Abhishek Subedi;Wen Tang;Tarutal Ghosh Mondal;Rih-Teng Wu;Mohammad R. Jahanshahi
Smart Structures and Systems
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v.31
no.4
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pp.335-349
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2023
Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.
We investigated the work-life balance of clinical professors in charge of patient care, research, and education at medical schools and the demand for work-life balance support according to position (professor, associate professor, or assistant professor). In total, 163 clinical professors completed the consent form and participated in the study. They filled out an online survey consisting of questions about essential characteristics, a work-life balance test, stress, burnout, work-life satisfaction, and work-life balance support needs. We analyzed the results by analysis of variance and cross-tabulation using IBM SPSS ver. 23.0. Differences were found in work-life balance, stress, burnout, and satisfaction with life and work by position. The requirements for support for work-life balance also varied by professional status. Professors had a higher balance between life and work than associate professors or assistant professors. The specific requirements for work-life balance support were also slightly different for each position. Overall, there was a high demand for work process simplification and efficiency for work support, flexible working hours and sabbatical years for family and leisure, and career management consulting and training support for growth. Assistant professors and associate professors had a lower level of work-life balance than professors, as well as higher levels of stress and burnout. Professors' job satisfaction was also higher than that of the other groups. Based on the results of this study, we hope that a healthy work environment can be established through work-life balance support suitable for clinical professors' positions.
The shear wave velocity is related with the stiffness of granular skeleton and mass density. The shear stiffness of the granular skeleton remains unaffected by the presence of the fluid. Bender elements are convenient shear wave transducers for instrumenting soil cells due to optimal soil-transducer coupling. This study addresses the principles of the shear wave, the design and implementation of bender elements including electromagnetic coupling prevention, directivity, resonant frequency, detection of first arrival, and near field effects. It is shown that electromagnetic coupling effects can be minimized using parallel-type bender elements. Thus, the in-plane S-wave directivity is quasi-circular. The resonant frequency of bender element installations depends on the geometry of the bender element, the anchor efficiency and the soil stiffness. One of the most cumbersome parts in the bender element test is near field effects, which affect the selection of arrival time. The selection of the first arrival within the near field Is effectively solved by the multiple reflection technique and signal matching technique. Bender elements, which requires several considerations, may be effective tools for the subsurface characterization by using S-wave.
Natural ventilation has proven to be an effective passive strategy in improving energy efficiency and providing healthy environments. However, such a strategy has not been commonly adopted to tall office buildings that traditionally rely on single-skin façades (SSFs), due to the high wind pressure that creates excessive air velocities and occupant discomfort at upper floors. Double-skin façades (DSFs) can provide an opportunity to facilitate natural ventilation in tall office buildings, as the fundamental components such as the additional skin and openings create a buffer to regulate the direct impact of wind pressure and the airflow around the buildings. This study investigates the impact of modified multi-story type DSFs on indoor airflow in a 60-story, 780-foot (238 m) naturally ventilated tall office building under isothermal conditions. Thus, the performance of wind effect related components was assessed based on the criteria (e.g., air velocity and airflow distribution), particularly with respect to opening size. Computational fluid dynamics (CFD) was utilized to simulate outdoor airflow around the tall office building, and indoor airflow at multiple heights in case of various DSF opening configurations. The simulation results indicate that the outer skin opening is the more influential parameter than the inner skin opening on the indoor airflow behavior. On the other hand, the variations of inner skin opening size help improve the indoor airflow with respect to the desired air velocity and airflow distribution. Despite some vortexes observed in the indoor spaces, cross ventilation can occur as positive pressure on the windward side and negative pressure on the other sides generate productive pressure differential. The results also demonstrate that DSFs with smaller openings suitably reduce not only the impact of wind pressure, but also the concentration of high air velocity near the windows on the windward side, compared to SSFs. Further insight on indoor airflow behaviors depending on DSF opening configurations leads to a better understanding of the DSF design strategies for effective natural ventilation in tall office buildings.
Jin-Kyung Cha;Hyunjin Park;Youngho Kwon;So-Myeong Lee;Dongjin Shin;Jong-Hee Lee
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.20-20
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2022
A traditional wheat breeding program needs more than 12-13 years to develop a new cultivar. In recent years, 'Speed breeding (SB)' system, which uses extremely extended photoperiod (22 h), enabled up to 4-6 generations of spring wheat per year. However, since almost 70% of wheat cultivars are winter type, and over 95% of total cultivation area is for winter wheat in Korea, optimized vernalization treatment was essential for improving the SB system. Several vernalization temperatures and durations were tested with various genotypes, and the 4 weeks of 8-10 ℃ vernalization treatment was the most effective to develop 4 generations per year, for both spring and winter type wheat cultivars. This 'Speed vernalization (SV)' system followed by SB, allowed developing a new F6 recombinant inbred lines (RILs) within 2 years. Among the 184 RILs, which derived from a cross between Jokoyung and Joongmo2008, two outstanding lines were selected for yield trial test, and then named Milyang52 and Milyang53. Compared to the traditional wheat breeding program, over 60% of the time was saved to develop these two lines. Marker-assisted selection and backcross were also combined with the SV system. YW3215-2B-1 (Jokoyung*3/Gamet), which has similar agronomic traits with Jokyoung and the same Glu-B1 allele with Garnet, was developed within 2.5 years. Thus, the SV system combined with molecular breeding technology would help breeders to make a new cultivar with less time and high efficiency.
Transporting clinical samples for microbiological testing requires a proper transport medium that guarantees the survival of microorganisms. Therefore, the aim of the study was to determine the ability of Amies Transport Medium (ATM) to maintain the viability of microorganisms in clinical specimens and its suitability as a transport medium for microbiological testing. This study evaluated the performance of swab provided by KS Co., Ltd. for three groups of bacteria comprising aerobic and facultative anaerobic bacteria, anaerobic bacteria, and fastidious bacteria, according to the Clinical and Laboratory Standard Institute (CLSI) 8.11.2. The ATM stability test was conducted by dividing the medium into two groups based on the product expiration date of use. All tested media, A and B (the date of manufacture and expiration date are different) showed ≥5 CFU, and there was no significant difference in the result values of Category A and Category B with different serial numbers for each test. The results of this experiment when cross-checked with the guidelines suggest that ATM is a suitable transport medium for microbiological testing, as it maintains the viability of microorganisms and is suitable for overgrowth trials. In addition, compared to the number of CFUs at the origin, the number of CFUs did not increase by more than 1 log after storage. These results have important implications for the development of transport media that can guarantee the survival of microorganisms in clinical specimens.
Veena Jaganivasan;Dona Samuel Karen;Bavya Chandrasekhar
Journal of Integrative Natural Science
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v.16
no.3
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pp.81-95
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2023
Colorectal cancer is one of the most common types of cancer worldwide, ranking third after lung and breast cancer in terms of global prevalence. With an expected 1.93 million new cases and 935,000 deaths in 2020, it is more prevalent in males than in women. Evidence has shown that during the later stages of colon cancer, STAT1 promotes tumor progression by promoting cell survival and resistance to chemotherapy. Recent studies have shown that inhibiting STAT1 pathway leads to a reduction in tumor cell proliferation and growth, and can also promote apoptosis in colon cancer cells. One of the recent approaches in the field of drug discovery is drug repurposing. In drug repurposing approach we have virtually screened FDA database against STAT1 protein and their interactions have been studied through Molecular docking. Cross docking was performed with the top 10 compounds to be more specific with STAT1 comparing the affinity with STAT2, STAT3, STAT4, STAT5a, STAT5b and STAT6. The drugs that showed higher affinity were subjected to Conceptual - Density functional theory. Besides, the Molecular dynamic simulation was also carried out for the selected leads. We also validated in-vitro against colon cancer cell lines. The results showed mainly Acetyldigitoxin has shown better binding to the target. From this study, we can predict that the drug Acetyldigitoxin has shown noticeable inhibitory efficiency against STAT1, which in turn can also lead to the reduction of tumor cell growth in colon cancer.
Thuc Duc TRAN;Thai Dinh TRUONG;Thong Van PHAM;Dien Huong PHAM
Journal of Distribution Science
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v.22
no.2
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pp.71-82
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2024
Purpose: Despite significant research on decision-making, researchers struggle to comprehend the decision-making process. This paper aims to not only examine the relationship between problem-solving skills, cognitive competency, and decision-making but also develop measurement instruments for cognitive competency and problem-solving skills to better model decision-making. Research Design, Methodology and Approach: A cross-sectional study was conducted by surveying 292 university students in HCM City, Vietnam, via email sent randomly by Google Forms. This study identifies the conceptual framework and tests the hypotheses using a deductive approach. The SPSS program was used to evaluate the scales' reliability, and the SmartPLS program was used to assess the measurement and structural models. Results: The results show that the research model better modelled the relationship between problem-solving skills, cognitive competency, and decision-making. Although thinking ability has no direct impact on decision-making, both creativity and problem-solving skills have a positive impact on decision-making. The mediating role of problem-solving skills is also determined by the positive relationship between cognitive competency and decision-making. Conclusions: This study highlights decision-making efficiency through the cognitive process from low to high levels and provides for policymakers and managers to explain the decision-making process in a variety of sectors, such as distribution chains, marketing, and human resource distribution.
The Journal of the Korea institute of electronic communication sciences
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v.18
no.5
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pp.999-1008
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2023
Early prediction of chronic diseases such as diabetes is an important issue, and improving the accuracy of diabetes prediction is especially important. Various machine learning and deep learning-based methodologies are being introduced for diabetes prediction, but these technologies require large amounts of data for better performance than other methodologies, and the learning cost is high due to complex data models. In this study, we aim to verify the claim that DNN using the pima dataset and k-fold cross-validation reduces the efficiency of diabetes diagnosis models. Machine learning classification methods such as decision trees, SVM, random forests, logistic regression, KNN, and various ensemble techniques were used to determine which algorithm produces the best prediction results. After training and testing all classification models, the proposed system provided the best results on XGBoost classifier with ADASYN method, with accuracy of 81%, F1 coefficient of 0.81, and AUC of 0.84. Additionally, a domain adaptation method was implemented to demonstrate the versatility of the proposed system. An explainable AI approach using the LIME and SHAP frameworks was implemented to understand how the model predicts the final outcome.
Lipoxygenase gives soybeans their grassy flavor, which can disrupt food processing efficiency. This study aimed to identify soybean genotypes with lipoxygenase deficiency among 1,001 soybean accessions and to develop kompetitive allele specific PCR (KASP) markers that can detect lipoxygenase mutations. Three lipoxygenase isozymes (Lox1, Lox2, and Lox3) were analyzed using a colorimetric assay based on a substrate-enzyme reaction. Among the 1,001 accessions examined, two (IT160160 and IT276392) exhibited a deficiency solely in Lox1, and one (IT269984) lacked both Lox1 and Lox2. IT160160 had a 74-bp deletion in exon 8 of Lox1 (Glyma13g347600), whereas IT276392 displayed a missense mutation involving the change of C to A at position 2,880 of Lox1. Moreover, we successfully developed four KASP markers that specifically target Lox1, Lox2, and Lox3 mutations. To validate the Lox1 KASP markers, we used two F2:3 populations generated through a cross between Daepung 2 (lipoxygenase wild type, maternal parent), IT160160, and IT276392 (null Lox1, paternal parent). The results revealed that the Daepung 2 × IT160160 group followed the expected 3:1 ratio according to Mendel's law, whereas the Daepung 2 × IT276392 group did not. Furthermore, a comparison between the colorimetric and KASP marker analyses results revealed a high agreement rate of 96%. KASP markers offer a distinct advantage by allowing the distinction of heterozygous types independent of other variables. As a result, we present an opportunity to expedite the lipoxygenase-deficient cultivar development.
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