Comprehensive Procedure Research Articles

Group Decision Making in Competency-Based Medical Education - Clinical Competency Committee

<p>臨床能力委員會(Clinical Competency Committee, CCC)在勝任能力導向醫學教育的總結性評量中扮演重要的角色。委員會根據以評量藍圖執行的職場觀察評量結果，進行系統性的討論，對學員的能力進展做出公正可靠的判斷，回饋給相關利害關係人，並協助學員擬定個人化之補強訓練計畫。進行會議前應有共識會議、師資培育課程、及學員能力進展資料閱讀，事前的學員自我評量能夠促進學員與教師對學員能力進展的認知，並促進學員對於教師回饋的接納理解程度；會議中須建立結構化的決策過程，最終獲得客觀且可信的決策成果；會議後應向學員提供回饋，並協助制訂補強學習計畫或提供訓練協助規劃。藉由完善的CCC程序，可提升臨床醫事人員的訓練品質、教師教學水準、醫療服務品質及專業認同。</p> <p> </p><p>Clinical Competency Committee (CCC) plays a key role in the summative assessment of competency-based medical education (CBME). Specifically, CCC conducts systematic discussions according to the results of workplace observation and assessment derived from assessment blueprints to provide an accountable and reliable judgment on the progression of trainees’ competencies. CCC then informs assessment results to stakeholders and assists trainees in developing personalized remedial learning plans. CCC members should conduct a consensus meeting, complete faculty training courses, and review trainees’ competency development data before calling a CCC meeting . Student self-assessment should also be completed before the CCC meeting to improve trainees’ and CCC members’ understanding of the progress of their competency development and to ensure that trainees agree with and accept teachers’ feedback. During the CCC meeting, a structured decision-making procedure must be constructed for objective and credible decision-making. After the meeting, feedback should be provided to students to assist them in developing remedial learning plans or training assistance plans. A comprehensive group decision-making procedure should be carried out in CCC to improve the quality of clinical staff training, teaching, and medical services as well as the professional identity of clinical staff.</p> <p> </p>

Relevance-Theoretic Comprehension procedures in the analysis of Donald Trump''''s interview on HBO.

Relevance-Theoretic Comprehension procedures in the analysis of Donald Trump''''s interview on HBO.

A Systematic Study of Application of Cognitive Intelligence in Mphasis – a Case Study

Introduction: The modern definition of intelligence is machines’ capacity to comprehend and adapt to surroundings employing innate skills and acquired knowledge. We have arguably reached a brand-new stage in the development of civilization. In recent years, the advancement of cognitive technology has accelerated rapidly. On many levels, their capabilities—both current and future—are very appealing. Their application in business is intended to save operating expenses while accelerating the rate of business development and improving the quality of services provided. Cognitive systems use logical human processes to interpret data in order to enable computers and robots to precisely mimic human actions, both in terms of repetitive, routine tasks and comprehensive procedures of completing a variety of tasks. Additionally, they carry out diagnostic and predicative tasks. They are used in the most recent technologies because they offer conclusions, shed light on processes, and offer automated actions based on data analysis and contextual human interactions. Since much of the labour done by employees is routine in nature, computers and algorithms may simply take over these activities. Information technology services and integrated solutions are offered by the Mphasis. It covers application services, infrastructure technology, and business process outsourcing. It adopts a customer-in view to transform organisations by utilising the sector-specific X2C2TM framework, which harnesses the power of cloud and cognitive to give hyper-personalized digital experiences to its customers. Background/Purpose: Mphasis is in the industry of: Business Services, Custom Software & IT Services, Management Consulting - leading applied technology services, helping enterprises transform businesses globally by applying next-generation technology. Design/Methodology/Approach: Referred websites and articles related to Mphasis development, services, cognitive applications. Findings: With regard to sales, delivery, and development, Mphasis innovates to produce excellent customer service and successful results. In order to maintain its clients at the top of the heap in a market that is constantly changing, its goal is to be flexible, nimble, and customer-centric. There have been companies with significant AI-related infrastructure in India. IISc has organizations with driving organizations like Robert Bosch, Faurecia; IIIT Bangalore is in association with Mphasis and focus Cognitive Computing; IIT Kharagpur has made AI inquire about focus with Capillary Technologies. Originality: This paper tries to give an overview of how Mphasis focuses on cognitive intelligence applications and anticipates 0the future of applied technology and forecasts tomorrow's trends. Paper Type: A Research Case study paper on the use of cognitive intelligence in Mphasis

Fiber morphology design of cellulose composites through multiscale simulation

The effects of fiber orientation control on cellulose composites, which are expected to improve mechanical properties, were systematically investigated, and a comprehensive fiber morphology design procedure was developed. A multiscale finite element simulation based on homogenization theory was employed to investigate the nonlinear properties of cellulose composites and quantitatively assess the effect of fibers on mechanical properties, with a particular emphasis on the distribution of strain energy. As the main factors in fiber morphology, we focused on two particular aspects: fiber orientation, which has a large influence, and aspect ratio, which varies with defibration, in addition to frequently-controlled fiber content ratio. Numerical simulation revealed that the elastic modulus and maximum tensile stress increase linearly with increasing the proposed parameter, fiber contribution proportion (CPf). Fiber orientation and content ratio were identified as the primary factors influencing the change rate in properties with respect to the CPf . Further, the fiber aspect ratio was found to be the secondary factor that influenced the properties according to the change rate determined by the primary parameters. Furthermore, the design procedure, constructed based on the CPf, was evaluated for three cases with different fiber morphology control strategies. The results demonstrated that the proposed fiber morphology design, across all cases evaluated, achieved the target values for both the elastic modulus and maximum tensile stress with errors ranging from 2.0 to 5.4%.

Optimisation of an underwater vehicle rotary docking skirt structure

ABSTRACT This paper presents a comprehensive procedure for the parametric design and analysis of a underwater vehicle rotary docking skirt (RDS) structure. Different types of software were integrated to improve the design efficiency, and different techniques were used to establish an approximate model of the RDS structure with high fitting accuracy. Nondominated sorting genetic algorithm II (NSGA-II) was improved by dynamic adjustment of the population size according to the number of iterations and new crossover and mutation operations (i.e. INSGA-II), which was then applied to a multi-objective optimisation model of the RDS structure. A Pareto solution set was obtained, and a sensitivity analysis was performed on the design variables and objective functions of four representative optimisation schemes. These results can be used to provide a richer selection for designers to reference when designing RDS structures. Abbreviations: RDS; Rotary docking skirt; NSGA-II; Nondominated sorting genetic algorithm II

The Effect of Conceptual Understanding Procedures Learning Model on Students' Higher Level Thinking Skills

Learning activities tend to be teacher-centered with conventional learning methods. In addition, the indicators trained are limited to C4 (analyzing) indicators. This has an impact on students' higher order thinking skills. This study aims to analyze the effect of the conceptual understanding procedures learning model on students' higher order thinking skills. This study uses a quasi-experimental research method with a quantitative research approach. The type of research design used is a non-equivalent control group design. The subjects in this study were students science class in senior high school with a study population of 205 students. The sampling technique used is cluster random sampling. The data collection technique used was a description test of 7 questions then measured using the t test. The results showed that the Conceptual Comprehension Procedure learning model had a significant effect on students' higher order thinking skills. This research has implications for the student learning process so that it can become an evaluation lesson for teachers to improve the quality of learning, especially with regard to training students' higher order thinking skills.

Facial Feminization Surgery: Preoperative Planning and Surgical Technique for a Harmonious Outcome.

Feminization of the face is as important as genital or chest surgeries in alleviating gender incongruence in transgender individuals. It comprises a myriad of procedures that address the skeletal and/or soft tissue components to give a harmonious result. The surgeries are custom-tailored for each individual based on facial anatomy as well as her desired changes for optimal results. A thorough understanding of the differences in male and female facial anatomy is crucial. The use of computed tomographic imaging with three-dimensional reconstruction and stereolithography models can greatly improve the planning as well as execution of these surgeries. There is an increase in demand for these surgeries, with a paucity of centers providing them. The aim of this article is to highlight the comprehensive facial feminization procedures, which have a high patient as well as surgeon satisfaction rate.

Finite Element Analysis of Microwave Tumor Ablation Based on Open-Source Software Components

Microwave ablation is a procedure for treating various types of cancers during which a small needle-like probe is inserted inside the tumor, which delivers microwave energy, causes tissue heating, and effectively produces necrosis of the tumor tissue. Mathematical models of microwave ablation involve the modeling of multiple physical phenomena that occur during the procedure, including electromagnetic wave propagation, heat transfer, and tissue damage. In this study, a complete model of a microwave ablation procedure based on open-source software components is presented. First, the comprehensive procedure of mesh creation for the complete geometric arrangement of the microwave ablation, including a multi-slot coaxial antenna, a real liver tumor taken from the database, and the surrounding liver tissue, is described. It is demonstrated that utilizing smart meshing procedures significantly reduces the usage of computational resources and simulation time. An accurate custom explicit Euler time loop was designed to obtain temperature values and estimate tissue necrosis across the computational domain during the time of microwave ablation. The simulation results obtained by solving the electromagnetic field using the finite element method in the frequency domain are presented and analyzed. The simulation was performed for a microwave frequency of 2.45 GHz, and the volumetric distribution of temperature and estimation of cell damage over 600 s are presented.

Nonsurgical Rhinoplasty: Diamond Injection Technique for Nasal Tip Contouring.

Background: A more pleasing nasal tip appearance is becoming the most frequent reason for nonsurgical aesthetic rhinoplasty procedures. Objective: To present the "Diamond Injection Technique," an innovative 4-point hyaluronic acid (HA) filler injection procedure for nasal tip refinement and to assess its aesthetic outcomes and efficacy. Methods: Data were collected from a prospective single-center cohort of patients undergoing nonsurgical rhinoplasty with injectable fillers. Anthropometric measurements, the 5-point Global Aesthetic Improvement Scale (GAIS), and a patient-reported questionnaire were used to evaluate the aesthetic outcomes and treatment efficacy before treatment and 6 months later. Results: The study included 107 patients; 82 were women. The median age was 35 (18-47) years. The mean volume of HA filler injected was 0.12 mL (range: 0.05-0.2). At 6 months, the GAIS-calculated outcome was excellent in 90.65% of patients, with a high degree of patient satisfaction and objectively pleasant changes in anthropometric measurements. Conclusions: The "Diamond Injection Technique" proves to be a safe, comprehensive, and effective procedure for refining the nasal tip to a pleasing diamond shape, satisfying a high percentage of patients.

Prediction of the Posture-Dependent Tool Tip Dynamics in Robotic Milling Based on Multi-Task Gaussian Process Regressions

Chatter vibration is one of the main factors that limit the productivity and quality of the robotic milling process. To predict the robotic milling stability, it is essential to obtain the tool tip frequency response function (FRF). The tool tip dynamics of a robot heavily depend on its postures and used tools. A state-of-art methodology of combining the regression model with the Receptance Coupling Substructure Analysis (RCSA) method is proved to be effective in predicting tool tip FRFs of machine tools for different positions and tools. However, for the milling robot, the cross coupling FRFs have an obvious influence on the dynamic property of the milling robot, thereby greatly affecting the milling stability boundary. It is of great challenge to directly integrate the effect of the cross coupling FRFs into the state-of-art approach to predict the tool tip dynamics. To tackle this challenge, in this paper, we propose an approach to predict the posture-dependent tool tip dynamics for different tools in robotic milling considering the cross coupling FRFs. First, a more comprehensive RCSA procedure is adopted to include the cross coupling FRFs. Then, the impact test is designed to measure the required FRF matrix. By fitting the measured FRF matrix with the multiple-degree-of-freedom (MDOF) model, the number of modal parameters is significantly reduced. Next, the Multi-Task Gaussian Process (MTGP) regression model is employed to mine the physical correlations between different modal parameters. Compared to the ordinary Gaussian Process regression model, the number of required regression models in MTGP is reduced and the prediction performance is improved in terms of accuracy and robustness. Furthermore, the effectiveness of the proposed approach is validated by the impact test and milling experiment on an industrial robot.

CorrFL: Correlation-Based Neural Network Architecture for Unavailability Concerns in a Heterogeneous IoT Environment

The Federated Learning (FL) paradigm faces several challenges that limit its application in real-world environments. These challenges include the local models’ architecture heterogeneity and the unavailability of distributed Internet of Things (IoT) nodes due to connectivity problems. These factors posit the question of “how can the available models fill the training gap of the unavailable models?". This question is referred to as the “Oblique Federated Learning" problem. This problem is encountered in the studied environment that includes distributed IoT nodes responsible for predicting CO2 concentrations. This paper proposes the Correlation-based FL (CorrFL) approach influenced by the representational learning field to address this problem. CorrFL projects the various model weights to a common latent space to address the model heterogeneity. Its loss function minimizes the reconstruction loss when models are absent and maximizes the correlation between the generated models. The latter factor is critical because of the intersection of the feature spaces of the IoT devices. CorrFL is evaluated on a realistic use case, involving the unavailability of one IoT device and heightened activity levels that reflect occupancy. The generated CorrFL models for the unavailable IoT device from the available ones trained on the new environment are compared against models trained on different use cases, referred to as the benchmark model. The evaluation criteria combine the mean absolute error (MAE) of predictions and the impact of the amount of exchanged data on the prediction performance improvement. Through a comprehensive experimental procedure, the CorrFL model outperformed the benchmark model in every criterion.

Reinforcement Learning Based Sliding Mode Control for a Hybrid-STATCOM

The hybrid static synchronous compensator (hybrid-STATCOM) is characterized with a wide compensation range and low dc-link voltage, which is a cost-effective reactive power compensator for medium voltage level application. However, the coupling part of the hybrid-STATCOM is time-varying, and its system model is nonlinear, which causes a great challenge for the controller design. This paper proposes a model-free reinforcement learning (RL) based sliding mode control (RL-SMC), which provides the inverter voltage as the control action of the hybrid-STATCOM to compensate the load reactive power and harmonic. The proposed RL-SMC is computationally efficient with high steady-state accuracy, fast response, and good robustness. First, an agent-environment framework (AEF) is proposed to enable RL. Then, the comprehensive design procedure of the RL-SMC is proposed. Finally, simulation and experimental results are carried out to verify the validity and effectiveness of the proposed RL-SMC under different load and grid conditions.

MTTfireCAL Package for R—An Innovative, Comprehensive, and Fast Procedure to Calibrate the MTT Fire Spread Modelling System

Fire spread behavior models are used to estimate fire behavior metrics, fire hazard, exposure, and risk across the landscape. One of the most widely used fire spread models is the minimum travel time (MTT), which requires a very time-consuming, interactive, trial-and-error calibration process to reproduce observed fire regimens. This study presents the MTTfireCAL package for R, a tool that enables fast calibration of the MTT fire spread models by testing and combining multiple settings and then ranking them based on the model’s capacity to reproduce historical fire patterns, such as fire size distribution and fire frequency. Here, we explain the main methodological steps and validate the package by comparing it against the typical calibration procedures in two study areas. In addition, we estimate the minimum number of fire runs required to ensure a reliable calibration. Overall, the use of MTTfireCAL R package and the optimization of the number of ignitions used allowed for a faster calibration of the MTT modeling system than the typical trial-and-error calibration. The MTT modeling system calibrated using MTTfireCAL was also able to better reproduce the historical fire patterns. This tool has the potential to support the academic and operational community working with MTT.

Influence of Internal Control Systems on Governance among Parastatals in Taiwan

The study sought to examine the influence of internal control systems on governance among parastatals in Taiwan. The research used the descriptive research design. The target population were 15 parastatals in Songshan District, Taiwan. The study picked 20 respondents from each of the parastatals yielding to sample size of 300. Questionnaires were used to collect data and reliability and validity of the research instruments were conducted. SPSS was used to do the analysis of the data. The findings of the study indicated that internal control systems have a positive effect on governance among parastatals in Taiwan. Internal control systems also contribute to the efficient and effective use of resources in parastatals. By implementing controls for financial management, budgeting, and resource allocation, these systems promote prudent and responsible use of resources. Effective resource utilization allows parastatals to optimize their performance, deliver public services more efficiently, and achieve their objectives effectively. Furthermore, internal control systems enhance risk management within parastatals. To enhance the influence of internal control systems on governance among parastatals in Taiwan, several recommendations can be made. Firstly, it is crucial to establish comprehensive internal control policies and procedures tailored specifically to the needs of parastatals, outlining control objectives and responsibilities. Secondly, regular training programs should be implemented to enhance the knowledge and skills of employees involved in governance and internal controls. Continuous monitoring and evaluation of internal control systems are important, along with reporting and addressing control deficiencies. Collaboration and information sharing among parastatals can promote best practices, while fostering a culture of ethics and integrity through a code of conduct is essential. These recommendations aim to strengthen governance practices, ensure consistency, and promote transparency and accountability within parastatals. Keywords: Internal Control Systems, Governance, Parastatals, Taiwan

Identification of a TuMV isolate (TuMV-ZR) from Pseudostellaria heterophylla and its development into a viral expression vector

Pseudostellaria heterophylla (P. heterophylla) is a popular Chinese medicinal herb that is cultivated widely in China. Viral infection is commonly encountered during the production of P. heterophylla. To identify viruses causing P. heterophylla disease, sRNA and mRNA libraries were built for 2 sets of P. heterophylla plants, one set that was planted only once (FGP) and one that was planted three consecutive three times (TGP) in a field, using virus-free tuberous roots as reproductive materials. A comprehensive procedure, including assembling virus-derived sRNA (vsRNA), assessing and cloning the full-length viral genome, building an infectious cloning vector and constructing a virus-based expression vector, was performed to identify viruses infecting P. heterophylla. Ultimately, 48 contig-related viruses were mined from 6 sRNA and 6 mRNA P. heterophylla libraries. A 9762-bp fragment was predicted to be the complete genome of TuMV virus. This sequence was cloned from P. heterophylla, and its infectivity was evaluated using the virus-infection model plant Nicotiana benthamiana (N. benthamiana) and host plant P. heterophylla. The resulting 9839-bp viral genome was successfully obtained from P. heterophylla and identified as a new P. heterophylla TuMV-ZR isolate. Simultaneously, TuMV-ZR infectious clones were shown to effectively infect P. heterophylla. Furthermore, TuMV-ZR expression vectors were developed, and the ability of a TuMV-ZR-based vector to express foreign genes was determined by analysis with the reporter gene EGFP. TuMV-ZR-based vectors were found to continuously express foreign genes in different organs of P. heterophylla throughout the whole vegetative period. In addition, TuMV-ZR vectors carrying EGFP accumulated in the tuberous roots of P. heterophylla, confirming that tuberous roots are key targets for viral infection and transmission. This study revealed the core pathogenicity of P. heterophylla mosaic virus and developed a new TuMV-ZR-based expression tool that led to long-term protein expression in P. heterophylla, laying the foundation for the identification of the mechanisms of P. heterophylla infection with mosaic viruses and developing tools to express value proteins in the tuberous roots of the medicinal plant P. heterophylla.

A system for the validation of collision avoidance algorithm performance of autonomous ships

Adequate validations on intelligent ships are essential to guarantee navigation safety and efficiency. In this paper an emulated validation system is constructed to test collision avoidance ability of autonomous ships in open waters, coastal regions and archipelago areas with different traffic densities. A synthetic map generator is designed, the map meshing conbines the techniques from Voronoi Tessellation, Poisson-disk Sampling and Perlin Noise to build up more natural coastlines and detailed elevation data. To imitate random encounter scenarios, a new method is designed to maintain target ship quantity, to conduct various tests, 3 types of water geography, different ship behaviors as well as manual and automatic control modes are applied, during testing, each ship is designed to follow the planned routes which are generated arbitrarily and then smoothed. A validation scheme is put forward for comprehensive testing procedures. Finally, A set of experiments on the collision avoidance algorithm show the merits and drawbacks, this verifies the effectiveness of the validation system.

Consensus on an assessment protocol for children with speech sound disorders in Sri Lanka.

Speech sound disorders (SSDs) are the most common form of communication disorders in children. SSD have an impact on children's abilities to make themselves understood to their listeners and can influence a child's social and emotional well-being as well as their academic achievements. Therefore, it is important to identify children with an SSD early, in order to provide appropriate intervention. A wealth of information on best practice in the assessment of children with SSD is available in countries where the speech and language therapy profession is well established. In Sri Lanka, there is a paucity of research evidence supporting assessment practices that are culturally and linguistically appropriate in SSDs. Therefore, clinicians rely on informal assessment methods. There is a need to understand more about how clinicians in Sri Lanka assess this caseload in order to get general agreement regarding comprehensive and consistent procedures for assessment of paediatric SSD in Sri Lanka. This would support speech and language therapists' (SLTs') clinical decision-making in relation to choice of appropriate goals and intervention for this caseload. To develop and gain consensus on an assessment protocol for Sri Lankan children with SSD that is culturally appropriate and based on existing research. A modified Delphi method was utilised to gather data from clinicians currently working in Sri Lanka. The research involved three rounds of data collection, exploring current assessment practices in Sri Lanka, ranking these in order of priority and establishing consensus on a proposed assessment protocol. The proposed assessment protocol was based on the results of the first and second rounds as well as previously published best practice guidelines. The proposed assessment protocol achieved consensus in relation to content, format and cultural appropriateness. SLTs affirmed the usefulness of the protocol within the Sri Lankan context. Further research is required to assess the feasibility and effectiveness of this protocol in practice. The assessment protocol supports practicing SLTs with a general guide to assessing children with suspected SSDs in Sri Lanka. The application of this protocol built upon consensus enables clinicians to improve their individual practice patterns based on best practice recommendations in the literature and the evidence on culturally and linguistically appropriate practices. This study has identified the need for further research in this area, including the development of culturally and linguistically specific assessment tools that would complement the use of this protocol. What is already known on the subject The assessment of children with speech sound disorders (SSDs) requires a comprehensive and holistic approach due to their heterogeneous nature. Although there is evidence to support the assessment of paediatric SSDs in many countries where the profession of speech and language therapy is established, there is limited evidence to support the assessment of children with SSDs in Sri Lanka. What this study adds This study provides information about current assessment practices in Sri Lanka and consensus on a proposed culturally appropriate protocol for the assessment of children with SSDs in this country. What are the clinical implications of this work? The proposed assessment protocol provides speech and language therapists in Sri Lanka with a guide for assessment of paediatric SSDs to support more consistent practice in this area. Future evaluation of this preliminary protocol is required; however, the methodology used in this research could be applied to the development of assessment protocols for other range of practice areas in this country.

Dried blood spots for doping controls-Development of a comprehensive initial testing procedure with fully automated sample preparation.

Currently, primarily urine, whole blood and serum samples are analyzed for doping-relevant substances in professional sports, but recently dried blood spots (DBS) have been introduced as complementary matrix, offering advantageous features, e.g. a minimally invasive sampling procedure. In order to cope with the increased application of DBS, a comprehensive initial testing procedure (ITP) was developed, optimized and validated, comprising a total of 233 substances representing all groups on the World Anti-Doping Agency's (WADA's) Prohibited List. The sample preparation was conducted by employing a fully automated system using an efficient flow-through extraction of a 4mm diameter spot followed by LC-HRMS/MS analysis. The procedure was successfully validated in terms of selectivity, limit of detection, reproducibility, carryover and robustness with respect to an alternative manual sample preparation, an alternative dried blood collection device and the sample extract stability, and was thus found to meet the required criteria of the relevant guidelines published by WADA for routine application. As a proof-of-concept, DBS samples were analyzed after the administration of the glucocorticoids prednisone and dexamethasone, as well as the stimulant pseudoephedrine and the beta-blocker propranolol. All substances were detected in post-administration samples for at least 4h and up to 24 h after intake, depending on the collection time period, using the developed testing procedure. In particular, for substances that are only banned in-competition, data obtained from DBS samples can be useful for the interpretation of adverse analytical findings. In conclusion, the developed ITP accounts for the anticipated increasing relevance of DBS in anti-doping analysis in the future and provides a foundation for optimized approaches for specific substance classes.

Total Quality Management Strategies and their Impact on Digital Transformation Processes in Educational Institutions. An Exploratory, Analytical Study of a Sample of Teachers in Iraqi Universities

One of the administrative concepts that has gained widespread traction across all industries, particularly the education sector, is total quality management techniques.Numerous industries have been successful in putting (quality management) into practice and benefiting from its tenets, allowing them to stand out in their applicability, It is one of the driving forces behind enterprises' shift to a knowledge-based economy, and to stay competitive, organizations must disseminate digital culture and focus on organizational transformation, The goal of the research is to present contemporary concepts that are not too far away, but it was not something that could be changed easily because it is an expression of life and one of the fundamental and widely recognized principles.Therefore, the research started from a problem represented by the lack of interest of the research sample in (total quality management) practices in the context of the digital transformation process, the practice of total quality management, how to lead the digital transformation processes, and knowing the relationship between them, conveyed in several different questions? Do our educational institutions have the plans and initiatives necessary to put comprehensive quality procedures into practice? Has TQM created a framework that explains the digital transformation process? The research was based on a sample of (170) respondents, all of whom were subjected to analysis and included a number of members of the bodies. It was conducted at a number of Iraqi universities, including Karbala, Babylon, AL-Furat Al-AwsatTechnical, andAl-Qadisiyah.Using the statistical program (SPSS, V.23), teaching from experts in quality assurance, university performance, and follow-up committees for e-learning, as well as the current study, a set of results have been reached, the most significant of these is that Total Quality Management is an organizational strategy that helped to start the road of digital transformation and is one of the essential elements that it uses to help firms develop their digital capabilities.The research's key conclusionis that the educational environment is experiencing an extreme state of flow.Digital transformation procedures should be used because they are no longer a choice but rather a management system and a perfect proactive action that can be implemented in thepostmodern era and begin to bear fruit.

Disentangling language-related item biases in stress research with people of Turkish origin in Germany: An application of the CCT procedure.

Psychological stress experiences play a major role in the development of ethnic health disparities. Investigating such relationships often requires the use of questionnaires in different languages, however, this involves the risk of biased measurements. Such biases may be even more likely to occur the closer the construct being measured is to cultural experiences. We adapted the culture, comprehension, and translation bias (CCT) procedure (Bader et al., 2021) to test three language-related item biases in the measurement of stress experience among people of Turkish origin in Germany (i.e., language choice, comprehension, and translation bias) in the Perceived Stress Scale (PSS) and the Multidimensional Acculturative Stress Inventory (MASI). One thousand three hundred four adult persons of Turkish origin living in Germany participated in an online survey with a quasi-experimental design: participants either chose the German version, were assigned the German version, or were assigned the Turkish version of the study questionnaire. Participants completed the 10-item PSS, 25-item MASI, and other measures, and provided sociodemographic data. The adapted CCT procedure revealed none of the language-related biases for the PSS, whereas for the MASI a language choice bias could be demonstrated for one item, a comprehension bias for one item, and a translation bias for five items. The results suggest that language-related item biases are trait-specific and that the CCT procedure is suitable for testing other item biases beyond those tested by Bader et al. Testing such item biases may improve the study of stress experiences in the context of ethnic health disparities. (PsycInfo Database Record (c) 2023 APA, all rights reserved).