This study analyzed the changes in Electroencephalogram(EEG) and Electrocardiogram(ECG) depending on the healing environment in order to find a way to improve the forest healing program based on the healing environment in response to the demand for qualitative improvement of the program since the program is a charged service. This study selected eight sites running forest healing programs at four national healing forests (i.e., Saneum, Cheongtaesan, Daegwanryeng, and Jangseong) - two routes per national healing forest - considering forest environments. This study chose NUMBER standard sampling plots ($20{\times}20m$) and measured three atmospheric environment items, seven physical environment items, two soil environment items, and eight vegetation environment items including forest sound and anion at each plot to evaluate physiological changes in it. EEG and ECG, which have been widely used in forest healing evaluation, were utilized as criteria. Seventy three subjects were selected with taking the age, drug, caffeine, smoking, and the time of last meal into consideration. As a result, EEG changes were correlated with three atmospheric environment items, six physical environment items, one soil environment item, and two vegetation environment items. ECG changes were significantly correlated with two atmospheric environment items, six physical environment items, two soil environment items, and two vegetation environment items (p<.05). It is expected that 11 environmental factors such as temperature, density, and altitude affecting EEG (e.g., alpha balance and gamma balance) and ECG (e.g., HRV mean) could be used as effective tools in developing more differentiated programs for improving healing effects.
Graphene, with impressive electronic properties, have high potential in the microelectronic field. However, graphene itself is a zero bandgap material which is not suitable for digital logic gates and its application. Thus, much focus is on graphene nanoribbons (GNRs) that are narrow strips of graphene. During GNRs fabrication process, the occurrence of defects that ultimately change electronic properties of graphene is difficult to avoid. The modelling of GNRs with defects is crucial to study the non-idealities effects. In this work, nearest-neighbor tight-binding (TB) model for GNRs is presented with three main simplifying assumptions. They are utilization of basis function, Hamiltonian operator discretization and plane wave approximation. Two major edges of GNRs, armchair-edged GNRs (AGNRs) and zigzag-edged GNRs (ZGNRs) are explored. With single vacancy (SV) defects, the components within the Hamiltonian operator are transformed due to the disappearance of tight-binding energies around the missing carbon atoms in GNRs. The size of the lattices namely width and length are varied and studied. Non-equilibrium Green's function (NEGF) formalism is employed to obtain the electronics structure namely band structure and density of states (DOS) and all simulation is implemented in MATLAB. The band structure and DOS plot are then compared between pristine and defected GNRs under varying length and width of GNRs. It is revealed that there are clear distinctions between band structure, numerical DOS and Green's function DOS of pristine and defective GNRs.
Objectives: Depression is a frequent complication of type 2 diabetes mellitus. This study aimed to investigate the relationship between low social support and risk for depression in people with type 2 diabetes through a meta-analysis. Methods: PubMed, ProQuest, SpringerLink, ScienceDirect, Scopus, the Cochrane Library, Embase, and Google Scholar were searched for English-language articles published up to 2021. Pooled adjusted odds ratios (aORs) were calculated using a random-effect model with 95% confidence intervals (CIs). Heterogeneity was evaluated by using the Cochrane Q test and I2 statistics. The risk of publication bias was estimated using a funnel plot, the Egger test, and the Begg test. The Joanna Briggs Institute Critical Appraisal Tools were used to assess the quality of evidence and the risk of bias. Results: Eleven studies were included in this meta-analysis, containing a total of 3151 people with type 2 diabetes mellitus. The pooled analysis showed that people with type 2 diabetes mellitus who had low social support had twice as high a risk of depression as those with high social support (aOR, 2.02; 95% CI, 1.51 to 2.70; p<0.001). A random-effect model was used because the heterogeneity was high (I2 = 87%). Conclusions: Low social support was found to increase the risk of depression among people with type 2 diabetes mellitus. Further investigation into factors that may moderate this relationship is required.
Asinwa, Israel Olatunji;Olajuyigbe, Samuel Olalekan
Journal of Forest and Environmental Science
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v.38
no.3
/
pp.141-151
/
2022
Soil seed banks as natural storage of plant seeds play an important role in the maintenance and regeneration of watershed. Natural regeneration potential of the soil seed bank of Land use types (LUTs) in Ogun River watershed (ORW) was investigated. ORW was stratified using proportionate sampling technique into Guinea Savannah (GS), Rainforest (RF) and Swamp Forest (SF) Ecological Zones (EZs). Three LUTs: Natural Forest (NF), Disturbed Forest (DF) and Farmland (FL) were purposively selected in GS: GSNF, GSDF, GSFL; RF: RFNF, RFDF, RFFL and SF: SFNF, SFDF, SFFL, respectively. Systematic line transects was used in the laying of the sample plots. Sample plots of 25 m×25 m were established in alternate positions. Ten 1 m×1 m quadrats were randomly laid for soil core sampling from previously randomly selected ten plots. The core samples (10) were pooled per plot in each LUT and placed in individual trays. Ten trays with sterilized soil were used as control. The trays were watered regularly and checked for seedlings emergence fortnightly for 18 months. The experimental design used was 3×3 factorial experiments. ANOVA, Diversity index (H') and Similarity index (SI) were used to analyze the data. There was significant difference in seedling emergence among ecological zones and land use types (p<0.05). A total of 4,400 seedlings emerged from the soil samples. All species were distributed among 32 families. FL in the RF had the highest number of germinated seeds (705±37.33 seedlings) followed by DF in the RF (701±49.6 seedlings). The lowest emergence was in NF of the SF (199±28.41 seedlings). DF in the RF had highest number of species (34) distributed among 22 families. Emergence from soil seed bank of NF in ORW was generally with more of tree species than herbs that were predominant in FL and DF.
Khan, Zahoor;Shafique, Maryam;Zeb, Amir;Jabeen, Nusrat;Naz, Sehar Afshan;Zubair, Arif
Microbiology and Biotechnology Letters
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v.49
no.1
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pp.65-74
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2021
Serine proteases are the most versatile proteolytic enzymes with tremendous applications in various industrial processes. This study was designed to investigate the biochemical properties, critical residues, and the catalytic potential of alkaline serine protease using in-silico approaches. The primary sequence was analyzed using ProtParam, SignalP, and Phyre2 tools to investigate biochemical properties, signal peptide, and secondary structure, respectively. The three-dimensional structure of the enzyme was modeled using the MODELLER program present in Discovery Studio followed by Molecular Dynamics simulation using GROMACS 5.0.7 package with CHARMM36m force field. The proteolytic potential was measured by performing docking with casein- and keratin-enriched residues, while the effect of the inhibitor was studied using phenylmethylsulfonyl fluoride, (PMSF) applying GOLDv5.2.2. Molecular weight, instability index, aliphatic index, and isoelectric point for serine protease were 39.53 kDa, 27.79, 82.20 and 8.91, respectively. The best model was selected based on the lowest MOLPDF score (1382.82) and DOPE score (-29984.07). The analysis using ProSA-web revealed a Z-score of -9.7, whereas 88.86% of the residues occupied the most favored region in the Ramachandran plot. Ser327, Asp138, Asn261, and Thr326 were found as critical residues involved in ligand binding and execution of biocatalysis. Our findings suggest that bioengineering of these critical residues may enhance the catalytic potential of this enzyme.
Chon, Sung-Bin;Lee, Min Ji;Oh, Won Sup;Park, Ye Jin;Kwon, Joon-Myoung;Kim, Kyuseok
The Korean Journal of Physiology and Pharmacology
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v.26
no.3
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pp.195-205
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2022
Determining blood loss [100% - RBV (%)] is challenging in the management of haemorrhagic shock. We derived an equation estimating RBV (%) via serial haematocrits (Hct1, Hct2) by fixing infused crystalloid fluid volume (N) as [0.015 × body weight (g)]. Then, we validated it in vivo. Mathematically, the following estimation equation was derived: RBV (%) = 24k / [(Hct1 / Hct2) -1]. For validation, non-ongoing haemorrhagic shock was induced in Sprague-Dawley rats by withdrawing 20.0%-60.0% of their total blood volume (TBV) in 5.0% intervals (n = 9). Hct1 was checked after 10 min and normal saline N cc was infused over 10 min. Hct2 was checked five minutes later. We applied a linear equation to explain RBV (%) with 1 / [(Hct1 / Hct2) -1]. Seven rats losing 30.0%-60.0% of their TBV suffered shock persistently. For them, RBV (%) was updated as 5.67 / [(Hct1 / Hct2) -1] + 32.8 (95% confidence interval [CI] of the slope: 3.14-8.21, p = 0.002, R2 = 0.87). On a Bland-Altman plot, the difference between the estimated and actual RBV was 0.00 ± 4.03%; the 95% CIs of the limits of agreements were included within the pre-determined criterion of validation (< 20%). For rats suffering from persistent, non-ongoing haemorrhagic shock, we derived and validated a simple equation estimating RBV (%). This enables the calculation of blood loss via information on serial haematocrits under a fixed N. Clinical validation is required before utilisation for emergency care of haemorrhagic shock.
Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.174-174
/
2023
The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.
Kim, Kyeong Sug;Choi, Su Jung;Jang, Su Mi;Ahn, Hyun Ju;Na, Eun Hee;Lee, Mi Kyoung
Journal of Home Health Care Nursing
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v.30
no.1
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pp.48-58
/
2023
Purpose: The purpose of this study was to construct a nomogram for predicting difficulty in peripheral intravenous cannulation (DPIVC) for adult inpatients. Methods: This study conducted a secondary analysis of data from the intravenous cannulation cohort by intravenous specialist nurses at a tertiary hospital in Seoul. Overall, 504 patients were included; of these, 166 (32.9%) patients with failed cannulation in the first intravenous cannulation attempt were included in the case group, while the remaining 338 patients were included in the control group. The nomogram was built with the identified risk factors using a multiple logistic regression analysis. The model performance was analyzed using the Hosmer-Lemeshow test, area under the curve (AUC), and calibration plot. Results: Five factors, including vein diameter, vein visibility, chronic kidney disease, diabetes, and chemotherapy, were risk factors of DPIVC. The nomogram showed good discrimination with an AUC of 0.81 (95% confidence interval: 0.80-0.82) by the sample data and 0.79 (95% confidence interval: 0.74-0.84) by bootstrapping validation. The Hosmer-Lemeshow goodness-of-fit test showed a p-value of 0.694, and the calibration curve of the nomogram showed high coherence between the predicted and actual probabilities of DPIVC. Conclusion: This nomogram can be used in clinical practice by nurses to predict DPIVC probability. Future studies are required, including those on factors possibly affecting intravenous cannulation.
Aliyu Ohiani Umaru;Olugbenga Okunlola;Umaru Adamu Danbatta;Olusegun G. Olisa
Economic and Environmental Geology
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v.56
no.3
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pp.259-275
/
2023
Pan African granitoids of Kaiama is comprised of K-feldspar rich granites, porphyritic granites, and granitic gneiss that are intruded by quartz veins and aplitic veins and dykes which trend NE-SW. In order to establish the geochemical signatures, petrogenesis, and tectonic settings of the lithological units, petrological, petrographical, and geochemical studies was carried out. Petrographic analysis reveals that the granitoids are dominantly composed of quartz, plagioclase feldspar, biotite, and k-feldspar with occasional muscovites, sericite, and opaque minerals that constitute very low proportion. Major, trace, and rare earth elements geochemical data reveal that the rocks have moderate to high silica (SiO2=63-79.7%) and alumina (Al2O3=11.85-16.15) contents that correlate with the abundance of quartz, feldspars, and biotite. The rocks are calc-alkaline, peraluminous (ASI=1.0-<1.2), and S-type granitoids sourced by melting of pre-existing metasedimentary or sedimentary rocks containing Al, Na, and K oxides. They plot dominantly in the WPG and VAG fields suggesting emplacement in a post-collisional tectonic setting. On a multi-element variation diagram, the granitoids show depletion in Ba, K, P, Rb, and Ti while enrichment was observed for Th, U, Nd, Pb and Sm. Their rare-earth elements pattern is characterized by moderate fractionation ((La/Yb)N=0.52-38.24) and pronounced negative Eu-anomaly (Eu/Eu*=0.02-1.22) that points to the preservation of plagioclase from the source magma. Generally, the geochemical features of the granitoids show that they were derived by the partial melting of crustal rocks with some input from greywacke and pelitic materials in a typical post-collisional tectonic setting.
For the precise measurements of special nuclear materials (SNM) including Pu and Am isotopes, we have used phoswich detector combination of two single crystal scintillators of Gd3Ga3Al2O12:Ce and CsI:Tl. High detection efficiency and sensitivity along with high figure of merit for the discrimination of these phoswich detectors ensures the detection and discrimination of thermal neutrons and gammas from spontaneous fission of Pu and other isotopes in presence of high gamma background. Using this detector, the low energy gammas, which is stopped completely in 1mm thick disc of GGAG, can be also discriminated from high energies gamma and shows linearity in wide range of sample quantities. By changing only the appropriate shielding, the similar setup was used for thermal neutron detection and shows a very good linearity over wide range. The quantity of a test sample was also calculated accurately by using the measured calibrated plot.
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