Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.
Background: Pyrethroid insecticides account for more than 30% of the global insecticide market and are frequently used in agricultural settings and residential and public pest control among the general population. While several animal studies have suggested that exposure to pyrethroids can alter glucose homeostasis, there is only limited evidence of the association between environmental pyrethroid exposure and diabetes in humans. Objectives: This study aimed to report environmental 3-phenoxybenzoic acid (3-PBA) concentrations in urine and evaluate its association with the risk of diabetes in Korean adults. Methods: We analyzed data from the Korean National Environmental Health Survey (KoNEHS) Cycle 2 (2012~2014) and Cycle 3 (2015~2017). A total of 10,123 participants aged ≥19 years were included. Multiple logistic regressions were used to calculate the odds ratios (ORs) for diabetes according to log-transformed urinary 3-PBA levels. We also evaluated age, sex, education, monthly income, marital status, alcohol drinking, physical activity, urinary cotinine, body mass index, and sampling season as potential effect modifiers of these associations. Results: After adjusting for all the covariates, we found significant dose-response relationships between urinary 3-PBA as quartile and the prevalence of diabetes in pooled data of KoNEHS Cycles 2 and 3. In subgroup analyses, the adverse effects of pyrethroid exposure on diabetes were significantly stronger among those aged 19~39 years (p-interaction<0.001) and those who consumed high levels of cotinine (p-interaction=0.020). Conclusions: Our findings highlight the potential diabetes risk of environmental exposure to pyrethroids and should be confirmed in large prospective studies in different populations in the future.
Purpose: Reduced port laparoscopic distal gastrectomy (RPLDG) using 3 ports is less invasive than conventional laparoscopic distal gastrectomy (CLDG) using 5 ports. Although RPLDG performed by expert surgeons is safe and feasible, novice surgeons have difficulty performing this procedure. This study evaluated the surgical outcomes and feasibility of RPLDG performed by a novice surgeon. Materials and Methods: The records of 136 patients who underwent laparoscopic distal gastrectomy for gastric cancer performed by a single novice surgeon between May 2016 and December 2018 were retrospectively reviewed. Among these 136 patients, 52 underwent RPLDG and 84 underwent CLDG. The clinicopathological characteristics, operative outcomes, and short-term postoperative outcomes of the 2 groups were compared. Results: The percentage of women was significantly higher in the RPLDG group than in the CLDG group (48.1% vs. 31%; P=0.045), but other baseline characteristics did not differ significantly between the groups. Billroth II anastomosis was performed significantly more frequent (90.4% vs. 73.8%, P=0.015) and operation time was significantly shorter (207.1±43.3 min vs. 225.5±44.6 min, P=0.020) in the RPLDG group than in the CLDG group. The time to first flatus, postoperative pain score, length of postoperative hospital stay, and incidence and severity of complications did not differ significantly between the groups. Analysis of the learning curve based on the operation time showed that performing RPLDG on 20-30 patients was required to achieve technical proficiency. Conclusions: RPLDG is a safe and feasible surgical procedure for the treatment of gastric cancer, even when performed by a novice surgeon.
Purpose: This study aimed to identify prognostic factors for patients with distant lymph node-involved gastric cancer (GC) using a machine learning algorithm, a method that offers considerable advantages and new prospects for high-dimensional biomedical data exploration. Materials and Methods: This study employed 79 features of clinical pathology, laboratory tests, and therapeutic details from 289 GC patients whose distant lymphadenopathy was presented as the first episode of recurrence or metastasis. Outcomes were measured as any-cause death events and survival months after distant lymph node metastasis. A prediction model was built based on possible outcome predictors using a random survival forest algorithm and confirmed by 5×5 nested cross-validation. The effects of single variables were interpreted using partial dependence plots. A contour plot was used to visually represent survival prediction based on 2 predictive features. Results: The median survival time of patients with GC with distant nodal metastasis was 9.2 months. The optimal model incorporated the prealbumin level and the prothrombin time (PT), and yielded a prediction error of 0.353. The inclusion of other variables resulted in poorer model performance. Patients with higher serum prealbumin levels or shorter PTs had a significantly better prognosis. The predicted one-year survival rate was stratified and illustrated as a contour plot based on the combined effect the prealbumin level and the PT. Conclusions: Machine learning is useful for identifying the important determinants of cancer survival using high-dimensional datasets. The prealbumin level and the PT on distant lymph node metastasis are the 2 most crucial factors in predicting the subsequent survival time of advanced GC.
A standard engineering model that reflects the current organization system and engineering operation process of domestic nuclear power plants was developed based on the Standard Nuclear Performance Model developed by the American Nuclear Energy Association. The level 0 screen, which is the main screen of the engineering model computer system, consisted of an object tree structure, which provided information that is phased down from a higher structure level to a lower structure level (i.e., level 3). The level 1 screen provided information related to the sub-process of the engineering operation, whereas the Level 2 screen provided information related to each engineering operation activity. In addition, the Level 2 screen provided additional functions, such as linking electronic procedures/guidelines, providing electronic performance forms, and connecting legacy computer systems (such as total equipment reliability monitoring system, configuration management systems, technical information systems, risk monitoring systems, regulatory information, and electronic drawing system). This screen level increased the convenience of user's engineering tasks by implementing them. The computerization of an engineering model that connects the entire engineering tasks of an establishment enables the easy understanding of information related to the engineering process before and after the operation, and builds a foundation for the enhancement of the work efficiency and employee capacity. In addition, KHNP developed an online training module, which operates as an e-learning process, on the overview and utilization of a standard engineering model to expand the understanding of standard engineering models by plant employees and to secure competitiveness.
Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R2 = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.
Yu, Jonathan S;Manzi, Joseph E;Apostolakos, John M;Carr II, James B;Dines, Joshua S
Clinics in Shoulder and Elbow
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v.25
no.2
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pp.145-153
/
2022
Background: While online orthopedic resources are becoming an increasingly popular avenue for patient education, videos on YouTube are not subject to peer review. The purpose of this cross-sectional study was to evaluate the quality of YouTube videos for patient education in ulnar collateral ligament (UCL) injuries of the elbow. Methods: A search of keywords for UCL injury was conducted through the YouTube search engine. Each video was categorized by source and content. Video quality, reliability, and accuracy were assessed by two independent raters using five metrics: (1) Journal of American Medical Association (JAMA) benchmark criteria (range 0-4) for video reliability; (2) modified DISCERN score (range 1-5) for video reliability; (3) Global Quality Score (GQS; range 1-5) for video quality; (4) ulnar collateral ligament-specific score (UCL-SS; range 0-16), a novel score for comprehensiveness of health information presented; and (5) accuracy score (AS; range 1-3) for accuracy. Results: Video content was comprised predominantly of disease-specific information (52%) and surgical technique (33%). The most common video sources were physician (42%) and commercial (23%). The mean JAMA score, modified DISCERN score, GQS, UCL-SS, and AS were 1.8, 2.4, 1.9, 5.3, and 2.7 respectively. Conclusions: Overall, YouTube is not a reliable or high-quality source for patients seeking information regarding UCL injuries, especially with videos uploaded by non-physician sources. The multiplicity of low quality, low reliability, and irrelevant videos can create a cumbersome and even inaccurate learning experience for patients.
Kim, Dongwook;Kim, Yuan H. Brad;Ham, Jun-Sang;Lee, Sung Ki;Jang, Aera
Food Science of Animal Resources
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v.40
no.2
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pp.183-196
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2020
The protective effect of pig skin gelatin water extracts (PSW) and the low molecular weight hydrolysates of PSW generated via enzymatic hydrolysis with Flavourzyme® 1000L (LPSW) against scopolamine-induced impairment of cognitive function in mice was determined. Seventy male ICR mice weighing 20-25 g were randomly assigned to seven groups: Control (CON); scopolamine (SCO, 1 mg/kg B.W., intraperitoneally (i.p.); tetrahydroaminoacridine 10 [THA 10, tacrine; 10 mg/kg B.W. per oral (p.o.) with SCO (i.p.)]; PSW 10 (10 mg/kg B.W. (p.o.) with SCO (i.p.); PSW 40 (40 mg/kg B.W. (p.o.) with SCO (i.p.); LPSW 100 (100 mg/kg B.W. (p.o.) with SCO (i.p.); LPSW 400 (400 mg/kg B.W. (p.o.) with SCO (i.p.). All treatment groups, except CON, received scopolamine on the day of the experiment. The oxygen radical absorbance capacity of LPSW 400 at 1 mg/mL was 154.14 μM Trolox equivalent. Administration of PSW and LPSW for 15 weeks did not significantly affect on physical performance of mice. LPSW 400 significantly increased spontaneous alternation, reaching the level observed for THA and CON. The latency time of animals receiving LPSW 400 was higher than that of mice treated with SCO alone in the passive avoidance test, whereas it was shorter in the water maze test. LPSW 400 increased acetylcholine (ACh) content and decreased ACh esterase activity (p<0.05). LPSW 100 and LPSW 400 reduced monoamine oxidase-B activity. These results indicated that LPSW at 400 mg/kg B.W. is a potentially strong antioxidant and contains novel components for the functional food industry.
Journal of the Institute of Convergence Signal Processing
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v.21
no.4
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pp.183-194
/
2020
Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room
Kim, Seog-Ju;Lyoo, In-Kyoon;Lee, Yu-Jin;Lee, Ju-Young;Jeong, Do-Un
Sleep Medicine and Psychophysiology
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v.12
no.2
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pp.122-132
/
2005
Objectives: The objective of this study is to assess cognitive functions and their relationship with sleep symptoms in young narcoleptic patients. Methods: Eighteen young narcolepsy patients and 18 normal controls (age: 17-35 years old) were recruited. All narcolepsy patients had HLA $DQB_1$ *0602 allele and cataplexy. Several important areas of cognition were assessed by a battery of neuropsychological tests consisting of 13 tests: executive functions (e.g. cognitive set shifting, inhibition, and selective attention) through Wisconsin card sorting test, Trail Making A/B, Stroop test, Ruff test, Digit Symbol, Controlled Oral Word Association and Boston Naming Test; alertness and sustained attention through paced auditory serial addition test; verbal/nonverbal short-term memory and working memory through Digit Span and Spatial Span; visuospatial memory through Rey-Osterrieth complex figure test; verbal learning and memory through California verbal learning test; and fine motor activity through grooved pegboard test. Sleep symptoms in narcolepsy patients were assessed with Epworth sleepiness scale, Ullanlinna narcolepsy scale, multiple sleep latency test, and nocturnal polysomnography. Relationship between cognitive functions and sleep symptoms in narcolepsy patients was also explored. Results: Compared with normal controls, narcolepsy patients showed poor performance in paced auditory serial addition (2.0 s and 2.4 s), digit symbol tests, and spatial span (forward)(t=3.86, p<0.01; t=-2.47, p=0.02; t=-3.95, p<0.01; t=-2.22, p=0.03, respectively). There were no significant between-group differences in other neuropsychological tests. In addition, results of neuropsychological test in narcolepsy patients were not correlated with Epworth sleepiness scale score, Ullanlinna narcolepsy scale score and sleep variables in multiple sleep latency test or nocturnal polysomnography. Conclusion: The current findings suggest that young narcolepsy patients have impaired attention. In addition, impairment of attention in narcolepsy might not be solely due to sleep symptoms such as excessive daytime sleepiness.
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