Advanced Skills Research Articles

No-Shave Long Hair Follicular Unit Excision Using an All-Purpose Skin-Responsive Device.

Current no-shave long hair-follicular unit excision (LH-FUE) techniques employ recesses (slots, notches, or grooves) in punch tips to reduce the long-hair shaft break rate (SBR) and graft transection rate (GTR). However, these methods demand advanced skills and extended procedure time. We aimed to evaluate a skin-responsive FUE technique without the use of recess-tipped punches, accommodating diverse hair and skin types in LH-FUE procedures. We retrospectively analyzed patients who underwent this technique using a UGraft Zeus device at five multinational clinics (Mexico, Colombia, India, United States, and Türkiye) from August 9, 2021, to April 11, 2023. Donor zones were pre-operatively graded for expected difficulty using the Sanusi FUE Scoring (SFS) Scale, ranging from class I (low difficulty) to V (high difficulty). Among 152 patients (mean age, 46 years; 146 straight-wavy, 6 curly-coiled hair), most (n=107) were class I donors. The GTR ranged 2.2%-4.3%, and was highest in class IV donors and those with thick-firm scalps. The SBR was 12.2%, and the average graft excision rate (GER; speed) was 440 grafts/h. Only 19G and 18G punches were used. All patients were satisfied with the procedure, with 57.4% reporting that they were "very happy". Surgeon willingness to perform no-shave LH-FUE significantly increased from 1.25 to 4.20 (on a scale of 1-5) after adopting this device. SFS class, skin thickness, and firmness, more than hair curliness, influenced the GTR, SBR, torque, and punch movement duration. Our findings reveal consistent success in conducting no-shave LH-FUE using this skin-responsive device across diverse patients. Notably, success was achieved without recess-tipped punches, resulting in low GTR and SBR, along with a high GER and increased patient satisfaction. These outcomes suggest enhanced procedure speed and ease of use, contributing to a greater willingness among surgeons to adopt this technique.

Tips and Tricks to Facilitate the Combined Iliofemoral Endarterectomy With Stenting for Heavily Calcified Common Femoral Artery Atherosclerosis With Involvement of the External Iliac Artery.

Management of a heavily calcified atherosclerotic occlusive disease involving the common femoral artery (CFA) and external iliac artery (EIA), poses a surgical challenge. Though the current guidelines recommend open surgical therapy for such lesions, this approach is neither easy nor represents the current real-life practice. To describe tips and tricks facilitating the hybrid technique for the management of distal iliofemoral atherosclerotic disease, where classic endarterectomy is inadequate or ill-performed. A contralateraly inserted guidewire reaches the distal iliac artery via the crossover technique and is directly retrieved from the femoral arteriotomy immediately after removal of the anterior plaque segment. The retrieved and secured guidewire enables extensive retrograde CFA endarterectomy over the wire with avusion proximally to the inguinal ligement, followed by patch arterioplasty. Externalizing the guidewire from the patch enables traction on it and facilitates advancement of the stent through tortuous or stenosed iliac vessels as well as accurate stent deployment to cover the margin of the EIA residual plaque. Moreover, this manipulation enables ipsilateral placement of a sheath and passage of a second, retrograde guidewire to perform kissing stenting in the common iliac vessels. Chronic thrombotic lesions require covered stents to avoid thrombus propagation and meticulous flushing before completion of the femoral patching. The combined iliofemoral endarterectomy with stenting does not require advanced endovascular skills and prevents complications associated with incomplete femoral endarterectomy. Extensive avulsion endarterectomy proximal to the inguinal ligament is efficiently and safely performed over a retrieved crossover guidewire, enabling precise residual stenting above the flexion site.

Impact of Online Tumor Board Simulation for Optimizing Testing and Treatment of Patients with BRAFV600E- mutant Metastatic Colorectal Cancer

Abstract Introduction/Objective Approximately 10% of patients with metastatic colorectal cancer (mCRC) have BRAF genetic mutations, 90% of which result in a V600E substitution. Although there are targeted therapies available, there has been confusion about new and emerging testing and treatment options for BRAFV600E-mutant mCRC. Methods/Case Report To meet these needs, ASCP designed a 60-minute, self-paced, CME/CMLE online tumor board simulation to: increase knowledge, skills, and competence of pathologists and laboratory professionals to ensure patients with mCRC are appropriately and efficiently tested for BRAF mutations in accordance with NCCN guidelines, and enable pathologists to guide medical oncologists in the appropriate diagnosis, testing, and treatment of patients with mCRC. In the simulation, an expert pathologist and oncologist presented patient cases involving BRAFV600E-mutant mCRC. Learners answered questions designed to help them carefully consider the nuances of each case, building their knowledge and skills related to the detection and optimal management of patients with BRAF-mutant mCRC. Results (if a Case Study enter NA) 250+ learners have participated, with results demonstrating greater understanding of the NCCN guidelines for molecular testing of patients with mCRC, the clinicopathologic characteristics of BRAF-mutant mCRC. The tumor board simulation also increased awareness of strategies for improving turnaround times in biomarker testing for patients with mCRC, as well as current and emerging treatment options for BRAFV600E-mutant mCRC, which were two of the main goals of the education. Conclusion This project advanced knowledge, skills, and competence among pathologists and laboratory professionals, particularly those in community practice, to help ensure that patients who may be eligible for new and emerging therapies for BRAFV600E-mutant mCRC receive effective, optimized, and timely biomarker testing and treatment. The education may be useful to learners who want an increased understanding of BRAF mutations and their role in treatment selection.

How to get the most out of phylogenetic imputation without abusing it

Abstract Phylogenies are viewed as potentially powerful resources to predict missing values in trait datasets, but they are often misused. Critically, many of the imputed values that completely or partially rely on phylogenetic information are trusted without convincingly demonstrating that the data meet the requirements for the predictions to be at least minimally valuable. I discuss that phylogenetic signal, which is the mainstay of phylogenetic imputation, is often interpreted as ‘strong’ because the outcome of randomization tests has prevailed over the actual strength of the signal in determining whether it is strong or not. This circumstance has led many researchers to infer conclusions based on ‘strong’ signals that are actually way more labile than a phylogenetic random walk (i.e. Brownian motion). Although trait evolutionary trajectories that nearly fit Brownian motion are typically considered as strongly conserved, the Brownian process is subject to high levels of stochasticity that may render spurious predictions under some circumstances. To my knowledge, very few studies (if any) that rely on phylogenetically imputed information have rigorously evaluated the expected accuracy of individual predictions, despite among‐lineage variability in prediction accuracy can be dramatic even for strongly conserved traits. Here, I advocate for a Monte‐Carlo approach that is based on trait simulations to assess the prediction accuracy that is expected for each missing value in the traits of interest, which can be continuous or discrete. The framework is presented in a detailed step‐by‐step R tutorial that was conceived for non‐specialized researchers to identify highly likely spurious predictions without the need for advanced technical and statistical skills. Although phylogenetic imputation has important limitations, I suggest that leveraging advances in our understanding of such hindrances and using the technique with caution and restraint will allow trait‐based research to progress further while sampling efforts continue replacing imputed data.

The ramifications of Missing Nursing Care on adverse patient outcomes are profound. Insights gleaned from data offer valuable perspectives on nursing practices and their direct repercussions on patient well-being

The study aims to explore the correlation between missed nursing care and adverse patient outcomes. It delves into the reasons behind missed nursing care leading to negative patient consequences. The research framework employs missed nursing care as an independent variable and adverse patient outcomes as a dependent variable. Utilizing convenient sampling, this cross-sectional quantitative deductive study gathered data from nurses. All factors under scrutiny were assessed via questionnaires utilizing an appropriate Likert scale. Out of a total population of 411 nurses, 202 were sampled. The study's findings indicate a direct relationship between missed nursing care and adverse patient outcomes, demonstrating that an increase in missed nursing care corresponds to a rise in negative patient consequences. These outcomes were statistically significant, with reliable scales and valid data. The research concludes that reducing missed nursing care is pivotal for improving adverse patient outcomes. It recommends offering advanced skill courses, implementing thorough monitoring of nurses' activities, and mandating the self-reporting of missed patient care and adverse events

Measuring learning in digital games: Applying a game‐based assessment framework

Digital games (DGs) have the potential to immerse learners in simulated real‐world environments that foster contextualised and active learning experiences. These also offer opportunities for performance assessments by providing an environment for students to carry out tasks requiring the application of knowledge and skills learned in the classroom. Although widely used for teaching and learning, there are challenges in using digital game applications for assessment. Designing assessments around tasks in complex learning environments like DGs is not always easy, particularly for educators new to using these technologies for teaching. This paper presents a game‐based assessment framework (GBAF) that is designed to be educator‐friendly and useful for the design of assessments for immersive learning environments. The application of the framework to the design of embedded and external (multiple‐choice questions) assessments is also presented. The GBAF offered an easy and structured basis for the design of two distinct assessments for a computer game. It provides educators with useful guidelines for designing assessments around pre‐existing games. Practitioner notesWhat is already known about this topicImmersive technologies are increasingly being used for teaching and learning due to their benefits to knowledge and skills acquisition. However, for educators interested in using these tools for formal classroom teaching, there is a lack of resources and guidance on assessment designs and implementations. The most commonly used assessment design framework, the evidence‐centred design (ECD), is complicated to use, requiring advanced machine learning skills to implement. This has so far limited its use to large‐scale computerised and game‐based testing.What this paper addsThis paper presents a framework developed to guide educators through the design and implementation of assessments when teaching with immersive learning applications. Grounded in the constructive alignment principles and the ECD framework, the game‐based assessment framework is designed to help educators align assessment tasks to game tasks and the intended learning outcomes. It also provides step‐by‐step guidelines for the identification of appropriate immersive applications. It shows the practical application of the framework to the design of embedded (in‐game) assessments and external (multiple‐choice tests) assessments.Implications for practice and/or policyThe framework presented in this paper provides a structured and pedagogically sound basis for the design of assessments when measuring performance, or skills and knowledge acquisition with immersive learning applications.

MENTORING IN INTEGRATING HOTS (HIGHER ORDER THINKING SKILLS) IN READING ASSESSMENT


 High Order Thinking Skills (HOTS) have been a topic of discussion among educators in Indonesia in recent years. The awareness of the importance of making test questions that contain HOTS is getting higher after seeing the test results of Indonesian students in several international standardized test events such as the Program of International Student Assessment (PISA) and Trends in International Mathematics and Science Study (TIMSS). It is a fact that PISA test and evaluation, the performance of Indonesian students is still relatively low. Consecutively, the average achievement scores of Indonesian students were ranked 62, 61, and 63 out of 69 countries evaluated. The fact drives this community service is done to enhance teachers’ competence in integrating HOTS into assessment, particularly in reading skills. The aim of this community service is to mentor Senior High School teachers who teach English Subjects with advanced skills to construct item tests that emphasize higher-order thinking skills in reading skills. The methods employed to achieve the goal are mentoring and focus group discussions. The result of this supervision is the increased ability of teachers in developing assessment of reading skills. This can be seen when the initial observation of the assessment of learning collected and analyzed was seen to have HOTS elements only 50%, and after the supervision and Focus Group Discussions were held, the ability was seen to increase to 80%, which means that the reading assessment created by Wijaya Putra High School teachers contain HOTS questions much higher than the initial conditions. In conclusion, this service activity is able to improve teachers' skills in developing HOTS-in reading assessments.

Design and Optimal Pose‐Constrained Visual Servoing of a Novel Active Flexible Endoscope Holder System for Solo Laparoscopic Surgery

Laparoscopic surgery (LS) has become an effective and widely accepted therapy for patients. However, performing LS requires advanced training and skills, as it demands high precision and dexterity due to visual feedback depending on the collaboration between the surgeon and endoscope assistant, restricted field of view, and limited dexterity inside the body. Thus, a flexible endoscope holder system with an automatic control scheme is proposed to assist LS performance, allowing the surgeon to perform solo LS. A DNA‐inspired helix‐based structure with wide‐angle and constant curvature bending is presented and made of printable nylon with selective laser sintering. The proposed flexible mechanism reduces the cost of manufacturing and assembling. Also, it has a hollow design for embedded sensing and actuation. Then, an optimization method is proposed, which provides a reference for the endoscope installation, robot placement, and pose selection. In addition, aiming at the misorientation problem, a pose‐constrained visual servoing control scheme for the endoscope system is developed. Both simulation and physical experiments are conducted to verify the effectiveness and feasibility of the proposed control scheme. Experimental results demonstrate that the proposed visual servoing scheme can maintain the optimized pose and reduce misorientation during automatic view steering.

Identifying the need to institutionalize digital equity among faculty: the experience of the Kenya Medical Training College

BackgroundThe use of digital tools and applications in health professions education is increasing exponentially, however this has the potential to increase the digital inequities with the resulting effect of vulnerable groups facing an increased risk of digital exclusion. It is therefore important to approach digitalization with contextual determinants of the intended and unintended impact in mind. We present a perspective paper on digital equity, informed by lessons learnt at the Kenya Medical Training College (KMTC).MethodsUsing a case description methodology, we examined routine educational data collected from faculty at KMTC in November 2022. This included quantitative and qualitative data on access, ownership, utilization, confidence and skills to create, share, and exchange knowledge on the institution’s learning management system. We used these factors as the conceptual framework for understanding how faculty adopt digitalization in health professions education.Results306 faculty responded to the survey (response rate 27.8%) of whom 90.8 and 75.2% had personal laptops at home and at work and 75.9% had internet at work. 53.4% (n = 163) knew they had accounts created on the institution’s learning management system (LMS) majority of whom had basic skills and were able to perform skills such as logging in and accessing learning resources. However, a minority had advanced skills needed for teaching and learning in the LMS.ConclusionMedical education institutions in LMICs need to adopt programs to enhance digital literacy and monitoring of access, utilization and self-efficacy across all learner and faculty groups, to ensure that digital technologies reduce rather than exacerbate existing inequities.

Increased in-hospital complication risk in women undergoing chronic total occlusion recanalization

Abstract Introduction Percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) is a complex procedure that requires advanced operator skills and dedicated devices. Despite increasing success rates of up to 95% in experienced centers, in-hospital complications associated with CTO PCI remain high, and predictors of short-term outcomes and complications are yet scarce. Female sex is often observed to be correlated with in-hospital complications in complex interventions, but current evidence related to CTO PCI is ambiguous and inconclusive. Our aim was to investigate the potential impact of sex on individual and composite in-hospital complications associated with CTO PCI. Methods We prospectively included patients undergoing CTO PCI at our university-affiliated tertiary care center over four years (2018-2021). In this analysis, we compared comprehensive baseline characteristics and angiographic parameters between men and women and estimated their correlation with a composite endpoint of in-hospital complications using adjusted logistic regression analysis. We presented group differences related to individual component in-hospital complications. Results Out of 271 patients undergoing antegrade or retrograde CTO PCI, 222 (81.9%) were men, and 49 (18.9%) were women. Compared with men, women were older (67 ±11 vs. 72±12 years, P=.005) and had less prior PCI (65.8% vs. 44.9%, P=.006). Both groups had comparable angiographic complexity. Overall MACCE was 2.6%, and any in-hospital complication occurred in 8 women (16.3%) and 15 men (6.8%). Univariate analysis showed that sex, J-CTO score, and proximal cap ambiguity were correlated with the primary composite endpoint. By adjusted multivariate analysis, sex was independently associated with any in-hospital complication (OR=.334; CI .129 to .864; P=.024). The results were numerically driven by major bleeding, acute kidney injury, and MACCE. Conclusion Our findings suggest that women undergoing CTO PCI are at an increased risk of any in-hospital complication, regardless of clinical severity. Further studies are needed to confirm this finding and explain potential gender disparities in patients undergoing CTO PCI.Clinical and angiography characteristicsIn-hospital complications

“ Hippapai !” Horse-Carriers: A Master Ship of Ancient Thalassocracies

Summary Most powerful ancient navies included a type of ship that conveyed cavalry known as hippagogos – a master weapon of all sea powers – to carry out their expeditions overseas. Ancient thalassocracies understood that their dominion depended not only on fighting ships. Cavalry was necessary for victory on land and was thus a necessary component of their maritime strategy. Control of Mediterranean waters necessitated the construction of horse-carriers that provided much needed auxiliary support to the fleet. Although a naval force might include only a few of these vessels, their role was essential, and for this reason they were part of every significant fleet. Only sea powers with large resources and advanced nautical skills could commission horse-transports, which were old warships that had been transformed. This investigation traces the evolution in the use of vessels conveying cavalry from Persian expeditions in the Aegean to the Battle of Actium. The study considers the literary and epigraphic sources evidencing them in order to emphasize their continued importance for the evolution of naval warfare throughout antiquity. Athenian horse-carriers are the best documented examples and are considered the most extensively, even though many other powers used these kinds of vessels. At the peak of their maritime empire, the Athenian employed horse-carriers on multiple occasions against their enemies. The city-state was renowned for them to the extent that Aristophanes dedicated a comedic episode to them in his play Knights, which indicates the great interest of elites in these vessels. The article also reassesses the role of the cavalrymen who played pivotal roles in the expeditions of all maritime empires in antiquity.

Facilitating “Omics” for Phenotype Classification Using a User-Friendly AI-Driven Platform: Application in Cancer Prognostics

Precision medicine approaches often rely on complex and integrative analyses of multiple biomarkers from “omics” data to generate insights that can help with either diagnostic, prognostic, or therapeutical decisions. Such insights are often made using machine learning (ML) models that perform sample classification for a particular phenotype (yes/no). Building such models is a challenge and time-consuming, requiring advanced coding skills and mathematical modelling expertise. Artificial intelligence (AI) is a methodological solution that has the potential to facilitate, optimize, and scale model development. In this work, we developed an AI-based, user-friendly, and code-free platform that fully automated the development of predictive models from quantitative “omics” data. Here, we show the application of this tool with the development of cancer survival prognostics models using real-life data from breast, lung, and renal cancer transcriptomes. In comparison to other models, our generated models rendered performances with competitive sensitivities (72–85%), specificities (76–85%), accuracies (75–85%), and Receiver Operating Characteristic curves with superior Areas Under the Curve (ROC-AUC of 77–86%). Further, we reported the associated sets of genes (biomarkers) and their expression patterns that were predictive of cancer survival. Moreover, we made our models available as online tools to generate prognostic predictions based on the gene expressions of the biomarkers. In conclusion, we demonstrated that our tool is a robust, user-friendly solution for developing bespoke predictive tools from “omics” data, which facilitate precision medicine applications to the point-of-care.

Artificial intelligence and the demand for skills in Russia

The problem of digital transformation of the labor market is widely discussed in the current scientific literature. In the context of the rapid spread of modern information technologies, in particular artificial intelligence (AI), many companies inevitably face difficulties in hiring highly qualified personnel. At the same time, research still lacks a clear understanding of the pace of AI adoption in different occupations, as well as what knowledge, skills, and abilities are actually in demand by employers. This study analyzes the demand for worker skills and the salaries offered by employers within firms, industries, and occupations. By focusing on AI skills, this paper adapts and extends the application of mainstream empirical methodology to the understudied context of the Russian labor market. The study uses data from firms and online job advertisements for the period from 2007 to 2020, and conducts econometric analysis to estimate the demand for skills. The results of the study show a rapid growth in the demand for AI skills in Russia, which is associated with significant wage premiums for these skills. However, when combined with other skills, the effect of AI skills can be negated. For example, the results suggest that basic and advanced computer skills are negatively complementary in terms of demand, which may lead to lower wages. Moreover, in the context of the Russian labor market, the demand for nontechnical skills in AI-related jobs is not associated with offering higher wages

Education and training for industry 4.0: a case study of a manufacturing ecosystem

PurposeThe purpose of this paper is to explore the approaches to education and training adopted by manufacturing organisations to identify and develop a set of learning principles for the successful transition to Industry 4.0.Design/methodology/approachA case study of a manufacturing ecosystem in Queensland, Australia was undertaken, that included semi-structured interviews with a total sample of 22 manufacturing industry representatives, an analysis of secondary data including organisational documents and government reports, and embedded cases of two manufacturing organisations.FindingsManufacturers successfully transitioning to Industry 4.0 are distinguished by a culture which values learning, management development to understand and lead innovation, experimental learning on the job and strong links to education and training providers through internships and upskilling pathways. These four principles inform approaches to creating tailored training solutions that respond to the unique needs of diverse manufacturing organisations.Research limitations/implicationsThe two case studies describe exemplary high performing companies only and not companies at earlier stages of adopting Industry 4.0. Therefore, future research could include a broader spectrum of companies across the adoption spectrum. Nevertheless, considered as a study of a total manufacturing ecosystem, there is strong alignment of views of government, industry, union and education stakeholders regarding the key factors of transition to Industry 4.0.Practical implicationsThere is a strong need for leaders of manufacturing organisations to enable a broad strategy of capability development beyond simple acquisition of new technologies. Detailed consideration and resourcing of on-the-job training and experimentation, talent attraction through innovation workplace cultures and strong relationships with education providers are important.Social implicationsGiven that Industry 4.0 technologies such as robotics and AI are now rapidly diffusing into other industry sectors, the research has broader implications for education and training for the future of work. These technologies could produce stark differences between efficiency versus innovation-oriented adoption strategies. Whilst the former could displace workers, the latter can open pathways for upskilling, product and process innovation and cross sector employment.Originality/valueThrough the ecosystem level case approach, multiple stakeholder perspectives provide triangulated insights into advanced manufacturer's education, skills and training strategies, uncovering four learning principles that underpin the approach of manufacturers successfully transitioning to Industry 4.0. The findings have practical implications for policy makers and industry bodies supporting the transition to advanced manufacturing and provide manufacturing managers with insights into successful education and skill strategies that can be adapted to specific organisational needs.

Abstract 349: Deep Learning Detection of Chest Compression Location Using Transesophageal Echocardiography

Background: Recent work evaluating intra-arrest transesophageal echocardiography (TEE) in cardiac arrest (CA) has demonstrated that chest compression (CC) location is a strong predictor of return of spontaneous circulation. However, advanced skills to interpret images during resuscitation represent an important barrier to implementation of this modality. Deep Learning (DL) models have been increasingly used to perform the automated interpretation of TEE images. Given the unique challenges during the interpretation of images, DL-based automation represents an attractive adjunct to facilitate the use of intra-arrest TEE. We sought to evaluate the feasibility of a DL model to identify CC location in TEE images obtained during CA resuscitation. Methods: We analyzed videos from out-of-hospital and in-hospital CA patients evaluated with TEE collected through the Resuscitative TEE Collaborative Registry (NCT04972526). We reviewed and selected images for the DL algorithm, using midesophageal long axis clips. Videos were selected based on the visualization of anatomical structures necessary to identify the CC location. Images were annotated by an expert classifying them in CC over the LV (CC-LV) vs CC over the left ventricular outflow tract (CC-LVOT). We used TEENet, an end-to-end DL approach with input of TEE clips containing single compression cycles, to classify clips in CC-LV and CC-LVOT. The TEENet architecture includes two 3D convolution layers, followed by a global average pooling layer, and then appends a fully connected layer with a sigmoid layer. We used the F1-score as the evaluation metric for the model's performance. Results: Ten videos containing a total of 47 single CC cycle clips were selected for inclusion in the model, each clip with an average of 25 frames. The model was trained using 80% of the data (37 clips) and tested using the remaining 20% (10 clips). The model achieved an F1-score of 0.7273 in classifying CC-LV from CC-LVOT. Conclusion: We report the creation of a novel DL-model with acceptable precision and recall performance in the detection of CC location using intra-arrest TEE videos. This work is a proof-of-concept for future research aimed to evaluate the potential of DL-assisted TEE-guided CA resuscitation.

From Compliance to Play: Enhancement of Phonemic Awareness Through Play-Based Learning Activities in Kindergarten

Phonemic awareness is a skill that begins developing from birth and continues to develop throughout a child’s early years. In the context of 21st-century learning, there is a growing demand for students to establish a solid foundation in this skill during their early developmental stages. Despite the recognized importance of phonemic awareness, there have been instances of low achievement in this area. This study aimed to assess the impact of incorporating play-based activities on improving phonemic awareness in kindergarten learners. The variables examined within phonemic awareness include letter sound fluency, blending, and segmenting. The study employed a quasi-experimental research design and utilized purposive sampling. A total of 20 kindergarten learners from Tangway Loob Elementary School participated in the study. The primary instruments for data collection were pre-tests and post-tests. The findings revealed that, before the implementation of play-based activities, kindergarten learners had a mean phonemic awareness score of 42.58, interpreting a moderate level of awareness. After the intervention, the learners attained a mean of 56.53, also interpreted as a moderate level of awareness. The analysis revealed a significant improvement in letter sound fluency and blending skills between the pre-test and post-test assessments. However, no significant difference was observed in terms of segmenting. In conclusion, this study demonstrated the effectiveness of incorporating play-based activities in enhancing the phonemic awareness of kindergarten learners. It is recommended that these activities be integrated into instructional practices to further develop phonemic skills, which serve as a crucial foundation for more advanced literacy skills.

Associations between cooking skills, cooking with processed foods, and health: A cross-sectional study.

To improve health outcomes, home cooking has been suggested as a solution to reduce intakes of processed foods. However, little is known about how cooking skills or cooking with processed foods influence health. This cross-sectional study examined associations between diet and health outcomes with cooking skills and cooking with processed foods. The dataset included a nationally representative sample of 18,460 adults from Canadian Community Health Survey (CCHS) annual component rapid response modules on food skills. In the CCHS rapid response modules, diet and health outcomes (fruit and vegetable intake, general health, mental health, and obesity), cooking skills and cooking with processed foods were collected through self-report. Separate logistic regression models were fitted for each outcome, controlling for age, income, and education, and stratified by sex. Adults with poor cooking skills were less likely to have adequate fruit and vegetable intake (≥5 servings per day) (p<0.001), very good general health (p<0.001) or mental health (p<0.001), and obesity (p=0.02), compared to advanced cooking skills. Adults who cooked with highly processed foods were less likely to have adequate fruit and vegetable intake (p<0.001), very good general health (p=0.002) or mental health (p<0.001), but more likely to have obesity (p=0.03), compared to cooking with minimally processed foods. Cooking skills alone appear insufficient to protect against obesity. Results suggest that not only are cooking skills important, but the quality of ingredients matter. Limiting the use of processed foods in addition to improving cooking skills are potential intervention targets to promote better health and diet outcomes.

Analysis of pigments and mortars from the wall paintings of the Roman archaeological site of Las Dunas (San Pedro de Alcántara, Malaga S Spain)

This study aims to describe the composition, texture, and arrangement of mortars and pictorial layers from a newly excavated Roman archaeological site in the province of Baetica, southern Spain. Representative fragments with well-preserved pictorial layers were analyzed using optical imaging, spectrophotometry, Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS) mapping, and X-ray diffraction. The results reveal similarities to other well-studied Roman archaeological sites, particularly in the use of mixtures of natural (hematite, goethite, aragonite, phyllosilicates, and quartz) and synthetic minerals (cuprorivaite) used in classical Roman pigments. However, the mortar from the investigated site shows a distinctive use of ferromagnesian silicates (olivine and pyroxenes from local ultramafic rocks) as aggregate material, making this site unique among all Roman provinces. Additionally, the common occurrence of Mg in the binder of the mortars under the form of brucite, hydromagnesite and magnesium silicate hydrates, indicates the use of a magnesian (dolomitic) lime that, according to the chemical analyses, was obtained by adding up to 15 wt% of powdered dolomitic marbles from nearby Roman quarries to the limestone. We speculate that this addition might be intended to improve the workability and mechanical resistances of the mortar in combination with the abundant ferromagnesian silicates used as aggregates, some of them showing chemically reactive rims in contact with the binder. In conclusion, this study provides further evidence of the advanced knowledge and skills achieved by Roman craftsmen who were able to adapt traditional recipes to suit local resources, obtaining materials of excellent quality and durability.

Designing a Master of Accounting Study Program Profile Website Using the Wordpress Content Management System

This article discusses designing a study program profile website using the WordPress Content Management System (CMS). Higher education has a need to present relevant and up-to-date information to prospective students, students, lecturers and the general public. A study program profile website can be an effective tool to meet these needs. The design method used in this research involves the needs analysis stage, interface design, selecting an appropriate WordPress theme, developing special features relevant to the study program, and testing functionality. Using the WordPress CMS as a content management platform makes it easy to manage and update content independently without requiring advanced programming skills. The result of this research is a study program profile website that is responsive, attractive, and easy to navigate. The features implemented include information about study programs, curriculum, lecturers, facilities and the latest news. Apart from that, it is equipped with a search feature to make it easier for users to find the specific information they want. Implementing the WordPress CMS as a content management platform provides time and cost efficiency benefits in managing a website. In addition, the flexibility and ease of adding or changing content ensures that the information presented is always up to date and relevant. In conclusion, designing a study program profile website using CMS WordPress is an effective solution for presenting up-to-date and relevant information to stakeholders in the academic environment. This research makes a contribution to the field of information technology, especially in the use of CMS platforms for efficient content management in the context of higher education.

Defining competencies for training non-native Korean speaking teachers: a Q methodology approach

Abstract Learners of Korean are increasing globally, but this growth can only be sustained by training local non-native teachers. To address this issue, this paper identifies the subjective perspectives of Korean language teaching professionals about the main competencies needed by non-native Korean teachers. Following a Q methodology protocol, 35 teachers sorted 42 statements about non-native Korean teacher competencies. The analysis identified four perspectives. Factor 1 stresses the ability to adapt teaching to the learning context and Korean language proficiency. Factor 2 stresses the importance of pursuing continuous professional development without deeming a near-native language proficiency essential. Factor 3 stresses the need to love the language and the ability to maintain advanced language skills. Factor 4 again stresses the need to love the Korean language, the profession, and the importance of a strong sense of responsibility as an educator. Results are discussed with reference to teacher training program design.