High Correlation Values Research Articles

Measurement properties of activity monitoring for a rehabilitation (AMoR) platform in post-stroke individuals in a simulated home environment

ABSTRACT Aim The aim of this study was to evaluate the measurement properties of activity monitoring for a rehabilitation (AMoR) platform for step counting, time spent in sedentary behavior, and postural changes during activities of daily living (ADLs) in a simulated home environment. Methods Twenty-one individuals in the post-stroke chronic phase used the AMoR platform during an ADL protocol and were monitored by a video camera. Spearman’s correlation coefficient, mean absolute percent error (MAPE), intraclass correlation coefficient (ICC), and Bland–Altman plot analyses were used to estimate the validity and reliability between the AMoR platform and the video for step counting, time spent sitting/lying, and postural changes from sit-to-stand (SI-ST) and sit-to-stand (ST-SI). Results Validity of the platform was observed with very high correlation values for step counting (rs = 0.998) and time spent sitting/lying (rs = 0.992) and high correlation for postural change of SI-ST (rs = 0.850) and ST-SI (rs = 0.851) when compared to the video. An error percentage above 5% was observed only for the SI-ST postural change (7.13%). The ICC values show excellent agreement for step counting (ICC3, k = 0.999) and time spent sitting/lying (ICC3, k = 0.992), and good agreement for SI-ST (ICC3, k = 0.859) and ST-SI (ICC3, k = 0.936) postural change. Values of the differences for step counting, sitting/lying time, and postural change were within the limits of agreement according to the analysis of the Bland–Altman graph. Conclusion The AMoR platform presented validity and reliability for step counting, time spent sitting/lying, and identification of SI-ST and ST-SI postural changes during tests in a simulated environment in post-stroke individuals.

The evaluation of the antioxidant activity of selected Eryngium species based on thin-layer chromatography fingerprints using chemometric tools

The purpose of the study was to confirm the utility of multivariate technique to predict antioxidant activity of selected Eryngium extracts based on chromatographic data. Five Eryngium species were analyzed using Thin Layer Chromatography (TLC) with silica gel to obtain their fingerprints. The highest relative content of quercitrin (marker) was observed for E. giganteum. The chemical similarity between extracts was evaluated by Principal Component Analysis (PCA) and Hierachical Cluster Analysis (HCA), and the results confirm the similarity between the same three E. planum from various natural sites. The total phenolic content with Folin–Ciocalteu reagent and antioxidant activity with DPPH reagent by spectrophotometry were determined, and the highest content of phenolics (concentration of gallic acid, mg⋅mL−1) was obtained for E. campestre, E. amethystinum and E. planum T. The highest antioxidant activity (concentration of gallic acid and inhibition %) were obtained for E. planum T. and E. amethystinum, while the lowest was obtained for E. planum Dębówka. High value of correlation coefficient between TLC and spectrophotometric data using Partial Least Squares Regression (PLS) confirms the usefulness of statistical method for the predicting the biological activity. In conclusion, the chromatographic and chemometric methods were suitable for prediction of antioxidant activity.

The Influence of Marketing Activities of Companies on Social Networks on the Purchase Decisions of Students

The study in this paper sought to assess how the company's marketing initiatives influence the purchasing choices of students. By surveying 230 students from the Faculty of Economics in Belgrade and analysing their responses, the researchers evaluated various aspects of the company's marketing strategies and the students' buying behaviour. Descriptive statistics revealed that the variables related to updating content on social media and utilising sponsored advertisements had the most significant impact, along with the variable of making purchasing decisions. The results of the regression and correlation analysis established the existence of statistically significant relationships and the influence of the variables of the company's marketing activity on the variables of students' purchase decisions. Based on the regression model of influence, it was determined that the variables of the company's marketing activities had the greatest impact on the variable of making purchase decisions, with the variables of sponsored ads and updating content on social networks making the greatest individual contribution. A two-component solution was obtained by factor analysis, where the first component gathered all the variables of the company's marketing activities and the purchasing decision variable, while the second component gathered the other variables of the students' purchasing decisions. Between these two components, increasingly high correlation values were found, which only indicates that there is a certain degree of variability between the company's marketing activities and students' purchasing decisions. The research conducted in this study aimed to determine the extent to which social media marketing is beneficial for students in finding products and services they need, as well as how influential it is in their purchasing decisions. It underscores the importance for companies to integrate social media marketing activities and determine the most suitable types of social media marketing strategies.

Development of a surfactant-assisted lanthanum anchored hydroxyapatite@polyaniline hybrid composite for the elimination of chromium ions from aqueous solution

The predominant cause of the global clean water deficit is water contamination caused by heavy metals discharged from various industrial effluents. Innovating low-cost adsorbents that can eliminate heavy metals from polluted water is essential to address this challenge. Human health can be negatively impacted by water contamination caused by the increased levels of carcinogenic heavy metals, such as chromium (Cr), found in wastewater. The main goal of this research is to remove chromium ions from an aqueous environment by utilizing the surfactant-assisted lanthanum anchored hydroxyapatite@polyaniline (CTAB-LaHAp@PANI) hybrid composite. Various analytical techniques including FTIR, XRD, SEM, EDX, TEM, TGA, and XPS analysis were utilized for the characterization of the prepared adsorbents. Different influencing factors such as contact time, solution pH, adsorbent dosage, and initial chromium concentration were systematically optimized through the batch method to achieve maximum removal efficiency of the CTAB-LaHAp@PANI hybrid composite. Remarkably, the CTAB-LaHAp@PANI demonstrated a maximal adsorption capacity of 98.2 mg/g, with an optimal contact time of 120 min at pH 3. The isotherm and kinetic analyses indicated that chromium adsorption onto the CTAB-LaHAp@PANI hybrid composite followed the Langmuir and pseudo-second-order kinetic models, supported by high correlation coefficient values. Moreover, the possible removal mechanism of chromium ions on the prepared hybrid composite was explained based on the results obtained from various analytical techniques. The as-prepared CTAB-LaHAp@PANI hybrid composite demonstrates a superior adsorption capacity, exceptional water stability, cost-effectiveness, and various other characteristics that render it an attractive choice for removing chromium ions from the aqueous phase.

Evaluation of Nine Planetary Boundary Layer Turbulence Parameterization Schemes of the Weather Research and Forecasting Model Applied to Simulate Planetary Boundary Layer Surface Properties in the Metropolitan Region of São Paulo Megacity, Brazil

This study evaluates nine Planetary Boundary Layer (PBL) turbulence parameterization schemes from the Weather Research and Forecasting (WRF) mesoscale meteorological model, comparing hourly values of meteorological variables observed and simulated at the surface of the Metropolitan Region of São Paulo (MRSP). The numerical results were objectively compared with high-quality observations carried out on three micrometeorological platforms representing typical urban, suburban, and rural land use areas of the MRSP, during the 2013 summer and winter field campaigns as part of the MCITY BRAZIL project. The main objective is to identify which PBL scheme best represents the diurnal evolution of conventional meteorological variables (temperature, relative and specific humidity, wind speed, and direction) and unconventional (sensible and latent heat fluxes, net radiation, and incoming downward solar radiation) on the surface. During the summer field campaign and over the suburban area of the MRSP, most PBL scheme simulations exhibited a cold and dry bias and overestimated wind speed. They also overestimated sensible heat flux, with high agreement index and correlation values. In general, the PBL scheme simulations performed well for latent heat flux, displaying low mean bias error and root square mean error values. Both incoming downward solar radiation and net radiation were also accurately simulated by most of them. The comparison of the nine PBL schemes indicated the local Mellor-Yamada-Janjic (MYJ) scheme performed best during the summer period, particularly for conventional meteorological variables for the land use suburban in the MRSP. During the winter field campaign, simulation outcomes varied significantly based on the site’s land use and the meteorological variable analyzed. The MYJ, Bougeault-Lacarrère (BouLac), and Mellor-Yamada Nakanishi-Niino (MYNN) schemes effectively simulated temperature and humidity, especially in the urban land use area. The MYNN scheme also simulated net radiation accurately. There was a tendency to overestimate sensible and latent heat fluxes, except for the rural land use area where they were consistently underestimated. However, the rural area exhibited superior correlations compared to the urban area. Overall, the MYJ scheme was deemed the most suitable for representing the convectional and nonconventional meteorological variables on the surface in all urban, suburban, and rural land use areas of the MRSP.

Analysis Of Factors In Tenders For Procurement Of Construction Goods/Services Using The E-Catalogue System

The government is updating regulations for procuring goods and services by introducing an e-catalogue system in the auction/tender process. Construction companies need to study the factors in tenders for the Procurement of construction goods/services using the e-catalogue system to ensure that the tender process using the e-catalogue system runs well and optimally. This research aims to analyze the factors in tenders for the Procurement of construction goods/services using the e-catalogue system. The method used was distributing questionnaires to small construction companies in Jombang Regency to collect data for further analysis. Based on data analysis, four factors were obtained, namely human resource factors (X1), principles of Procurement of goods and services (X2), infrastructure condition factors and e-catalogue support system arrangements (X3), and benefits factors for implementing e-catalogues (X4). The results were then tested for validity and reliability to ensure the validity and reliability of the data. Further analysis was carried out using descriptive analysis methods and Pearson correlation analysis. The results of the descriptive analysis show that the highest factor in tenders for the Procurement of construction goods/services using the e-catalogue system is the human resources factor (X1), with a mean value of 3.620 and a standard deviation value of 0.047. According to the research outcomes regarding Pearson correlations the relationship between factors that has the highest correlation value is (X1) with (X3) both have a strong correlation with a correlation value of 0.771.

Aerobic granular sludge sequencing batch reactor for high strength domestic wastewater treatment: Assessing kinetic models and microbial community dynamics

The study aims to treat high strength domestic wastewater (HSDW) and cultivate microbial granular sludge in a sequencing batch reactor (SBR). A bench-scale bioreactor was used for startup. Response surface methodology (RSM) was used to determine the ideal parameters for removing organic materials from HSDW. Organic loading rate (OLR) and cycle time were the independent variables taken into consideration, while the response variable was COD removal. Results from RSM revealed that the optimal conditions for achieving > 98 % COD and TP (>80) removal were a cycle length of 6 h and an OLR of 1.5 kgCOD/m3d. The Modified-Kincannon and the Grau second-order kinetic models were compared to the COD removal rate for the SBR system. The saturation rate constant (Ni) and maximal substrate removal rate (Vc) were proposed to be 6.8 g L−1 d−1 and 0.83 g L−1 d−1, respectively, based on the modified Stover-Kincannon model. The modified Stover-Kincannon (R2 = 0.93673) and Grau second order (R2 = 0.99219) models high correlation coefficient values show that the experimental results and the prediction for the microbial aerobic granular based SBR system accord well. It was discovered that the modified Stover-Kincannon model was less suitable than the Grau second order model. The system microbial community changed because of the granulation process, as the reactor design operation had a big impact on the community structure. Decreased filamentous bacteria favoured several taxa that have been found to exist in granular biomass that is appropriate for treating wastewater. This study sheds important light on the complex interactions that occur between microbial populations and operational variables all through the granulation process in SBR.

Classroom Management in Improving the Quality of Learning in the Education Units

This study focuses on classroom management in education units as a basis to improve the quality of learning. This process relates to the instruments used for data collection. The instrument consisted of thirty-five related to classroom management. The sample was 142 people who were spread in the education unit of Riau Province, Indonesia. Sampling was undertaken by random sampling in accordance with the readiness of the respondent. Data were analysed by substituting the respondents’ results through descriptive statistics, then using the Product Moment correlation method, the contribution of indicators in realizing the success of implementing learning through ANOVA. The average demographic data of the respondents was 4.273 (very high); compile a lesson plan was 4.304 (very high); carry out learning was 4.352 (very high); assess achievement was 4.233 (very high); carry out follow-up the results of the assessment of learning achievement was 3.813 (high). Quality did not vary with a very high correlation value so that it contributed a role in building class management up to 100%.

Klasterisasi Kabupaten/Kota di Provinsi Papua Berdasarkan Indikator Pembangunan Manusia Tahun 2022

The Human Development Index (HDI) is a human development metric empowered by several main elements that reflect the quality of life, namely HLS, RLS, PKK, and UHH. High HDI is one of the basic capital for a country's sustainable development. The improvement of human development in Indonesia continues to increase every year. However, there is still uneven development between regions in Indonesia. The HDI of Papua Province has always been the lowest in Indonesia in the last 10 years and each indicator is still unevenly distributed between districts/cities. This needs to be a special concern by the government. Thus, this study was carried out with the aim of grouping districts / cities in Papua Province based on human development indicators with the application of the agglomerative hierarchy cluster method. Based on the highest correlation value, Average Linkage is the best method with the optimal number of clusters formed is five clusters (Very High, High, Medium, Low, and Very Low) according to the Calinski-Harabasz Index test conducted. The findings of this study can be the basis for designing equitable development policies in districts/cities in Papua Province.

Single-beat mapping during programmed ventricular stimulation identifies infarct-related ventricular tachycardia isthmus sites

Abstract Introduction Complete characterization of reentrant ventricular tachycardia (VT) circuits using classical electrophysiological criteria and high-density mapping during VT is complex. Often, VT episodes cannot be fully characterized because of hemodynamic instability during the mapping procedure. This common limitation has motivated the implementation of mapping strategies during sinus rhythm or ventricular pacing aiming to identify scar regions associated with VT isthmuses or potential arrhythmogenicity. However, these strategies still require time-consuming catheter-based mapping. Purpose We aimed to develop and validate a single-beat mapping strategy during programmed ventricular stimulation (PVS) to identify scar regions associated with VT isthmus sites. We hypothesize that protected VT isthmuses within scar regions are characterized by larger activation time dispersion than surrounding scar areas not related to critical isthmus sites. Methods Experimental study including 16 pigs with established myocardial infarction (MI) in the anterior wall. Ten-to-twelve weeks after MI, pigs underwent left ventricular characterization using 3D late-gadolinium enhancement cardiac magnetic resonance imaging, and further invasive electroanatomical mapping to obtain high-density sequential activation maps during ventricular pacing and VT. High-density maps were compared with single-beat maps using a 64-pole basket catheter positioned in the left ventricle. After VT induction, high-density activation maps in well-tolerated VT episodes were used to identify VT isthmus sites. Simultaneous activation data from the 64-pole basket catheter were also obtained during PVS and VT. Off-line analysis was performed to: (i) validate single-beat activation maps during the baseline drive pacing cycle length (S1), and (ii) identify basket-catheter electrodes with the larger local activation time-dispersion score (LAT-DS) during PVS including up to 4 coupled extrastimuli (S2, S3, S4, S5) (Figure 1). LAT-DS was defined as the normalized product of the LAT of each electrode and the activation dispersion among its neighboring electrodes. Results Basket-catheter based single-beat activation maps during S1 pacing showed high correlation values with high-density sequential activation maps (N=16. R²=0.91). In 7 pigs, the VT isthmus site was fully characterized using high-density activation maps. During any of the coupled extrastimuli of the PVS protocol, basket catheter electrodes colocalizing with documented VT isthmus sites on high-density maps showed higher LAT-DS values compared to surrounding electrodes located on scar or healthy regions. Conversely, LAT values alone could not differentiate scar regions relevant for VT maintenance during PVS protocol (Figure 2). Conclusions Sixty-four pole single-beat activation maps during PVS identify left ventricular scar areas with higher than surrounding LAT-DS values that are associated with VT isthmus sites.Figure 1.Experimental modelFigure 2.A-Example. B-C-Full results

Cross-shelf transport of high chlorophyll-a coastal waters by frontal eddies in the south of Java sea

Intense mesoscale eddy activity has been observed off the southern Java coast (SJC), yet its impact on local ecosystems remains largely unknown. To investigate this, we examined remotely sensed altimetry, chlorophyll-a (Chl-a), and sea surface temperature (SST) data, focusing on their response to eddies in the region. Our eddy detection and tracking analysis revealed a unique cyclonic frontal eddy near the SJC coast and a large anticyclonic eddy offshore, active from July to September 2019. The cyclonic frontal eddy induced water transport through eddy filaments, upwelled subsurface cold water, and enhanced Chl-a concentrations by horizontally entraining Chl-a-rich shelf water offshore. The anticyclonic eddy then contributed to further distributing this enriched water southward. The mean cross-shelf transport associated with the frontal eddy was estimated at 1.80–2.33 Sv offshore, exporting approximately 1.87–2.40 × 103 tons of Chl-a to the Indian Ocean during its lifetime. Additionally, the spatial cross-correlation analysis of zonal and meridional wind stress with Chl-a revealed relatively high correlation values (0.6–1) and short lag times (<5 days) in offshore areas, indicating that the role of wind in the Chl-a advection cannot be ignored. We propose a three-stage mechanism to explain the presence of high Chl-a offshore:1) Wind-driven upwelling intensifies coastal nutrients, elevating Chl-a concentrations in coastal waters, 2) Frontal cyclonic eddy facilitates the retention and offshore export of these upwelling-enriched waters. and 3) Anticyclonic eddy advects these nutrient-rich waters further south. The combination of enhanced coastal upwelling and eddies can explain nutrient-rich coastal waters in offshore regions.

Correlation between serum 1,25-dihydroxyvitamin D and 25-hydroxyvitamin D in response to analytical procedures; a systematic review and meta-analysis

Abstract Objectives In this study, the aim is to provide a more detailed understanding of vitamin D metabolism by evaluating the correlation between 1,25-dihydroxyvitamin D (1,25(OH)2D) and 25-hydroxyvitamin D (25(OH)D) according to the variations in measurement methods and clinical conditions. Methods We searched PubMed, Embase, and Web of Science for studies reporting correlation results between 1,25(OH)2D and 25(OH)D. We performed a meta-analysis based on the correlation results of 1,25(OH)2D and 25(OH)D in different clinical conditions. We included a total of 63 studies and our laboratory’s results in the meta-analysis. The studies were categorized into high-quality methods group (HQMG), medium-quality methods group (MQMG), and low-quality methods group (LQMG) based on the 25(OH)D and 1,25(OH)2D measurement. Results In the healthy, renal disease, and other disease groups, the highest correlation values were observed in the studies categorized as HQMG, with values of 0.35 (95 % CI; 0.23–0.48), 0.36 (95 % CI; 0.26–0.42), and 0.36 (95 % CI; 0.22–0.48), respectively. Significant statistical heterogeneity was observed in the healthy, renal disease, and other disease groups, with I2 values of 92.4 , 82.7, and 90.7 %, respectively (p&lt;0.001). Both Funnel plots and the results of Egger’s and Begg’s tests indicated no statistically significant bias across all studies. Conclusions A significantly low correlation was found between 25(OH)D and 1,25(OH)2D. However, higher correlations were found in the studies categorized as HQMG. Various factors, including methodological inadequacies and disparities, might contribute to this. In the future, with more accurate and reproducible measurements of 1,25(OH)2D, a clearer understanding of vitamin D metabolism will be achieved.

Forecasting of the Dental Workforce with Machine Learning Models

The aim of this study is to determine the factors affecting the dental workforce in Turkey to estimate the dentists employed with machine learning models. The predicted results were obtained by applying machine learning methods; namely, generalized linear model (GLM), deep learning (DL), decision tree (DT), random forest (RF), gradient boosted trees (GBT), and support vector machine (SVM) were compared. The RF model, which has a high correlation value (R2=0.998) with the lowest error rate (RMSE=656.6, AE=393.1, RE=0.025, SE=496115.7), provided the best estimation result. The SVM model provided the worst estimate data based on the values of the performance measurement criteria. This study is the most comprehensive in terms of the dental workforce, which is among the healthcare resources. Finally, we present an example of future applications for machine learning models that will significantly impact dental healthcare management.

Evaluation of tensile failure behavior of ultra high performance concrete under double-edge wedge splitting and direct tension loadings

UHPC tensile strength is often measured indirectly through splitting tests and flexural tests substituted for direct tensile tests. However, the tensile strain-hardening and multiple cracking performance of UHPC is highly sensitive to the testing techniques and the specimen shape used. In this paper, the double-edge wedge splitting (DEWS) test and direct tensile test were performed to evaluate the tensile strain-hardening properties and damage evolution of UHPC. The digital image correlation (DIC) technique was utilized to detect the cracking opening displacement (COD) and evaluate the damage evolution in the tensile stress vs. crack opening response. The results show that the tensile strength between DEWS and direct tensile tests in UHPC strain-hardening and strain-softening stages had a high correlation value of 0.98. Moreover, the difference in cracking strengths in the DEWS and direct tensile tests was less than 5 %, and those of peak strengths were fewer than 5.23 MPa. An improvement in relative COD increment was observed in DEWS and direct tensile tests before 90 % of the peak load at the post-peak branch. Results indicate that the DEWS testing is an efficient way to evaluate the UHPC tensile failure properties.

Perception of maxillary incisor inclination and its correlation with dental cephalometric measurements.

To correlate the clinical perception of maxillary incisor inclination from photographs of the smiling face with cephalometric measurements, using conventional incisor axis reference points and crown reference points. Cross-sectional study. Department of Orthodontics, School of Dentistry, University of Lisbon (Portugal). Eight orthodontists. The perception of maxillary incisor inclination of 47 female patients (mean age 23.4 ± 1.5 years) was evaluated by eight orthodontists. The participants' photographs (smiling frontal, smiling three-quarter and smiling profile) were shown to each assessor and a continuous visual analogue rating scale was used to assess the perception of maxillary incisor inclination. Pearson's correlation and linear regression were calculated between each cephalometric measurement and the perception of incisor inclination. Anatomical crown inclination measurements U1ac-FH (r = 0.854; P < 0.01) and U1ac-SN (r = 0.845; P < 0.01) had the highest correlation values with the assessors' perception of maxillary incisor inclination. Conventional incisor axis measurements showed the lowest correlation values (r = 0.668-0.756). Cephalometric measurements of the labial surface of the anatomical crown of the maxillary incisors showed the strongest correlations with the clinical perception of maxillary incisor inclination from photographs. For optimal aesthetics, the inclination of the labial surface of maxillary incisor crown should be evaluated.

Improving pressure drop predictions for R134a evaporation in corrugated vertical tubes using a machine learning technique trained with the Levenberg–Marquardt method

The present investigation utilized a machine learning structure to ascertain the pressure drop in vertically positioned, corrugated copper tubes during the evaporation process of R134a. The evaporator was a counter-flow heat exchanger, in which R134a flowed in the inner corrugated tube and hot water flowed in the smooth annulus. Different evaporation mass fluxes (195–406 kg m-2 s-1) and heat fluxes (10.16–66.61 kW m-2) were used with artificial neural networks at different corrugation depths. A multilayer perceptron artificial neural network model with 13 neurons in the hidden layer was proposed. Tan-Sig and Purelin transfer functions were used in the network model developed with the Levenberg–Marquardt training algorithm. The dataset, which consisted of 252 data points, related to the evaporation process, was divided into training (70%), validation (15%), and testing (15%) groups in an arbitrary manner. The artificial neural network model has been demonstrated to effectively forecast the pressure drop that occurs during evaporation. The mean squared error was computed for the ΔP values observed during the evaporation processes, yielding a value of 1.96E-03. The artificial neural network exhibited a high correlation coefficient value of 0.94479. The estimation fluctuations exhibited a range of ± 10%, whereas the experimental and anticipated ΔP data demonstrated a divergence of ± 10.3%.

Temporal Complementarity Analysis of Wind and Solar Power Potential for Distributed Hybrid Electric Generation in Chile

We evaluate the temporal complementarity in daily averages between wind and solar power potential in Chile using Spearman’s correlation coefficient. We used hourly wind speed and solar radiation data for 176 geographic points from 2004 to 2016. The results allow us to identify four zones: Zone A1 on the coast and in the valleys in the north of Chile between latitudes 18° S and 36° S, with moderate positive correlation; Zone A2 in the north Andes between latitudes 25° S and 33° S, with weak negative correlation; Zone B in the center-south part of the country between latitudes 36° S and 51° S with moderate negative correlation; and Zone C in the south, between latitudes 51° S and 55° S with null or weak positive correlation. On the one hand, the interannual analysis shows that Zone A1 keeps uniform correlation values with negative asymmetry, i.e., higher correlation values. On the other hand, there is positive asymmetry in most of the years in Zone A2, i.e., lower (or negative) values of correlation. Zone B shows an interannual oscillation of the median correlation, while Zone C shows a larger dispersion in the interannual results. Significance analysis shows that 163 out of the 176 points are statistically significant, while Zones A1, A2, and B have significant correlations, with Zone C being marginally significant. The results obtained are relevant information for further studies on the location of hybrid generation facilities. We expect our methodology to be instrumental in Chile’s energetic transition to a 100% renewable generation matrix.

Specific features of the sorption of methylene blue by biochars based on pine and birch carbonizates

We obtained pine and birch biochars by carbonising sawdust at 500°C for 3 hours with a heating rate to the specified temperature of 10°C/min, with a fairly good yield for slow pyrolysis of 29% and 36% and particle sizes of up to 160 and 350 μm, respectively. Two-hour alkaline activation resulted in a decrease in particle size (20–60 µm for birch and 50-150 µm for pine coals), an increase in bulk and real densities, and a slight increase in pH. Using the energy dispersive analysis, we established the carbon basis of activated biochars and identified a tendency to an increase in the carbon content and a decrease in oxygen as a result of activation, which led to reduced O/C ratio of 0.258 for birch charcoal and 0.243 for pine charcoal. The kinetic sorption curves of the methylene blue dye on all studied coal samples were correctly described by a pseudo-second order model. The adsorption rate depended on the number of adsorption centres and was controlled by the contribution of the chemical reaction. A significant share of electrostatic interactions between the cationic dye and the negatively charged biochar surface could be expected. The sorption capacity of the initial and activated birch charcoal was twice higher than the corresponding pine samples. The Langmuir adsorption model correctly described the sorption of methylene blue on the studied biochars, which was confirmed by the high values of correlation coefficients. The efficiency of sorption purification from the cationic methylene blue on activated biochars from birch and pine reached 98 and 49%, respectively, which agreed well with the values of the adsorption capacity and sorption rates on these coal samples.

Psychometric Property Examination of a Self-Assessment Fear Scale in Turkish Children Aged 4-12 Years: A Methodological Study.

Background: Given the lack of validated tools to assess fear in Turkish children, this research aims to address this gap by conducting a methodological study to examine the validity and reliability of the Fear Scale, thereby providing health care professionals and researchers with a reliable instrument to evaluate fear levels in this population. Methods: The research was conducted on 150 children aged 4-12 years and their parents who applied to the pediatric blood collection unit of Koç University Faculty of Medicine Hospital. In the study, the "Sociodemographic Characteristics Form," "Fear Scale," and "Child Fear Scale" were used for data collection. Results: A very high statistically significant positive relationship was obtained between the Fear Scale and the Child Fear Scale (r = .973; p < .001). The high correlation value between the two forms indicates that the child form is valid. The content validity index and item content validity index values of the scale were found to be 0.98. A very good level of statistically significant agreement was achieved between the Fear Scale and the Child Fear Scale (κ = .878; p < .001). Conclusion: It was found that the Turkish psychometric properties of the Fear Scale are valid and reliable for children aged 4-12 years. It is suggested that pediatric nurses use the scale in clinics to evaluate their fear about procedural operations.

Ultrasonic velocity change imaging of a human forearm

Abstract We have investigated noninvasive imaging of the adipose region in the living human body, utilizing an ultrasonic velocity change (UVC) method caused by body temperature change. Our primary goal is to determine the optimal measurement conditions for acquiring effective UVC images. To achieve this objective, we applied the UVC method to the forearm area, which is easily comprehensible in terms of the body’s internal structure and less susceptible to motion artifacts from the heartbeat. By utilizing echo data approximately 30 s after initiating ultrasonic warming, adjusting the time difference between paired images for UVC image generation to multiples of the heartbeat period, and selectively extracting and analyzing image pairs with high correlation values, we successfully obtained effective UVC images targeting humans for the first time. This process enables noninvasive differentiation between subcutaneous fat and muscle regions in the human forearm.