Effect of Air Flow Rates in Versatrap Slit Impactor Cassettes on the Collection of Atmospheric Mold Spores in a Rural Community

Exposure to mold allergens including mold spores and hyphal fragments are associated with allergic sensitization which is a risk factor for asthma in a community. Smaller aerodynamic size of spores (åµm) allows them to penetrate and settle in the lower airways and produce damaging byproducts (allergens, glucans, mycotoxins, and other immunomodulators). Usually mold spores in ambient atmosphere are collected by impactors in air monitoring stations and in most cases these impactors are operated in a single standard air flow rate. However, sampling efficiency of an impactor can change in different air flow rates and since spore aerodynamic sizes vary a lot and temperature and humidity of ambient air can influence aerodynamic properties of airborne mold spores in the atmosphere, we hypothesize that mold data acquired based on a single air sampling flow rate ‰ÛÒ as currently being reported by most ambient air monitoring stations in the United States - could be incomplete. In this study, we have collected atmospheric molds spores simultaneously at three different air flow rates (5L, 10L, and 15L per minute) and samples were collected from four ambient locations in Statesboro, Georgia in different days with different climatic conditions. Spores were collected by the VersaTrapå¨ spore trap cassettes, which provide the sampling versatility to capture mold spores of wide size range from 1.5 to 3.9 åµm. The narrow slit inlet of the VersaTrapå¨ focuses particles toward the clear glass slide coated with a sticky substrate. As hypothesized, we found a substantial difference between spore concentrations collected at different air flow rates: 1306 å± 960, 1709 å± 1430, 1081 å± 923 spores/m3 at 5L, 10L, and 15L per minute (for one hour). We also found diurnal variations of spore concentrations at different times of the day and maximum spore concentration levels were observed between late afternoon and evening

TRENDS AND PROSPECTS OF DIGITAL TWIN TECHNOLOGIES: A REVIEW

© Quantum Journal of Engineering, Science and Technology (QJOEST). This is an open access article under the CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/The plethora of technologically developed software and digital types of machinery are widely applied for industrial production and the digitalization of building technologies. The fourth industrial revolution and the underlying digital transformation, known as Industry 4.0 is reshaping the way individuals live and work fundamentally. However, the advent of Industry 5.0 remodels the representation of industrial data for digitalization. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on the theoretical and static model has been a conventional and powerful tool for the verification, validation, and optimization of a system in its early planning stage, but no attention is paid to the simulation application during system run-time. Dynamic simulation of various systems and the digitalization of the same is made possible using the framework available with Digital Twin. After a complete search of several databases and careful selection according to the proposed criteria, 63 academic publications about digital twin are identified and classified. This paper conducts a comprehensive and in-depth review of this literature to analyze the digital twin from the perspective of concepts, technologies, and industrial applicationsPeer reviewe

Influence of Serum Lycopene on Fatality among Lung Cancer Patients: An 18-Year Follow Up of a National Cohort

A potent antioxidant, lycopene, is the most abundant and naturally-occurring carotenoid in tomatoes and tomato-based foods. It is frequently found in pink grapefruit, watermelon, guava, and papaya; and it provides fruits and vegetables their red and pink colors. Lycopene promotes high levels of free-radical scavenging compared to other carotenoids such as β-carotenoids. It inhibits cellular proliferation, angiogenesis, and metastasis through multiple biochemical pathways. Epidemiological studies suggest that consumption of lycopene-rich foods is associated with decreased risk of prostate, lung, breast and GI tract cancers. To our knowledge, influence of lycopene on lung cancer mortality has not been characterized. Thus, the objective of this study was to determine whether there is an association between serum lycopene levels and lung cancer mortality. A retrospective cohort study was conducted with 14,358 adult participants in phase II of the National Health and Nutrition Examination Survey III (1991-1994) (NHANES III). This served as baseline and was correlated with the National Death Index database for a 15 year (1991-2006) follow-up study. Hazard ratios (HRs) for all-cause and cancer-related deaths for individuals with high, medium, and low serum lycopene levels were calculated using the Cox Proportional Hazards Regression Model. The unadjusted HR of deaths associated with low serum levels (25% cutoff) of lycopene were 1.67 (95%CI=1.24-2.23) and 1.00 (ref). After adjusting for multiple risk factors such as age and sex, the HR for lung cancer mortality were 1.00 (ref) and 1.45 (95%CI=1.08-1.96) for low serum levels (25% cutoff). Adjusted HR for lung cancer death using 3-level categorization (and adjusted for fruits and vegetables) was 1.67 (95%CI=1.03-2.71) for low vs. high levels of lycopene. Also, adjusted HR for lung cancer death using 3-level categorization (and unadjusted for fruits and vegetables) was 1.68 (95%CI=1.04-2.72) for low vs. high levels of lycopene. Results suggest that high serum lycopene levels significantly reduce the risk of death from lung cancer. Thus, not only does lycopene decrease risk of lung cancer development, it also decreases lung cancer mortality. Further studies are needed to explain the physiological mechanisms of this phenomenon

Influence of Serum Lypocene on Lung Cancer Mortality: An 18-Year Follow-Up Study of a National Cohort

A potent antioxidant, lycopene, is the most abundant and naturally-occurring carotenoid in tomatoes and tomato-based foods. It is frequently found in pink grapefruit, watermelon, guava, and papaya; and it provides fruits and vegetables their red and pink colors. Lycopene promotes high levels of free-radical scavenging compared to other carotenoids such as β-carotenoids. It inhibits cellular proliferation, angiogenesis, and metastasis through multiple biochemical pathways. Epidemiological studies suggest that consumption of lycopene-rich foods is associated with decreased risk of prostate, lung, breast and GI tract cancers. To our knowledge, influence of lycopene on lung cancer mortality has not been characterized. Thus, the objective of this study was to determine whether there is an association between serum lycopene levels and lung cancer mortality. A retrospective cohort study was conducted with 14,358 adult participants in phase II of the National Health and Nutrition Examination Survey III (1991-1994) (NHANES III). This served as baseline and was correlated with the National Death Index database for a 15 year (1991-2006) follow-up study. Hazard ratios (HRs) for all-cause and cancer-related deaths for individuals with high, medium, and low serum lycopene levels were calculated using the Cox Proportional Hazards Regression Model. The unadjusted HR of deaths associated with low serum levels (25% cutoff) of lycopene were 1.67 (95%CI=1.24-2.23) and 1.00 (ref). After adjusting for multiple risk factors such as age and sex, the HR for lung cancer mortality were 1.00 (ref) and 1.45 (95%CI=1.08-1.96) for low serum levels (25% cutoff). Adjusted HR for lung cancer death using 3-level categorization (and adjusted for fruits and vegetables) was 1.67 (95%CI=1.03-2.71) for low vs. high levels of lycopene. Also, adjusted HR for lung cancer death using 3-level categorization (and unadjusted for fruits and vegetables) was 1.68 (95%CI=1.04-2.72) for low vs. high levels of lycopene. Results suggest that high serum lycopene levels significantly reduce the risk of death from lung cancer. Thus, not only does lycopene decrease risk of lung cancer development, it also decreases lung cancer mortality. Further studies are needed to explain the physiological mechanisms of this phenomenon

Effect of Different Air Flow Rates on the Collection of Atmospheric Mold Spores of Different Sizes by a Slit Impactor

Exposure to mold spores are associated with allergic sensitization, which is a risk factor for atopic asthma in a community. Small aerodynamic sizes of spores (\u3c10 \u3eμm) allow them to penetrate in the lower airways and produce damaging byproducts including allergens and other immunomodulators. Usually mold spores in ambient atmosphere are collected by impactors in air monitoring stations, which are operated in a single standard air flow rate. However, sampling efficiency of an impactor can change in different air flow rates. Because spore aerodynamic sizes vary a lot and atmospheric temperature and humidity can influence aerodynamic properties of airborne mold spores, we hypothesize that mold data acquired based on a single air sampling flow rate – as currently being reported by most ambient air monitoring stations - could be incomplete. In this study, we have collected atmospheric mold spores simultaneously at three different air flow rates (5 L, 10 L, and 15 L per minute) and samples were collected from four rural ambient locations in different days. VersaTrap® spore trap cassettes were used for sampling, which provide the sampling versatility to capture mold spores of 1.5–3.9 μm. As hypothesized, we found a substantial difference between total spore concentrations collected at different air flow rates: 1.306 ± 960, 1.709 ± 1.430, 1.081 ± 923 spores/m3 at 5 L, 10 L, and 15 L per minute, respectively. Mold spores of Aspergillus/Penicillium (typically \u3c3 \u3eμm aerodynamic diameter) showed less variability compared to Ascopsores and Cladosporium

Development of maize plant dataset for intelligent recognition and weed control

This paper focuses on the development of maize plant datasets for the purposes of recognizing maize plants and weed species, as well as the precise automated application of herbicides to the weeds. The dataset includes 36,374 images captured with a high-resolution digital camera during the weed survey and 500 images annotated with the Labelmg suite. Images of the eighteen farmland locations in North Central Nigeria, containing the maize plants and their associated weeds were captured using a high-resolution camera in each location. This dataset will serve as a benchmark for computer vision and machine learning tasks in the intelligent maize and weed recognition research

PathoFusion: An Open-Source AI Framework for Recognition of Pathomorphological Features and Mapping of Immunohistochemical Data

We have developed a platform, termed PathoFusion, which is an integrated system for marking, training, and recognition of pathological features in whole-slide tissue sections. The platform uses a bifocal convolutional neural network (BCNN) which is designed to simultaneously capture both index and contextual feature information from shorter and longer image tiles, respectively. This is analogous to how a microscopist in pathology works, identifying a cancerous morphological feature in the tissue context using first a narrow and then a wider focus, hence bifocal. Adjacent tissue sections obtained from glioblastoma cases were processed for hematoxylin and eosin (H&E) and immunohistochemical (CD276) staining. Image tiles cropped from the digitized images based on markings made by a consultant neuropathologist were used to train the BCNN. PathoFusion demonstrated its ability to recognize malignant neuropathological features autonomously and map immunohistochemical data simultaneously. Our experiments show that PathoFusion achieved areas under the curve (AUCs) of 0.985 ± 0.011 and 0.988 ± 0.001 in patch-level recognition of six typical pathomorphological features and detection of associated immunoreactivity, respectively. On this basis, the system further correlated CD276 immunoreactivity to abnormal tumor vasculature. Corresponding feature distributions and overlaps were visualized by heatmaps, permitting high-resolution qualitative as well as quantitative morphological analyses for entire histological slides. Recognition of more user-defined pathomorphological features can be added to the system and included in future tissue analyses. Integration of PathoFusion with the day-to-day service workflow of a (neuro)pathology department is a goal. The software code for PathoFusion is made publicly available

PathoFusion: An Open-Source AI Framework for Recognition of Pathomorphological Features and Mapping of Immunohistochemical Data

We have developed a platform, termed PathoFusion, which is an integrated system for marking, training, and recognition of pathological features in whole-slide tissue sections. The platform uses a bifocal convolutional neural network (BCNN) which is designed to simultaneously capture both index and contextual feature information from shorter and longer image tiles, respectively. This is analogous to how a microscopist in pathology works, identifying a cancerous morphological feature in the tissue context using first a narrow and then a wider focus, hence bifocal. Adjacent tissue sections obtained from glioblastoma cases were processed for hematoxylin and eosin (H&E) and immunohistochemical (CD276) staining. Image tiles cropped from the digitized images based on markings made by a consultant neuropathologist were used to train the BCNN. PathoFusion demonstrated its ability to recognize malignant neuropathological features autonomously and map immunohistochemical data simultaneously. Our experiments show that PathoFusion achieved areas under the curve (AUCs) of 0.985 ± 0.011 and 0.988 ± 0.001 in patch-level recognition of six typical pathomorphological features and detection of associated immunoreactivity, respectively. On this basis, the system further correlated CD276 immunoreactivity to abnormal tumor vasculature. Corresponding feature distributions and overlaps were visualized by heatmaps, permitting high-resolution qualitative as well as quantitative morphological analyses for entire histological slides. Recognition of more user-defined pathomorphological features can be added to the system and included in future tissue analyses. Integration of PathoFusion with the day-to-day service workflow of a (neuro)pathology department is a goal. The software code for PathoFusion is made publicly available