures of 2.5D conformational biointerfaces were formed by cross-linking microaggregates that were established and connected by epoxy cross-linking bonds and provided the extra 0.5D degree of freedom on structure design and functional specialization through artificially manipulating the constituents and density of microaggregates. Besides, the intersecting channels among microaggregates gave 2.5D biointerfaces diffusion behaviors, which further brought good wettability and biodegradability. The integrative biointerfaces behaved well on cell viability and enhanced the cell adhesion strength in vitro, which could be attributed to the collaborations of collagen and epoxy groups. The subcutaneous implant model in rats was utilized to investigate soft tissue response, and the results demonstrated that the tissues around implantation areas healed well and without calcification or infection. The coating of integrative biointerfaces alleviated the fibrosis around implantation areas, and the inflammatory responses and foreign body reactions were improved.
Subject(s)
Collagen , Polymers , Rats , Animals , Surface Properties , Wettability , Cell Adhesion , Polymers/chemistryABSTRACT
Ammonia (NH3) plays an important role in the atmospheric environment such as the formation of PM2.5, the concentration monitoring of which could hence help in the air quality assessment. In this study, a method for quantitative monitoring of atmospheric NH3 was developed based on modifier-enhanced selectivity detection using a homemade vacuum ultraviolet photoionization ion mobility spectrometry (VUV-PI-IMS). To enhance the resolution and sensitivity of measuring NH3, 2-butanone as the gas modifier was introduced into the drift tube with the drift gas. Atmospheric NH3 can be selectively detected, where the peak-to-peak resolution (RP-P) of 7.69 was obtained. The product ions were identified to be [C4H8O]2NH4+ by using a homemade time-of-flight mass spectrometer. The calculated limit of detection (LOD) was 0.39 ppbv improving about 10 times. For the most common concentration variation of atmospheric NH3 in the range of 10-100 ppbv, the linear curve was obtained with R2 of 0.997. Lastly, the VUV-PI-IMS was used to monitor the evolution of atmospheric NH3 near our laboratory and mounted on a car for monitoring the regional distribution of atmospheric NH3 in Dalian, China. The results also showed that VUV-PI-IMS has a promising application prospect in monitoring the concentration of atmospheric NH3 and supporting the air quality assessment.
ABSTRACT
In order to enhance cone-beam computed tomography (CBCT) image information and improve the registration accuracy for image-guided radiation therapy, we propose a super-resolution (SR) image enhancement method. This method uses super-resolution techniques to pre-process the CBCT prior to registration. Three rigid registration methods (rigid transformation, affine transformation, and similarity transformation) and a deep learning deformed registration (DLDR) method with and without SR were compared. The five evaluation indices, the mean squared error (MSE), mutual information, Pearson correlation coefficient (PCC), structural similarity index (SSIM), and PCC + SSIM, were used to validate the results of registration with SR. Moreover, the proposed method SR-DLDR was also compared with the VoxelMorph (VM) method. In rigid registration with SR, the registration accuracy improved by up to 6% in the PCC metric. In DLDR with SR, the registration accuracy was improved by up to 5% in PCC + SSIM. When taking the MSE as the loss function, the accuracy of SR-DLDR is equivalent to that of the VM method. In addition, when taking the SSIM as the loss function, the registration accuracy of SR-DLDR is 6% higher than that of VM. SR is a feasible method to be used in medical image registration for planning CT (pCT) and CBCT. The experimental results show that the SR algorithm can improve the accuracy and efficiency of CBCT image alignment regardless of which alignment algorithm is used.
ABSTRACT
The Xinyanggang River in Yancheng City, one of the essential rivers entering the Yellow sea, has imported abundant pollutants to the coast of Jiangsu Province. Trace elements (Cr, Ni, Cu, Zn, As, Rb, Sr, Mo, Pb, Th, U, Sc, Ga, Se, Zr, Nb, and Sn) in surface sediments in the Xinyanggang River were measured to analyze the spatial distribution, risk assessment, and source appointment. The results showed that the parts of 17 trace elements presented high average values in river sediments, such as Zr (309.19 mg/kg), Sr (182.72 mg/kg), Zn (77.67 mg/kg), and Cr (70.63 mg/kg). Compared with some coastal rivers, the Xinyanggang River was polluted by certain trace elements, such as Cr, Zn, and As. Based on the analysis of the enrichment factor (EF), the contamination factor (CF), the pollution load index (PLI), and the geoaccumulation index (Igeo), trace elements in sediments showed unpolluted to moderate contamination and mild to moderate enrichment. Among them, Zn, Pb, and Sn were highly polluted. The multivariate analysis, the principal component analysis-multiple linear regression (APCS-MLR) model, and the Unmix model identified four contributing trace element sources. Cr, Th, U, Se, Zr, and Nb originated from manufacturing industries and hydrodynamic transport erosion. Ni, Rb, Sc, and Ga were attributed to natural source. Cu, Zn, Mo, Pb, and Sn were contributed from mixed sources including industrial wastewater and transportation emissions. As and Sr were associated mainly with mixed sources of agriculture and combustion. These four sources of metals accounted for 22.5 %, 5.7 %, 15.3 %, and 11.1 % by using the APCS-MLR model, whereas 22.9 %, 39.7 %, 17.5 %, and 19.9 % by using the Unmix model, respectively.
Subject(s)
Metals, Heavy , Trace Elements , Water Pollutants, Chemical , Metals, Heavy/analysis , Trace Elements/analysis , Rivers , Lead , Water Pollutants, Chemical/analysis , Geologic Sediments , Environmental Monitoring/methods , China , Risk AssessmentABSTRACT
It is crucial to investigate the distribution and origin of black carbon (BC) in the environment for evaluating human inputs and developing pollution control strategies. This study analyzed BC in coastal river sediments from Haizhou Bay, Eastern China. The concentrations (dry weight) of the BC, char, soot, and total organic carbon (TOC) in coastal river sediments flowing into Haizhou Bay were 0.11-4.68, 0.06-4.24, 0.04-0.70, and 0.15-2.29 mg/g, respectively. Char and soot accounted for 38.54-90.70% and 9.30-61.46% of BC, with an average of 68.95% and 31.05%, respectively. The results show that the spatial variation of char was markedly presented in river sediment (108.27%), followed by that of BC (89.25%), TOC (58.69%), and soot (55.85%). The BC was mainly distributed in the Shawang River and the Shiliang River, soot was distributed primarily in the Shawang River, and char was mainly distributed in the Shiliang River. This finding supports the presence of anthropogenic activity sources in coastal rivers. The grey correlation analysis results show that industrial and agricultural activities greatly influenced BC emissions, as the influence degree of four socio-economic variables on BC contamination decreased as follows: regional total production value, population density, total agricultural production value, and total industrial production value. The char/soot ratio, an index to discriminate the source of BC contamination in sediments, was found to range from 0.63 to 9.75 with an average of 2.75. The result indicates that BC in Haizhou Bay was contributed from mixed sources including transportation emissions, fossil fuel combustion, and biomass combustion. The study demonstrates that BC could be an effective indicator for the degree and spatial distribution of organic pollutants in coastal river sediments.
Subject(s)
Rivers , Soot , Humans , Soot/analysis , Bays , Environmental Monitoring/methods , Carbon/analysis , Geologic Sediments/analysis , ChinaABSTRACT
Most soft actuators have the ability of monotonic responsiveness. That is, there is only one response action after being stimulated once. In this work, a temporarily responsive bilayer hydrogel actuator is designed and fabricated by combining a tertiary amine-containing pH-responsive layer and a urease-containing non-responsive layer. The hydrogel actuator can achieve programed deformation and recovery driven by chemical fuels (i.e., acidic urea solutions), which is essentially regulated by rapid acidification and slow enzymatic production of ammonia for recovering the pH of the system. The actuation extent and duration can be simply controlled by the fuel levels, and the repeated actuations are also possible via refueling. Furthermore, we fabricate several hydrogel devices that can display specific patterns or lift an item. This enzymatic method shows new possibilities to control the temporary actuation of polymer hydrogels potentially useful in many fields such as soft robotics, biomimetic devices, and environmental sensing.
Subject(s)
Biomimetic Materials , Hydrogels , PolymersABSTRACT
Pure fish skin collagen hydrogels as a wound dressing have lower thermodynamic stability than mammalian collagen and usually suffer from poor mechanical properties, weak degradation resistance and insufficient functionalities such as antioxidant and anti-inflammatory properties to meet clinical needs that limit its further application. Here, a silver carp skin collagen hydrogel is successfully constructed via the cross-linking of the laccase-protocatechuic aldehyde (LAC-PAL) and the structure of the hydrogel is further consolidated and strengthened by the interaction of PAL and Fe3+. In this collagen hydrogel system, Fe3+, acting as a second cross-linker, consolidates and enhances the stability of the hydrogel after LAC-PAL cross-linking. This cross-linking method improves the resistance to degradation with a reduction in its degradation rate from 89.45% to 38.66% and endows the hydrogel with antioxidant activity. The in vitro data show that the hydrogel promotes cell proliferation and adhesion exhibiting good biocompatibility. Animal experiments show that the hydrogel contributes to angiogenesis and improves inflammatory response in the early stages of wound healing, resulting in promoting wound healing. Altogether, this newly developed collagen hydrogel is expected to be applied in wound repair as a wound dressing.
ABSTRACT
Objective: To evaluate the biomechanical performances of the sacroiliac screw fixation of the first sacral vertebra with different lengths of screws using the Finite-Element Method. Methods: First, pelvic CT images were generated from a healthy volunteer, and multislice sagittal views were produced to determine the axis for the first sacral vertebra geometric osseous fixation pathway (GOFP). Subsequently, according to the geometric size and mechanical parameters of the iliosacral screw, the screw models with the same diameter of 7.3 mm and different lengths of 80 mm, 90 mm, 100 mm, 110 mm, 120 mm, 130 mm and 140 mm were built. Then the seven screws were assembled with the pelvic model. The maximum von Mises stress and the shape variables were evaluated for the pelvis and the screws. Results: Results are shown for the pelvic and GOFP screw, respectively. The simulation results show that the maximum von Mises stress in the cortex of the pelvic ring of the pelvis with the 130-mm length screw is the lowest among the pelvic models with different screws. Moreover, the peak displacement of the pelvis with the 130-mm length screw is the smallest. These results indicate that under the standing condition, a 130-mm length screw can decrease the stress concentration and result in a more effective transfer of stress within the reconstructed pelvis. In addition, the displacement of the screw with a 130-mm length is the smallest among all the considered screws. The peak von Mises stresses in the 130-mm length screw and the cortex are still within a low and elastic range below the yielding strengths of the materials. Conclusion: Through the finite element analysis, the GOFP can be used as a safe and effective way for iliosacral screw fixation. The optimal length of the screw may be 130 mm length.
ABSTRACT
There is a great demand for the rapid and non-invasive atherosclerosis screening method. Cholesterol content in the epidermis of the skin is an early biomarker for atherosclerosis. Risk assessment of atherosclerosis can be achieved by measuring cholesterol in the epidermis. Here, we synthesised a new fluorescent digitonin derivative (FDD) for the non-invasive detection of skin cholesterol. The results of fluorescence spectroscopy studies indicated that the probe exhibited desirable selectivity for cholesterol. The proof-of-concept preclinical study confirmed that FDD can detect different concentrations of skin cholesterol; patients diagnosed with atherosclerotic cardiovascular disease and the at-risk atherosclerosis group exhibited higher skin cholesterol content than the normal group. The area under the ROC curve for distinguishing the normal/disease group was 0.9228 (95% confidence interval, 0.8938 to 0.9518), and the area under the ROC curve for distinguishing the normal/risk group was 0.9422 (95% confidence interval, 0.9178 to 0.9665). We anticipate that this non-invasive skin cholesterol test may be used as a risk assessment tool for atherosclerosis screening in a large population for further examination and intervention in high-risk populations.
ABSTRACT
Spatial frequency domain imaging is a non-contact, wide-field, fast-diffusion optical imaging technique, which in principle uses steady-state spatially modulated light to irradiate biological tissue, reconstruct two-dimensional or three-dimensional tissue optical characteristic map through optical transmission model, and further quantify the spatial distribution of tissue physiological parameters by multispectral imaging technique. The selection of light source wavelength and light field spatial modulation frequency is directly related to the accuracy of tissue optical properties and tissue physiological parameters extraction. For improvement of the measurement accuracy of optical properties and physiological parameters in the two-layer tissue, a multispectral spatial frequency domain imaging system is built based on liquid crystal tunable filter, and a data mapping table of spatially resolved diffuse reflectance and optical properties of two-layer tissue is established based on scaling Monte Carlo method. Combined with the dispersion effect and window effect of light-tissue interaction, the study applies numerical simulation to optimize the wavelength in the 650-850â nm range with spectral resolution of 10â nm. In order to minimize the uncertainty of the optical properties, Cramér-Rao bound is used to optimize the optical field spatial modulation frequency by transmitting the uncertainty of optical properties. The results showed that in order to realize the detection of melanin, oxyhemoglobin, deoxyhemoglobin, water and other physiological parameters in two-layer tissue, the best wavelength combination was determined as 720, 730, 760 and 810â nm according to the condition number. The findings of the Cramér-Rao bound analysis reveal that the uncertainty of optical characteristics for the frequency combinations [0, 0.3] mm-1, [0, 0.2] mm-1, and [0, 0.1] mm-1 increases successively. Under the optimal combination of wavelength and frequency, the diffuse reflectance of the gradient gray-scale plate measured by the multi-spectral spatial frequency domain imaging system is linearly correlated with the calibration value. The error between the measured liquid phantom absorption coefficient and the collimation projection system based on colorimetric dish is less than 2%. The experimental results of human brachial artery occlusion indicate that under the optimal wavelength combination, the change of the second layer absorption coefficient captured by the three frequency combinations decreases in turn, so as the change of oxygen saturation.
ABSTRACT
In this study, combined Dark Target and Deep Blue (DTB) aerosol optical depth at 550 nm (AOD550 nm) data the Moderate Resolution Imaging Spectroradiometer (MODIS) flying on the Terra and Aqua satellites during the years 2003-2020 are used as a reference to assess the performance of the Copernicus Atmosphere Monitoring Services (CAMS) and the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) AOD over Bangladesh. The study also investigates long-term spatiotemporal variations and trends in AOD, and determines the relative contributions from different aerosol species (black carbon: BC, dust, organic carbon: OC, sea salt: SS, and sulfate) and anthropogenic emissions to the total AOD. As the evaluations suggest higher accuracy for CAMS than for MERRA-2, CAMS is used for further analysis of AOD over Bangladesh. The annual mean AOD from both CAMS and MODIS DTB is high (>0.60) over most parts of Bangladesh except for the eastern areas of Chattogram and Sylhet. Higher AOD is observed in spring and winter than in summer and autumn, which is mainly due to higher local anthropogenic emissions during the winter to spring season. Annual trends from 2003-2020 show a significant increase in AOD (by 0.006-0.014 year-1) over Bangladesh, and this increase in AOD was more evident in winter and spring than in summer and autumn. The increasing total AOD is caused by rising anthropogenic emissions and accompanied by changes in aerosol species (with increased OC, sulfate, and BC). Overall, this study improves understanding of aerosol pollution in Bangladesh and can be considered as a supportive document for Bangladesh to improve air quality by reducing anthropogenic emissions.
Subject(s)
Air Pollutants , Satellite Imagery , Aerosols/analysis , Air Pollutants/analysis , Bangladesh , Carbon , Environmental Monitoring/methods , Retrospective Studies , SulfatesABSTRACT
In this study, the interaction between the packaging effect (Qaâ) and total chlorophyll-a concentration (Ct) or total size index (SIt) was investigated to explore the potential bio-optical mechanism in phytoplankton cells in the global oceans. In addition, the long-term spatiotemporal characteristics of these interactions were necessary for grasping their variation. Numerous in situ surface measurements (phytoplankton pigment and absorption coefficients) from the global oceans were analyzed first, and then correlation and causality analyses were performed on the satellite-deduced Qaâ, Ct, and SIt in the global oceans during 2002-2020. The results show a negative correlation between Qaâ and Ct or SIt in the low latitudes (30°S-30°N) and a positive correlation in the middle latitudes (30°S-55°S and 30°N-55°N). The causality analysis reveals a mutual and asymmetric cause-effect relationship between Qaâ and Ct or SIt in the low latitudes. The stabilization effect of Qaâ contributes to a 10%-50% variation in Ct and SIt, with 40%-60% uncertainty of Qaâ caused by Ct and SIt in the low latitudes, which is inverse in the middle latitudes. The remaining contribution to each variable mainly originates from long-term trends and noise. Combining the analysis between Qaâ and the irradiance, the balancing processes in phytoplankton cells are different in the low (phytoplankton-driving mode) and middle latitudes (irradiance-driving mode), which is related to photoacclimation and photoinhibition. The analyses provide insights into the quantitative interpretation of the relationship between Qaâ and Ct or SIt, which contribute knowledge that has not been previously reported.
Subject(s)
Chlorophyll , Phytoplankton , Cell Size , Chlorophyll/analysis , Chlorophyll A/metabolism , Oceans and Seas , Phytoplankton/physiologyABSTRACT
SIGNIFICANCE: Optical properties (absorption coefficient and scattering coefficient) of tissue are the most critical parameters for disease diagnosis-based optical method. In recent years, researchers proposed spatial frequency domain imaging (SFDI) to quantitatively map tissue optical properties in a broad field of contactless imaging. To solve the limitations in wavebands unsuitable for silicon-based sensor technology, a compressed sensing (CS) algorithm is used to reproduce the original signal by a single-pixel detectors. Currently, the existing single-pixel SFDI method mainly uses a random sampling policy to extract and recover signals in the acquisition stage. However, these methods are memory-hungry and time-consuming, and they cannot generate discernible results under low sampling rate. Explorations on high performance and efficiency single-pixel SFDI are of great significance for clinical application. AIM: Fourier single-pixel imaging can reconstruct signals with less time and space costs and has fewer reconstruction errors. We focus on an SFDI algorithm based on Fourier single-pixel imaging and propose our Fourier single-pixel image-based spatial frequency domain imaging method (FSI-SFDI). APPROACH: First, we use Fourier single-pixel imaging algorithm to collect and compress signals and SFDI algorithm to generate optical parameters. Given the basis that the main energy of general image signals is concentrated in the range of low frequency of Fourier frequency domain, our FSI-SFDI uses a circular-sampling scheme to sample data points in the low-frequency region. Then, we reconstruct the image details from these points by optimization-based inverse-FFT method. RESULTS: Our algorithm is tested on simulated data. Results show that the root mean square error (RMSE) of optical parameters is lower than 5% when the data reduction is 92%, and it can generate discernible optical parameter image with low sampling rate. We can observe that our FSI-SFDI primarily recovers the optical properties while keeping the RMSE under the upper bound of 4.5% when we use an image with 512 × 512 resolution as the example for calculation and analysis. Not only that but also our algorithm consumes less space and time for an image with 256 × 256 resolution, the signal reconstruction takes only 1.65 ms, and requires less RAM memory. Compared to CS-SFDI method, our FSI-SFDI can reduce the required number of measurements through optimizing algorithm. CONCLUSIONS: Moreover, FSI-SFDI is capable of recovering high-quality resolvable images with lower sampling rate, higher-resolution images with less memory and time consumed than previous CS-SFDI method, which is very promising for clinical data collection and medical analysis.