High Recognition Research Articles

Bohlokwa bja dinonwane tša Sepedi thutong ya mabokgoni a ngwagakgolo wa 21

The aim of the study is to highlight the importance of folktales in the teaching of 21st Century skills in the Sepedi language classrooms. The learning skills to be discussed are communication, creativity, collaboration and critical thinking. The study followed qualitative approach and the data collection method used was document analysis method. The theory adopted for the study is Ethnography of Communication by Hymes (1962), supported with Text-Based Approach for Language Teaching as stated in Sepedi Curriculum and Assessment Policy Statement (CAPS: 2011). The findings for the study revealed that folktales have been around as long as the existence of man and they played a very important role in the teaching of indigenous people on how to go about in their lives. The study recommends that folktales should be part of the formal education and be given high recognition like other genres that are being taught in schools, also should be formally assessed. The study will benefit teachers and learners due to the fact that learners will be able to relate to the texts and learning will be easy for them.

Investigation of silicon doped carbon dots/Carboxymethyl cellulose gel platform with tunable afterglow and dynamic multistage anticounterfeiting

The remarkable optical properties of carbon dots, particularly their tunable room-temperature phosphorescence, have garnered significant interest. However, challenges such as aggregation propensity and complex phosphorescence control via energy level manipulation during synthesis persist. Addressing these issues, we present a facile gel platform for tunable afterglow materials. This involves chemically cross-linking biomass-derived silicon-doped carbon dots with carboxymethylcellulose and incorporating non-precious metal salts (BaCl2, CaCl2, MgCl2, ZnCl2, ZnBr2, ZnSO4) to enhance phosphorescence. Metal salts boost intersystem crossing via spin–orbit coupling, elevating triplet state transitions and activating phosphorescence. Chemical bonding and salt-induced coordination/electrostatic interactions establish confinement effects, suppressing non-radiative transitions. Diverse salt-gel interactions yield gels with tunable phosphorescence lifetimes (9.48 ms to 32.13–492.39 ms), corresponding to afterglow durations ranging from 3.20 to 11.86 s. With its broad tunability and high recognition, this gel material exhibits promising potential for dynamic multilevel anti-counterfeiting applications.

의료기관 종사자들의 전자의무기록 인증제 시행 목적에 대한 인식

This study was conducted to examine the perceptions of employees at tertiary and general hospitals, which have passed the certification of Electronic Medical Record (EMR) systems, regarding the objectives of the EMR certification program. The study was conducted from the perspectives of the public, medical institutions, and the industry. Data collection spanned from August 1 to October 31, 2022, involving responses from 1,187 employees across 11 or more accredited hospitals. The analysis included descriptive statistics, mean analysis, regression analysis, and Scheffé's analysis to understand the perceptions from the three different perspectives. The results revealed that from the public's perspective, the highest recognition was for “enhanced information security in medical information leading to the prevention of personal data breaches and security incidents” (t=-3.827, p<.01). From the perspective of medical institutions, the highest but not statistically significant recognition was for “improved clinical decision support such as medication warnings and effective history management of medical information, enabling safer and higher quality medical services” (f=-1.612). From the industrial perspective, there was high recognition for “the capability to meet market quality demands due to national recognition of EMR system quality standards” (f=-3.154, p<.01). Linear regression analysis was conducted to identify factors influencing the recognition of the objectives of the EMR certification system. The results showed that the model explained 27.4% of the variance for the public perspective, 26.9% for the medical institution perspective, and 28.6% for the industrial perspective, with all models being significant (P<.05). Following the implementation of the EMR certification system, medical institution employees positively perceived it from the perspectives of the public, medical institutions, and the industry. Future efforts should focus on enhancing system functionality awareness among employees, improving quality, and government and medical institutions should work together to enhance user interoperability of the system.

Celebrating Orthodontist’s highest recognition

Celebrating Orthodontist’s highest recognition

Fatores determinantes no reconhecimento de uma fonte usual de cuidado por adolescentes brasileiros

Abstract The present study aimed to analyze the demographic, socioeconomic, and health factors and risk behaviors associated with the recognition of a Usual Source of Care (USC), according to gender. This work was a cross-sectional study, based on the National Survey of School Health (2015), conducted with 100,464 Brazilian adolescents. Descriptive analyses were performed based on Pearson’s χ2, and the prevalence ratio (PR) through logistic regression models in Stata 14 for each type of USC (Primary Health Care (PHC), Private Practice, Hospital, and Emergency), stratified by sex. Recognition of a USC was reported by 55.5% of the adolescents, 58.6% of whom were female. In the multivariate analysis, the variables that present social, economic, and risk behavior inequalities showed positive associations for USC PHC for both genders. For the other types of USC, the demographic and socioeconomic characteristics showed negative associations. The results of this study showed that PHC is the service with the highest recognition among adolescents in conditions of social vulnerability. This reinforces the need to consolidate the PHC in order to favor the health care of adolescents, establishing bonds and improving access to health actions.

Determinants factors in the recognition of a usual source of care by Brazilian adolescents.

The present study aimed to analyze the demographic, socioeconomic, and health factors and risk behaviors associated with the recognition of a Usual Source of Care (USC), according to gender. This work was a cross-sectional study, based on the National Survey of School Health (2015), conducted with 100,464 Brazilian adolescents. Descriptive analyses were performed based on Pearson's χ2, and the prevalence ratio (PR) through logistic regression models in Stata 14 for each type of USC (Primary Health Care (PHC), Private Practice, Hospital, and Emergency), stratified by sex. Recognition of a USC was reported by 55.5% of the adolescents, 58.6% of whom were female. In the multivariate analysis, the variables that present social, economic, and risk behavior inequalities showed positive associations for USC PHC for both genders. For the other types of USC, the demographic and socioeconomic characteristics showed negative associations. The results of this study showed that PHC is the service with the highest recognition among adolescents in conditions of social vulnerability. This reinforces the need to consolidate the PHC in order to favor the health care of adolescents, establishing bonds and improving access to health actions.

Research on Cultural and Creative Design Based on Modal Theory and AIGC Technology

Abstract Modal theory is an important basis for studying cultural inheritance and dissemination. This paper combines modal theory and AIGC technology to innovate the cultural and creative design method. Through the calculation and analysis of modal recognition degree and other indicators, the modal factors that should be applied or innovated in cultural and creative design are identified. Using this paper’s cultural and creative design method, the analysis of Liangzhu culture and Shu brocade patterns is conducted separately. In the Liangzhu culture modal recognition, the higher recognition is pattern representation, morphological representation, and artifact function, and the lower recognition is color representation, aesthetic concept, material representation, and philosophical thought. The order of the popularity of the modal elements of pattern representations is from high to low: abstract pattern > animal pattern > geometric pattern. The traditional patterns of Shu brocade are in the order of color expression: A (0.209) > subject matter content, D (0.206) > surface features, C (0.162) > organization, B (0.148) > aesthetic meaning, F (0.138) > symbolic meaning E (0.137). When using AIGC to assist cultural and creative design, it is necessary to take into account the modal factors with smaller weight values to ensure that the final design can be loved by the public and achieve the dual goals of cultural heritage and economic benefits.

Analysis of the timeliness of teaching methods of university education oriented to comprehensive development in student management

Abstract With the development of higher education, the number and scale of college students are expanding, and the new situation poses challenges to the management of college students. This paper proposes a comprehensive development evaluation model for college students based on combination assignments and conducts a consistency test for expert ranking using Spearman’s rank correlation coefficient. The indicators are scored using the fuzzy affiliation degree method to eliminate the influence of dimensionlessness and the positive and negative differences between indicators. The correlation coefficient of G1 is corrected by standard deviation to determine the optimal combination of weights for the objective function, and it is dynamically adjusted according to the changes of the data in practice to reflect the degree of deviation and the comparative difference of each single weight. Finally, School C was chosen as the research object to study the timeliness of the comprehensive development teaching model in student management. The results show that among the 650 students in School C, the highest score of student comprehensive development evaluation is 4.083±0.65, which indicates that the comprehensive development evaluation in School C possesses goals and needs with high recognition as the premise of implementation and has strong theoretical and practical significance for the comprehensive development of college students.

In situ doped Cs2AgIn0.9Bi0.1Cl6:8%Yb,2%Er/PVDF composite films for the printing of multimodal fluorescent anti-counterfeiting marks

The fluorescent anti-counterfeiting technology has become one of the most desirable candidates in practical anti-counterfeiting applications owing to its adjustable emission, high recognition and design flexibility. However, the security level of single emitting fluorescent materials was lower, and no longer able to cope with current forgery techniques, so the development of higher level multimodal fluorescent anti-counterfeiting technologies was urgent. In this report, lead-free double perovskite (DP) material CsAgBiCl6 was chosen as the host and a technique for in situ growth in polymer polyvinylidene difluoride (PVDF) was proposed to obtain large-scale high-quality Cs2AgBiCl6/PVDF composite films (CFs). Subsequently, the Cs2AgIn0.9Bi0.1Cl6:8%Yb,2%Er/PVDF CFs with both down-conversion and up-conversion optical properties was achieved by hybrid (In3+/Yb3+/Er3+) doping, which was able to displayed inconsistent fluorescence emission (orange and green) under different excitation sources, and their fluorescence intensities exhibited tunability with the change of the environmental temperature, greatly enhancing its competitiveness in the field of fluorescent anti-counterfeiting. Finally, different anti-counterfeiting marks have been designed by the screen-printing process, and the complex encryption once again ensured the security of the information, while bringing a new gospel to the subsequent development of lead-free DP materials.

Attitude of cardiac surgery nurses on kinesiophobia management: a qualitative study

ObjectivesThis study aimed to investigate the knowledge, attitudes and practical experiences of cardiac surgery nurses regarding kinesiophobia management during early mobilisation.DesignUsing a descriptive qualitative research method, 21 cardiac surgery nurses...

Undetected Exogenous Insulin Administration in a Child: Assessment of Assay Limitations and Impact on the Practice of Laboratory Medicine

Abstract Introduction/Objective The development of new synthetic insulin analogues over the past few decades has significantly impacted the management of hypoglycemia. However, accurately measuring these analogues presents challenges due to variable cross-reactivity with many insulin assays. Failure to consider cross-reactivity may lead to the misdiagnosis of exogenous insulin administration. Methods/Case Report A 13-year-old female with a history of type 1 DM was presented to an outside hospital emergency department with symptoms indicative of hypoglycemia. Multiple child protective services (CPS) referrals are noted. The patient had experienced several episodes of hypoglycemia over the prior week with blood glucose in the 30-40 mg/dL range. There were no associated symptoms of diarrhea, emesis, or fatigue. The patient was transferred to a pediatric hospital were preliminary investigations indicated abnormally low blood glucose levels with low insulin and C-peptide levels. Further evaluation was initiated to determine the underlying cause of these episodes and to ensure appropriate adjustments in insulin dosing and regimen. Initially, the Elecsys insulin assay (Roche Diagnostics) was utilized to quantify insulin levels which shows a low cross-reactivity for insulin lispro and glargine. To validate the hypothesis of an undetected exogenous insulin overdose, blood samples were sent to another laboratory employing The Advia Centaur insulin assay (Siemens) which exhibits a higher cross-reactivity for insulin lispro and glargine (89%-143%, respectively), indicating a higher recognition and measurement sensitivity for these insulin analogues. The analysis using this assay revealed significantly elevated insulin levels, corroborating the presence of an insulin overdose. The sample at the time of presentation at the outside hospital was confirmed to be 434.1 mU/L. A sample collected 17 hours later had an insulin level of 23.5 mU/L. Results (if a Case Study enter NA) NA Conclusion This case study highlights the critical issue of undetected insulin overdose in a child and emphasizes the limitations of the initial insulin assay employed. Improving assay sensitivity and reliability will enhance patient care and safety. This case study reminds clinicians and laboratory professionals of the need for ongoing quality assurance and vigilance in their practices.

Effect of symptoms recognition in patients with recurrent acute myocardial infarction: from KRAMI-RCC

Abstract Background Clinical significance of self-recognition for myocardial infarction symptom in the general population has been well-known. However, evidence of self-recognition for ischemic symptoms in patients with recurrent myocardial infarction is limited. The study is aimed to verify the association between self-recognition and clinical characteristics, and clinical outcomes in patients with recurrent myocardial infarction. Method From 2016 to 2019, the Korean Registry of Acute Myocardial Infarction for Regional Cardiocerebrovascular Centers (KRAMI-RCC), a web-based registry for myocardial infarction in South Korea, was used. We divided into two groups based on self-recognition in questionnaire. Patient characteristics and clinical outcomes were analyzed. Result Among 11,894 MI patients, the rate of recurrent MI was 9.7%. The rate of self-recognition in subjects with first MI and recurrent MI was 14.4% and 52.0%, respectively (p<0.001). Patients without responses to the self-recognition questionnaire were excluded (n=86). Finally, enrolled subjects were 1,050. Males had a higher rate of self-recognition (79.3% vs. 69.0%). Younger patients, higher graduation levels, and living with a spouse were associated with the well-recognized symptoms. Chest pain, cold sweating, and radiating pain were related to being noticed as a symptom of MI. However, no difference of respiratory difficulties and stomachache in both groups was observed. The unrecognized group had more frequently occurred with cardiogenic shock and heart failure. A history of stroke and malignancy was associated with a low incidence of recognition. Patients with dyslipidemia had a high recognition rate. There was no difference of symptom recognition between ST elevation MI and non-ST elevation MI. Interestingly, previously registered patients in KRAMI-RCC were significantly associated with higher recognition. The symptom recognition was related to prompt visit in regional cardiovascular centers (57% vs. 47%, p=0.002). The in-hospital mortality rate in the unrecognized group was higher at 6.7% compared to the recognized group (1.5%, p<0.000). Unrecognized MI symptoms and a presentation with cardiogenic shock were independent predictors in multivariate analysis to predict a model for in-hospital mortality. Conclusion The MI symptom recognition rate was still low in patients with recurrent MI. Self-recognition of MI symptoms was an independent predictor for in-hospital mortality. In this study, it is thought that rapid symptom recognition might help patients with myocardial infarction visit the hospital as soon as possible, thereby reducing cardiogenic shock and death.Multivariable analysisSelf-recognition and Outcomes

Nutritional ingredients and functional components of cultivated and wild-simulated Astragali radix using widely targeted metabolomics

Commercial Astragali radix (AR) is mainly derived from cultivated Astragali radix (CAR) and wild-simulated Astragali radix (WAR). WAR has a higher recognition than CAR because it contains rich functional components. AR is an important medicinal and food-homologous substance; however, there is a lack of comprehensive evaluation of different planting patterns and their influence on AR nutritional content and medicinal components. Here, we investigated the total contents of amino acid (TAA), flavonoid (TFC), and phenolic acid (TPC) components in AR under different planting patterns and systematically compared them. CAR had high TAA content, whereas WAR had significant TFC and TPC amounts. A total of 674 metabolites, 330 primary and 344 secondary metabolites were identified. The nutritional differences between CAR and WAR can be explained by the accumulation of amino acids and their derivatives, lipids, saccharides and alcohols. Discrepancies in flavonoid, phenolic acid, and terpenoid contents produced differences in medicinal quality. Additionally, 110 key differential metabolites were screened, 88 of which were potential biomarkers, distinguishing between CAR and WAR. This study comprehensively characterized the metabolic products of AR, emphasizing their nutritional and medicinal value, and provided new insights on the differences in nutritional and health promotion ability between CAR and WAR.

Ultrahigh PLQY Lead‐Free Organic–Inorganic Hybrid Zirconium‐Based Perovskites in Anticounterfeiting Applications

AbstractOrganic hybrid halide perovskite, which has excellent characteristics of low cost, nontoxicity, and high recognition, has attracted extensive attention in optical anticounterfeiting applications. In this paper, (TEA)2ZrCl6 (TEA = tetraethylammonium) single crystals (SCs) are synthesized by an easy‐to‐operate hydrothermal method, which exhibits excitation wavelength‐dependent emission at 254 and 365 nm, respectively. Moreover, the photoluminescence quantum yield of (TEA)2ZrCl6 SCs achieves 84.7%, with the introduction of Sb3+ ions. (TEA)2ZrCl6 and doped (TEA)2ZrCl6 patterns can be recognized with excitation by different wavelengths. In addition, as‐prepared (TEA)2ZrCl6 crystals show interesting radioluminescence for another anticounterfeiting model with the light yield of 17 709 photons per MeV. The experimental results indicate the novel (TEA)2ZrCl6 SCs have a huge potential for X‐ray imaging and anticounterfeiting.

Significant Factors of Job Satisfaction among the Library Professionals in Tamilnadu: A Study

Library professionals play a vital role in supporting learning, research, and community development. Job satisfaction is important for these professionals as it can affect their motivation, productivity, and overall well-being. The researcher aims to evaluate the various job satisfaction factors among the library professionals in Tamilnadu. Data were collected through survey questionnaire method among the 150 library professionals and analysed using Principle Component analysis, Rotated component matrix and SPSS. This study resulted that 50% of the library professionals are satisfied with the salary, 48.2% of the respondents were satisfied with the promotion criteria, 45 % of the library professionals were happy about the job security, 69.8 % were felt the good relationship of the employer and the higher recognition.

Trends and hotspots in critical thinking research over the past two decades: Insights from a bibliometric analysis

Critical thinking has received significant scholarly attention in education over the years. This study conducted a bibliometric analysis of critical thinking during the last two decades (2000–2021) to identify research trends and hotspots of critical thinking. After data processing, 2043 publications related to critical thinking were retrieved from the Web of Science (WOS). Our analysis covers the number of publications per year, most used keywords, most productive countries/regions, institutions and authors, and most cited publications. The results show that critical thinking received increasing interest throughout this period; the research topics of critical thinking were rich and constantly evolving; the publications in western countries/regions have a stronger impact and higher recognition than do those in non-western countries; and critical thinking instruction has become the most popular research topic. This study holds important implications and should serve as a reference for future research.

지식산업센터 개발사업의 리스크 요인 및 관리방안 연구

1. CONTENTS (1) RESEARCH OBJECTIVES The purpose of this study is to preemptively explore the risk factors derived from the development process of the Knowledge Industry Center, which has recently been in the limelight as a new development project product, and to derive risk management measures for them. (2) RESEARCH METHOD As a research method, multi-level decision-making techniques (AHP and Fuzzy-AHP analysis methods) were used to analyze the importance of risk factors in each development stage and to derive risk management plans. (3) RESEARCH FINDINGS Risk management measures in order of importance include securing a construction company with recognition and brand, monitoring policy trends and adjusting business timing by development stage, establishing and verifying plans in preparation for product demand, blocking disputes through guarantee insurance, etc., and reducing risks through interest sharing. 2. RESULTS As a result of the analysis, it was confirmed that the overall importance of AHP and Fuzzy-AHP adjusted overall importance were similar in rank by risk factor. The top 5 risk factors as a result of importance are failure to secure a construction company with high recognition and brand, marketing planning, failure to select a project start time due to failure to predict the real estate economic downturn, failure to set an appropriate development scale that does not consider the future demand of the Knowledge Industry Center, failure to secure business partners (equity investors, financial companies, construction companies), and insufficient funding plan to secure project costs (bridge loans, main PF) appeared in order.

Multi-Objective Optimization Design and Experimental Investigation for a Prismatic Lithium-Ion Battery Integrated with a Multi-Stage Tesla Valve-Based Cold Plate

High current rate charging causes inevitable severe heat generation, thermal inconsistency, and even thermal runaway of lithium-ion batteries. Concerning this, a liquid cooling plate comprising a multi-stage Tesla valve (MSTV) configuration with high recognition in microfluidic applications was proposed to provide a safer temperature range for a prismatic-type lithium-ion battery. Meanwhile, a surrogate model with the objectives of the cooling performance and energy cost was constructed, and the impact of some influential design parameters was explored through the robustness analysis of the model. On this basis, the multi-objective optimization design of the neighborhood cultivation genetic algorithm (NCGA) was carried out. The obtained results demonstrated that if the MSTV channel was four channels, the valve-to-valve distance was 14.79 mm, and the thickness was 0.94 mm, the cold plate had the most effective cooling performance and a lower pumping power consumption. Finally, the optimization results were verified by a numerical simulation and an experiment, and the performance evaluation was compared with the traditional serpentine channel. The results reported that the optimized design reduced the maximum temperature and standard surface standard deviation of the cold plate by 26% and 35%, respectively. The additional pump power consumption was 17.3%. This research guides the design of battery thermal management systems to improve efficiency and energy costs, especially under the high current rate charging conditions of lithium-ion batteries.

A multi-channel convolutional neural network based on attention mechanism fusion for facial expression recognition

Abstract Facial expressions can reflect people’s inner emotions to a certain extent, and studying facial expressions can help psychologists capture expression information in time and understand patients’ psychological changes quickly. In this paper, we establish a multi-channel convolutional neural network face expression recognition model based on the fusion of the attention mechanism. With the help of the attention mechanism and multi-channel convolutional neural network, we input expression images and perform average pooling and maximum pooling, output the features with high recognition after pooling, and identify the features with high recognition in expression images throughout the process. And with the help of multi-scale feature fusion, we improve the detection of subtle changes, such as the corners of the mouth and the eyes of the expression image target. The loss function is used to calculate the loss rate of facial expression images, which leads to the correct rate of facial expression recognition by a multi-channel convolutional neural network based on the fusion of attention mechanisms. It is demonstrated that the highest recognition correct rate of the multi-channel convolutional neural network faces expression recognition model with attention mechanism fusion is 93.56% on the FER2013 dataset, which is higher than that of the MHBP model by 23.2%. The highest correct recognition rate on the RAF-DB dataset is 91.34%, which is higher than the SR-VGG19 model by 19.39%. This shows that the multi-channel convolutional neural network face expression recognition based on the fusion of attention mechanisms improves the correct rate of facial expression recognition, which is beneficial to the research and development of psychology.

Application of artificial intelligence for automatic cataract staging based on anterior segment images: comparing automatic segmentation approaches to manual segmentation.

Cataract is one of the leading causes of blindness worldwide, accounting for >50% of cases of blindness in low- and middle-income countries. In this study, two artificial intelligence (AI) diagnosis platforms are proposed for cortical cataract staging to achieve a precise diagnosis. A total of 647 high quality anterior segment images, which included the four stages of cataracts, were collected into the dataset. They were divided randomly into a training set and a test set using a stratified random-allocation technique at a ratio of 8:2. Then, after automatic or manual segmentation of the lens area of the cataract, the deep transform-learning (DTL) features extraction, PCA dimensionality reduction, multi-features fusion, fusion features selection, and classification models establishment, the automatic and manual segmentation DTL platforms were developed. Finally, the accuracy, confusion matrix, and area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the performance of the two platforms. In the automatic segmentation DTL platform, the accuracy of the model in the training and test sets was 94.59 and 84.50%, respectively. In the manual segmentation DTL platform, the accuracy of the model in the training and test sets was 97.48 and 90.00%, respectively. In the test set, the micro and macro average AUCs of the two platforms reached >95% and the AUC for each classification was >90%. The results of a confusion matrix showed that all stages, except for mature, had a high recognition rate. Two AI diagnosis platforms were proposed for cortical cataract staging. The resulting automatic segmentation platform can stage cataracts more quickly, whereas the resulting manual segmentation platform can stage cataracts more accurately.