• Horticultural Science & Technology
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• v.30 no.3
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• pp.270-277
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• 2012

Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.7
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• pp.1108-1114
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• 2007

Twenty eight non-lactating and non-pregnant adult Serra da Estrela ewes, ranging in body condition score (BCS) from 1 to 4 were used to study the relationships between BCS, live weight (LW), body composition and fat partition. Ewes were slaughtered and their kidney knob and channel fat (KKCF), sternal fat (STF) and omental plus mesenteric fat (OMF) were separated and weighed. Left sides of carcasses as well as the respective lumbar joints were then dissected into muscle, bone and subcutaneous (SCF) and intermuscular fat (IMF). The relationship between LW and BCS was studied using data from 1,396 observations on 63 ewes from the same flock and it was found to be linear. Regression analysis was also used to describe the relationships among BCS and/or LW and weights (kg) and percentages in empty body weight (EBW) of dissected tissues. The prediction of weights and percentages in EBW of total fat (TF) and of all fat depots afforded by BCS was better than that provided by LW. Only the weight of muscle and the percentage of bone in the EBW were more efficiently predicted by LW than by BCS. IMF represented the largest fat depot with a BCS of 1 and 2, whereas SCF was the most important site of fat deposition with a BCS of 3 and 4. Allometric coefficients for each fat depot in TF suggest that the fat deposition order in ewes from this breed is: IMF, OMF, SCF and KKCF. Results demonstrate that BCS is a better predictor than LW of body reserves in this breed and that LJ is a suitable anatomical region to evaluate BCS.

• Journal of East-West Nursing Research
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• v.25 no.2
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• pp.183-192
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• 2019

Purpose: This study aimed to examine the mediating effect of illness perception on the relationship between family function and health behavior of patients with risk factors for metabolic syndrome. Methods: This is a cross-sectional correlational study. Data were collected from 160 patients using self-administered questionnaires including the Illness Perception Questionnaire-Revised, Family APGAR, and the Health Behavior Scale. The data were analyzed using Pearson's correlation coefficients, independent t-test and multiple linear regression analysis by the SPSS 23.0 program. Results: Health behavior was significantly correlated with family function (r=.30, p<.001) and illness perception of controllability by treatment (r=-.21, p=.007). Family function was a significant predictor of health behavior and illness perception, and the influence of family function on health behavior was partially mediated by illness perception of controllability by treatment. Conclusion: The findings of this study indicate that family function is a critical factor affecting health behavior and illness perception, and illness perception of controllability by treatment mediates the influence of family function on health behavior. It is necessary to develop a psycho-cognitive intervention program for enhancing supportive family function and for modifying negative illness perceptions to improve health behavior in patients with risk factors for metabolic syndrome.

• Women's Health Nursing
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• v.27 no.1
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• pp.49-57
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• 2021

Purpose: Aromatase inhibitors (AIs) are widely prescribed for postmenopausal women with breast cancer and are known to cause musculoskeletal pain. This study aimed to identify factors associated with AI continuation intention among breast cancer survivors (BCS). Methods: A cross-sectional survey was conducted on 123 BCS (stages I-III), who had been taking AIs for at least 6 weeks. Participants were recruited from a cancer center in Goyang, Korea, from September to November 2019. Descriptive statistics, Welch analysis of variance, Pearson correlation coefficients, and simple linear regression were used for the analysis. Results: Beliefs about endocrine therapy was a significant predictor of AI continuation intention (β=.66, p<.001). The majority of participants (87.0%) reported experiencing musculoskeletal pain since taking AIs and the score for the worst pain severity within 24 hours was 5.08±2.80 out of 10. Musculoskeletal pain, however, was not associated with AI continuation intention. Fear of cancer recurrence (FCR) was clinically significant (≥13) for 74.0% of the respondents (mean, 17.62±7.14). Musculoskeletal pain severity and pain interference were significantly associated with FCR (r=.21, p<.05; r=.35, p<.01, respectively). Pain interference was significantly associated with beliefs about endocrine therapy (r=-.18, p<.05). Conclusion: AI continuation intention can be modified by reinforcing patients' beliefs about endocrine therapy. Musculoskeletal pain may have a negative effect on beliefs about endocrine therapy and increase FCR among BCS. Thus, awareness of musculoskeletal pain during AI therapy should be raised and further research is required to develop multidisciplinary pain management strategies and clinical guidelines to reinforce beliefs about endocrine therapy.

• Journal of Environmental Health Sciences
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• v.27 no.2
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• pp.127-137
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• 2001

Polychlorinated biphenyls(PCBs) are halogenated aromatic compounds with the empirical formula $C_{12}$ $H_{10-n}$C $l_{n}$(n=1~10), and are a mixture of possible 209 different chlorinated congeners. PCBs were widely used as dielectric fluids for capacitors and transformers, plasticizers, lubricant inks and paint addirives. Once released into the environment, PCBs persist for years because they are so resistant to degradation. In addition to their persistence in the environment, PCBs in ecological food chains undergo biomagnification because of their high degree of lipophilicity. In 1970s, the worldwide production of PCBs was ceased and the import of PCBs was prohibited since 1983 in Korea. In spite of these actions, many PCBs seems to be still in use. The environmental load of PCBs will continue to be recycled through air, land, water, and the biosphere for decades to come. This study was conducted to measure the concentrations of PCBs in the serum samples of 112 women by GC/MSD and GC/ECD. The main results of this study were as follows. 1. PCBs were detected in all samples. The mean $\pm$SD levels of PCBs in the serum were 3.613$\pm$0.759 ppb, and median were 3.828 ppb. 2. The correlation coefficients of the concentrations of 13 PCB congeners were from minimum, 0.7913 to maximum, 0.9985, and all was significant(p=0.0001). The correlation coefficient between the concentrations of PCBs and p,p'-DDE was 0.9641(p=0.0001). 3. There was a positive association between age and PCBs' concentrations (simple linear regression ; $R^2$=0.86, $\beta$=0.08023, p<0.001). 4. There was a positive association between total lipids in the serum and PCBs' concentrations (simple linear regression ; $R^2$=0.7058, $\beta$=0.00486, p<0.001). 5. For possible predictors of PCBs and p,p' -DDE levels in the serum, age adjusted model (Y=$\beta$$_{0}$+$\beta$$_1$age+ $B_2$X) was applied. For BMI, major residential area, wether to eat caught fish by angling, where to eat caught fish by angling(by parents in the past), fish consumption, meat consumption, meat consumption, and dairy consumption, there was no association. For total conception frequency and lactation frequency and lactation period, there was negative association.ion.

• Journal of Korean Academy of Nursing
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• v.30 no.6
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• pp.1543-1555
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• 2000

Home health care is moving into a set of new realities. An era of competition and cost containment has arrived. Before nurses are able to contain costs or describe the relationship between nursing activities, cost must be accurately measured based on the nurse's workload. Nurses in home health care usually desire to measure expenses for one of three reasons : reimbursement, management, or research. The purpose of the study was to investigate the work input by Registered Nurse in each of the home health care activities by relative value units and identify the factors affecting the nurses' total work input in health care services. To measure the work input by nurses, work was defined by four dimensions: time, physical effort, mental effort, and stress. This study used a descriptive-correlational design. Data collection consisted of two phases. In phase I, data on home health activities performed by nurses were collected. In phase II, data on nurses' time, physical effort, mental effort, and stress in each of home health care activities discovered phase I were collected. In this method, the respondent was asked to rate a service in relation to a reference service using a ratio scale. The sample included 39 home health care nurses. The results of the study indicated that home health care activities performed by the nurses were in 10 categories and 69 items. Measuring the relative work inputs in each of home health care activities, and foley catheterization was selected as the reference to service. In terms of time and physical effort dimensions, full bath service was rated as the most strenuous among 69 activities by the respondents, and intramuscular injection was rated as least. It was found that emergency treatment required the highest mental effort and the highest stress, while blood sugar tests required the lowest mental effort. Approximately 91.3% of the variance in total work input was accounted for by the linear combination of time, physical effort, mental effort judgement, and stress. Examining the regression coefficients of those variables, physical effort, time, and stress were found as the predictors which were significantly associated with the total work of nurses in home health care. Professional nursing's next step in the conundrum of economic volatility is to develop a tool to reflect the interaction of functional deficiency and direct professional nursing care. And this will be a more accurate predictor of nursing resource use and ultimately a great forcaeter cost.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.312-318
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• 2010

This study was carried out to develop and test a prototype program that recommends the nitrogen topdressing rate using the color digital camera image taken from rice field at panicle initiation stage (PIS). This program comprises four models to estimate shoot N content (PNup) by color digital image analysis, shoot N accumulation from PIS to maturity (PHNup), yield, and protein content of rice. The models were formulated using data set from N rate experiments in 2008. PNup was found to be estimated by non-linear regression model using canopy cover and normalized green values calculated from color digital image analysis as predictor variables. PHNup could be predicted by quadratic regression model from PNup and N fertilization rate at panicle initiation stage with $R^2$ of 0.923. Yield and protein content of rice could also be predicted by quadratic regression models using PNup and PHNup as predictor variables with $R^2$ of 0.859 and 0.804, respectively. The performance of the program integrating the above models to recommend N topdressing rate at PIS was field-tested in 2009. N topdressing rate prescribed for the target protein content of 6.0% by the program were lower by about 30% compared to the fixed rate of 30% that is recommended conventionally as the split application rate of N fertilizer at PIS, while rice yield in the plots top-dressed with the prescribed N rate were not different from those of the plots top-dressed with the fixed N rates of 30% and showed a little lower or similar protein content of rice as well. And coefficients of variation in rice yield and quality parameters were reduced substantially by the prescribed N topdressing. These results indicate that the N rate recommendation using the analysis of color digital camera image is promising to be applied for precise management of N fertilization. However, for the universal and practical application the component models of the program are needed to be improved so as to be applicable to the diverse edaphic and climatic condition.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.5
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• pp.386-395
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• 2006

The core questions for determining nitrogen topdress rate (Npi) at panicle initiation stage (PIS) are 'how much nitrogen accumulation during the reproductive stage (PNup) is required for the target rice yield or protein content depending on the growth and nitrogen nutrition status at PIS?' and 'how can we diagnose the growth and nitrogen nutrition status easily at real time basis?'. To address these questions, two years experiments from 2001 to 2002 were done under various rates of basal, tillering, and panicle nitrogen fertilizer by employing a rice cultivar, Hwaseongbyeo. The response of grain yield and milled-rice protein content was quantified in relation to RVIgreen (green ratio vegetation index) and SPAD reading measured around PIS as indirect estimators for growth and nitrogen nutrition status, the regression models were formulated to predict PNup based on the growth and nitrogen nutrition status and Npi at PIS. Grain yield showed quadratic response to PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict grain yield had a high determination coefficient of above 0.95. PNup for the maximum grain yield was estimated to be 9 to 13.5 kgN/10a within the range of RVIgreen around PIS of this experiment. decreasing with increasing RVIgreen and also to be 10 to 11 kgN/10a regardless of SPAD readings around PIS. At these PNup's the protein content of milled rice was estimated to rise above 9% that might degrade eating quality seriously Milled-rice protein content showed curve-linear increase with the increase of PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict protein content had a high determination coefficient of above 0.91. PNup to control the milled-rice protein content below 7% was estimated as 6 to 8 kgN/10a within the range of RVIgreen and SPAD reading of this experiment, showing much lower values than those for the maximum grain yield. The recovery of the Npi applied at PIS ranged from 53 to 83%, increasing with the increased growth amount while decreasing with the increasing Npi. The natural nitrogen supply from PIS to harvest ranged from 2.5 to 4 kg/10a, showing quadratic relationship with the shoot dry weight or shoot nitrogen content at PIS. The regression models to estimate PNup was formulated using Npi and anyone of RVIgreen, shoot dry weight, and shoot nitrogen content at PIS as predictor variables. These models showed good fitness with determination coefficients of 0.86 to 0.95 The prescription method based on the above models predicting grain yield, protein content and PNup and its constraints were discussed.

• Korean Journal of Psychosomatic Medicine
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• v.21 no.1
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• pp.18-26
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• 2013

Objectives : Type D personality was originally introduced to study the role of personality in predicting outcomes of heart disease. However, researches showed that other medical conditions are also affected by this personality. The purpose of this study was to evaluate the relationship between type D personality and somatic symptom complaints in depressive patients. Methods : Eighty-two individuals diagnosed with depressive disorder were included. Type D personality was measured with DS14. Patient Health Questionnaire(PHQ) 9 and 15 were used to measure depression severity and somatization tendencies. For alexithymia, TAS-20 was used. Student T-test and linear regression analysis were performed. The best regression model was determined by stepwise variable selection. Results : More than half of the subjects(56%) complained at least medium degree somatic symptoms according to PHQ-15 criteria. Two-thirds of the subjects were classified as Type D personality(63.4%). The mean PHQ-15 score of the Type D individuals was significantly higher than the remaining subjects(PHQ-15 mean=12.7, $p=8.2{\times}10^{-7}$). The best regression model included age, PHQ-9 score and NA subscale score as predictor variables. Among these, only the coefficients of age($p=1.5{\times}10^{-3}$) and NA score($p=1.5{\times}10^{-7}$) were found to be statistically significant. Conclusions : The result showed that Type D personality was one of the strong predictors of somatic complaints among depressive individuals. The finding that negative affectivity rather than social inhibition was more closely associated with somatization tendencies does not fully agree with the traditional explanation that inability to express negative emotion predispose the individuals to somatic symptoms. The finding that alexithymia was not shown to be a significant predictors also substantiated this discrepancy. However, it might be possible that the high correlation between NA and SI subscore(r=0.65) and between NA and TAS-20 score(r=0.44) hid the additional effects of social inhibition and alexithymia. Further research with a larger sample would be needed to investigate the effects of the latter two components over and above the effect of negative affectivity on the somatic complaints in depressive patients.