Validation Data Research Articles

Data Validation Utilizing Expert Knowledge and Shape Constraints

Data validation is a primary concern in any data-driven application, as undetected data errors may negatively affect machine learning models and lead to suboptimal decisions. Data quality issues are usually detected manually by experts, which becomes infeasible and uneconomical for large volumes of data. To enable automated data validation, we propose “shape constraint-based data validation”, a novel approach based on machine learning that incorporates expert knowledge in the form of shape constraints. Shape constraints can be used to describe expected (multivariate and nonlinear) patterns in valid data, and enable the detection of invalid data which deviates from these expected patterns. Our approach can be divided into two steps: (1) shape-constrained prediction models are trained on data, and (2) their training error is analyzed to identify invalid data. The training error can be used as an indicator for invalid data because shape-constrained models can fit valid data better than invalid data. We evaluate the approach on a benchmark suite consisting of synthetic datasets, which we have published for benchmarking similar data validation approaches. Additionally, we demonstrate the capabilities of the proposed approach with a real-world dataset consisting of measurements from a friction test bench in an industrial setting. Our approach detects subtle data errors that are difficult to identify even for domain experts.

OPTIMIZATION OF CNN + MOBILENETV3 FOR INSECT IDENTIFICATION: TOWARD HIGH ACCURACY

Developments in the field of artificial intelligence and deep learning, particularly Convolutional Neural Networks (CNN) techniques, have expanded the research potential and applications in ecology, including efficient and accurate insect classification. However, there are challenges in achieving high levels of accuracy with similar computational efficiency. In response, the efficient MobileNetV3 architecture was investigated to improve the insect pest classification process. Through an analytical descriptive quantitative approach and insect datasets from Kaggle, this study tested the effectiveness of CNN models optimized with MobileNetV3. The results indicated that the optimized model achieved classification accuracy of up to 90%, with consistent performance between training and validation data and significant loss reduction. With high precision and processing efficiency, this discovery makes a substantial contribution to deep learning applications in the field of intelligent agriculture, promising methodological improvements for other classification problems. Despite offering a promising solution, this study recognizes the limitation in dataset diversity and suggests further exploration with more varied datasets to strengthen the model's application in actual agricultural practices.

Studying eruption patterns of mandibular third molars for forensic age assessment: Introducing current reference data from a population of black South Africans.

Evaluation of the eruption of mandibular third molars in orthopantomograms (OPGs) is a method of forensic age assessment. The objective of our study was to provide valid reference data for this trait within a population of black South Africans. The study was guided by the criteria for reference studies in age assessment. A study population from Pretoria, South Africa comprising 670 OPGs obtained from 338 black females and 332 black males aged between 15.00 and 25.97 years was analysed. All OPGs were performed for medical indication during the period from 2011 to 2022 and were retrospectively evaluated. From the 670 OPGs, a total of 1021 mandibular third molars were evaluated. The assessment of mandibular third molars was conducted using the staging scale presented by Olze et al. in 2012. Two experienced dentists evaluated the OPGs independently of each other. If the two examiners diverged in their assessments, a consensus stage was assigned. As expected, the mean, median and minimal age increased with higher stages for both teeth and both sexes. The minimum age recorded for stage D, indicating complete tooth eruption, was 15.79 years in females and 16.62 years in males. As it is the case for previous reference studies in other countries, placing exclusive reliance on the evaluation of mandibular third molar eruption is inadequate for ascertaining the age of majority among Black South Africans. Future studies need to examine if our results are transferable to other countries in Sub-Saharan Africa.

Using satellite image data to identify rice varieties through linear spectral unmixing method (case study: Karangjati Sub District, Ngawi Regency)

<p>Remote sensing technology has increasingly emerged as a potent tool for precision agriculture, particularly in facilitating the mapping and monitoring of crops on a large scale. An application of this technology is the identification of different types of rice by analyzing the pixels acquired in satellite images. Regrettably, the pixels in the image have been mixed from different recorded items. Therefore, they have the potential to influence the outcome of the identification. An effective approach to address this problem is to employ the linear spectral unmixing (LSU) technique. The LSU approach quantifies the ratio of pure objects in every pixel of an image by utilizing the spectral value associated with the endmember of the rice variety. The investigation was carried out in the Karangjati District during the generative stage (70 ± DAP) of the rice planting season. The data indicates that the dominant variety is Inpari 32 HDB. The data validation tests, which involved the use of a confusion matrix and Kappa analysis, resulted in an overall accuracy rate of 85.48% and a Kappa analysis score of 70.6%.<strong></strong></p>

Age-related patterns in mandibular third molar eruption: presenting new forensic age assessment reference data from a Chinese population.

Valid reference data are essential for reliable forensic age assessment procedures in the living, a fact that extends to the trait of mandibular third molar eruption in dental panoramic radiographs (PAN). The objective of this study was to acquire valid reference data for a northern Chinese population. The study was guided by the criteria for reference studies in age assessment.To this end, a study population from China comprising 917 panoramic radiographs obtained from 430 females and 487 males aged between 15.00 and 25.99 years was analysed. Of the 917 PANs, a total of 1230 mandibular third molars were evaluated.The PANs, retrospectively evaluated, were performed for medical indication during the period from 2016 to 2021. The assessment of mandibular third molars was conducted using the staging scale presented by Olze et al. in 2012. Two independent examiners, trained in assessing PANs for forensic age estimation, evaluated the images. In instances where the two examiners diverged in their assessments these were subsequently deliberated, and a consensus stage was assigned.The mean age increased with higher stages for both teeth and both sexes. The minimum age recorded for stage D, indicating complete tooth eruption, was 15.6 years in females and 16.1 years in males. Consequently, the completion of mandibular third molar eruption was observed in both sexes well before reaching the age of 18. In light of our results, it is evident that relying solely on the assessment of mandibular third molar eruption may not be sufficient for accurately determining the age of majority. Contrary to previous literature, this finding of a completed eruption of the mandibular third molars in northern Chinese individuals is only suitable for detecting the completion of the 16th year of life in males according to our results. However, as the results are inconsistent compared to other studies in the literature, the trait should not be used as the only decisive marker to prove this age threshold in males from northern China.

Implementation of the Teaching Factory Learning Model to Improve Student Competencies in Entrepreneurship Subjects at SMKN 1 Bagor, Nganjuk Regency

This study aims to determine (1) the implementation of the teaching factory learning program, (2) describe the implementation of the teaching factory learning model in improving students in entrepreneurship subjects. Teaching factory learning aims to train students to become entrepreneurs. Teaching factory is implemented by setting up a business unit or company at school. The method used in this research is descriptive qualitative method. The data collection techniques used are documentation, interviews and questionnaires. Data validity uses credibility test criteria, transferability, dependability, and confirmabilitaty criteria. The data analysis technique used is the Miles and Huberman model, namely data reduction (Data Reduction), data presentation (Data Display), and conclusion drawing / verification. The results of this study can be obtained that: 1) the implementation of teaching factory learning is in accordance with the concepts and elements, equipment and equipment have been fulfilled, the marketing aspect has not been maximized, 2) teaching factory learning to improve student competence in entrepreneurship subjects. The goal is to train and facilitate students to maximize their talents and interests. The principles make students independent by instilling an entrepreneurial mentality, and 3) students have motivation to move forward, creativity, commitment innovation and honesty, The level of tendency of the entrepreneurial spirit of students is included in the high category. the implementation of the teaching factory learning model in improving student competence in entrepreneurship subjects includes 3 components, namely: (1) Product, (2) Block Schedule, (3) Job Sheet. The results of the Implementation of the Teaching Factory Learning Model are: the practical learning process is carried out based on real work procedures (real job), teaching factory learning is done by learning by doing, teaching factory learning activities produce learning that takes place centered on students (student active learning). Keywords: teaching factory learning model, student entrepreneurial competence

MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery.

Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction datasets are urgently needed for large language models. To address this, we present MISATO, a dataset that combines quantum mechanical properties of small molecules and associated molecular dynamics simulations of ~20,000 experimental protein-ligand complexes with extensive validation of experimental data. Starting from the existing experimental structures, semi-empirical quantum mechanics was used to systematically refine these structures. A large collection of molecular dynamics traces of protein-ligand complexes in explicit water is included, accumulating over 170 μs. We give examples of machine learning (ML) baseline models proving an improvement of accuracy by employing our data. An easy entry point for ML experts is provided to enable the next generation of drug discovery artificial intelligence models.

Membangun Kesehatan Mental Generasi Alpha: Urgensi Konseling dalam Mengatasi Tantangan Bullying di Era Sosial Media Melalui Komunikasi Empati

This research aims to determine the urgency of counseling in overcoming the challenges of bullying in the era of social media through empathetic communication. This research is a qualitative-descriptive study with a phenomenological approach to observe and describe natural phenomena that occur in the alpha generation in the social media era. Research data was obtained from bullying cases on social media, as well as from journal articles and other relevant literature. Analysis of this research data involves data reduction, data presentation, and conclusion. The validity of the research data was carried out using triangulation testing. The results of this research show that building the mental health of the Alpha generation through counseling is essential in the modern era filled with technology. Counseling creates a safe space to share experiences and feelings, helping them manage technological stress and social pressure. Addressing bullying in the age of social media requires empathetic communication, approaching the perpetrator with tact, providing positive support, and creating a safe place to talk. This can form a culture that is friendly, and supportive, and teaches the values of diversity and respect for others. Counseling and empathetic communication are not only solutions to psychological problems and bullying, but also a strong foundation for the mental and emotional well-being of the Alpha generation in an ever-changing world.

Optical Properties and Possible Origins of Atmospheric Aerosols over LHAASO in the Eastern Margin of the Tibetan Plateau

The accuracy of cosmic ray observations by the Large High Altitude Air Shower Observatory Wide Field-of-View Cherenkov/Fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples over 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and Ångström Exponent (AE) at 440–870 nm (AE440–870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD is in the order of spring > summer > autumn = winter. The monthly average maximum of AOD440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE440–870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India regions. These results are presented for the first time, providing a detailed analysis of aerosol seasonality and origins, which have not been thoroughly documented before in this region, also enriching the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau.

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.

Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Long-term Satellite-derived Bathymetry of Arctic Supraglacial Lake from ICESat-2 and Sentinel-2

Abstract. The polar ice sheets serve as natural thermostats, regulating Earth’s temperatures. The Greenland Ice Sheet (GrIS), the second-largest ice sheet, is a critical indicator of climate change and global warming. Estimating the volume of supraglacial lakes on the GrIS, which is directly linked to the extent of melting in the Arctic ice sheet, requires information on both lake area and water depth. Conventional bathymetric methods (i.e., airborne bathymetric LiDAR, shipborne echo-sounder) are commonly used for accurate water depth measurement. However, polar supraglacial lakes face challenging conditions, leading to uncertainties in their spatial and temporal distribution. To overcome the limitations, this study combines Sentinel-2 and ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) to estimate bathymetry and detect changes in lake volume on the GrIS from 2019 to 2023. Firstly, Sentinel-2 images were pre-processed, and ICESat-2 single-photon LiDAR points were extracted using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method, followed by the bathymetric corrections as the training data. Subsequently, three bathymetry models (i.e., log-linear, log-ratio, and BP (Back Propagation) neural network) were constructed using Sentinel-2 images and ICESat-2 data. Lastly, the highresolution ArcticDEM (Arctic Digital Elevation Model) was used as the validation data to assess the satellite-derived bathymetry accuracy. In this study, the log-ratio model yielded the best results with the R2, RMSE, and MAE of 0.92, 0.79 m (lower than 10% of the maximum depth), and 0.62 m. The results demonstrate the feasibility of the integrated active and passive remote sensing approach for bathymetry in Arctic supraglacial lakes.

Manajemen Badan Amil Zakat Nasional Sumatera Utara dalam Meningkatkan Kesejahteraan Sosial Mustahik

This study aims to determine the management of the Empowerment of the North Sumatra National Amil Zakat Agency in improving mustahik social welfare. This study uses a descriptive qualitative approach to observe the natural conditions of the North Sumatra National Amil Zakat Agency. The data source of this study refers to mustahik conditions through non-part participant observation and semi-structured interview results. This research data is also sourced from journal articles, and relevant literature. In analyzing research data, researchers refer to the concept of reduction, presentation, and drawing conclusions. Data validity techniques This study refers to triangulation. The results of this study indicate that the North Sumatra Baznas plays a central role in improving mustahik welfare with a focus on zakat. Through the identification of poverty, surveys, and collaboration with local stakeholders, Baznas compiled sharia -based programs such as North Sumatra Care and North Sumatra Makmur. They changed the paradigm of giving zakat from consumptive to productive, involving training skills, financial education, and business capital. With a holistic approach, Baznas ensured that zakat improved mustahik welfare, reflecting productive investment for sustainable social welfare.

Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA

ABSTRACT Cropland fallowing is choosing not to plant a crop during a season when a crop is normally planted. It is an important component of many crop rotations and can improve soil moisture and health. Knowing which fields are fallow is critical to assess crop productivity and crop water productivity, needed for food security assessments. The annual spatial extent of cropland fallows is poorly understood within the United States (U.S.). The U.S. Department of Agriculture Cropland Data Layer does provide cropland fallow areas; however, at a significantly lower confidence than their cropland classes. This study developed a methodology to map cropland fallows within the Northern Great Plains region of the U.S. using an easily implementable decision tree algorithm leveraging training and validation data from wet (2019), normal (2015), and dry (2017) precipitation years to account for climatic variability. The decision trees automated cropland fallow algorithm (ACFA) was coded on a cloud platform utilizing remotely sensed, time-series data from the years 2010–2019 to separate cropland fallows from other land cover/land use classes. Overall accuracies varied between 96%-98%. Producer’s and user’s accuracies of cropland fallow class varied between 70-87%.

Deformation Prediction Model of Existing Tunnel Structures with Equivalent Layered Method–Peck Coupled under Multiple Factors

The existing tunnel structure, the new underpass tunnel structure and the rock strata in the area of influence of the crossover tunnel are interacting systems that are affected by various factors, such as dynamic and static excavation loads and dynamic and static train loads. The existing theoretical models for the deformation prediction of existing tunnels lack the synergistic analysis of dynamic and static loads on both existing and new tunnels. Based on the theory of the current layer method and Peck’s empirical formula, this paper considers the stiffness of existing tunnels, the stiffness of new tunnels, the loads of excavation methods and the loads of existing tunnels. The results show that a theoretical model for the prediction of the deformation of double-lane highway tunnels underneath existing railroad tunnels with the coupling of the current layer method and Peck under multiple factors is constructed; a modified Peck settlement formula for the base plate of the existing tunnels is put forward; and, through numerical calculations and monitoring data for validation and optimization, it is proved that the theoretical model is applicable to the excavation of tunnels underneath mountainous areas mined by the blasting method.

Cross-sectional associations between patterns and composition of upright and stepping events with physical function: insights from The Maastricht Study

IntroductionAge-related declines in physical functioning have significant implications for health in later life. Physical activity (PA) volume is associated with physical function, but the importance of the pattern in which PA is accumulated is unclear. This study investigates associations between accelerometer-determined daily PA patterns, including composition and temporal distribution (burstiness) of upright and stepping events, with physical function.MethodsData was from participants who wore an activPAL3 accelerometer as part of The Maastricht Study. Exposures included a suite of metrics describing the composition and the temporal distribution (burstiness) of upright and sedentary behaviour. Physical function outcomes included the six-minute walk test (6MWT), timed chair-stand test (TCST), grip strength (GS), and SF-36 physical functioning sub-scale (SF-36pf). Multivariable linear regression models were used to assess associations, adjusting for covariates including overall PA volume (daily step count).ResultsParticipants(n = 6085) had 6 or 7 days of valid data. Upright and stepping event metrics were associated with physical function outcomes, even after adjusting PA volume. Higher sedentary burstiness was associated with better function (6MWT, TCST, and SF-36pf), as was duration and step volume of stepping events (6MWT, TCST, GS, and SF-36pf), step-weighted cadence (6MWT, TCST, and SF-36pf). Number of stepping events was associated with poorer function (6MWT, GS, and SF-36pf), as was upright event burstiness (SF-36pf). Associations varied according to sex.ConclusionOur study reveals that diverse patterns of physical activity accumulation exhibit distinct associations with various measures of physical function, irrespective of the overall volume. Subsequent investigations should employ longitudinal and experimental studies to examine how changing patterns of physical activity may affect physical function, and other health outcomes.

The Value of Character Education in Wayang Beber Pacitan Ninth Scene

Wayang beber Pacitan is a type of wayang that has existed since the Majapahit era. This type of wayang is a painting which is divided into 24 scenes. Each scene has a main character and supporting characters. Each character possesses different characteristics. The purpose of this study is to find out and describe the main characters in the ninth scene of wayang beber Pacitan, namely, Prabu Brawijaya and Prabu Klana. This study follows the qualitative descriptive research methodology. Several data collection techniques were used, for example, observation, interviews, and document analysis. Purposive sampling was used as a sampling technique. Interactive analysis methods, with Roland Barthes’s semiotic theory, namely, through denotative, connotative, and mythical stages, were used for data analysis. Moreover, triangulation was used for data validation. The research concludes that the characters in the ninth scene can be divided into two, namely, Prabu Brawijaya, as the protagonist, and Prabu Klana, as the antagonist. Prabu Brawijaya, as the protagonist, has the character of being careful, wise, and alert, while Prabu Klana, as the antagonist, has the character of being easily angry, self-willed, and arrogant. The ninth scene of wayang beber Pacitan teaches us about the value of character education so one should always be careful in acting and wise in making decisions and should not be arrogant and selfish as this will have a negative impact on oneself and others. Apart from being an entertainment medium, wayang beber performances can also be used as a medium to convey moral messages. Through stories and understanding the characters in each scene, it can be used as a medium of character education. Keywords: antagonist, character, protagonist, scene, wayang beber

An Improved Pedotransfer Function for Soil Hydrological Properties in New Zealand

This paper describes a new pedotransfer function (PTF) for the soil water content of New Zealand soils at seven specific tensions (0, −5, −10, −20, −40, −100, −1500 kPa) using explanatory variables derived from the S-map soil mapping system. The model produces unbiased and physically plausible estimates of the response at each tension, as well as unbiased and physically plausible estimates of the response differences that define derived properties (e.g., macroporosity and total available water content). The PTF is a development of an earlier model using approximately double the number of sites compared with the earlier study, a change in fitting methodology to a semi-parametric GAM Beta response, and the inclusion of sample depth. The results show that the new model has resulted in significant improvements for the soil water content estimates and derived quantities using standard goodness-of-fit measures, based on validation data. A comparison with an international PTF using explanatory variables compatible with variables available from S-map (EUPTF2) suggests that the model is better for prediction of soil water content using the limited information available from the S-map system.

The National Cancer Database Conforms to the Standardized Framework for Registry and Data Quality.

Standardization of procedures for data abstraction by cancer registries is fundamental for cancer surveillance, clinical and policy decision-making, hospital benchmarking, and research efforts. The objective of the current study was to evaluate adherence to the four components (completeness, comparability, timeliness, and validity) defined by Bray and Parkin that determine registries' ability to carry out these activities to the hospital-based National Cancer Database (NCDB). Tbis study used data from U.S. Cancer Statistics, the official federal cancer statistics and joint effort between the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), which includes data from National Program of Cancer Registries (NPCR) and Surveillance, Epidemiology, and End Results (SEER) to evaluate NCDB completeness between 2016 and 2020. The study evaluated comparability of case identification and coding procedures. It used Commission on Cancer (CoC) standards from 2022 to assess timeliness and validity. Completeness was demonstrated with a total of 6,828,507 cases identified within the NCDB, representing 73.7% of all cancer cases nationwide. Comparability was followed using standardized and international guidelines on coding and classification procedures. For timeliness, hospital compliance with timely data submission was 92.7%. Validity criteria for re-abstracting, recording, and reliability procedures across hospitals demonstrated 94.2% compliance. Additionally, data validity was shown by a 99.1% compliance with histologic verification standards, a 93.6% assessment of pathologic synoptic reporting, and a 99.1% internal consistency of staff credentials. The NCDB is characterized by a high level of case completeness and comparability with uniform standards for data collection, and by hospitals with high compliance, timely data submission, and high rates of compliance with validity standards for registry and data quality evaluation.

Cross-Cultural Adaptation and Validation of the Romanian Musculoskeletal Tumor Society Scoring System for Patients with Extremity Bone Sarcomas

Background and Objectives: Primary malignant bone tumors are rare lesions, and their complex treatment can lead to functional impairment. It is important to have a postoperative assessment tool for patients’ functional outcomes to be evaluated and to consequently adapt future treatments in the pursuit of a continuous improvement of their quality of life. The Musculoskeletal Tumor Society Score (MSTS) is a validated specific system score that is used frequently in the follow-up of these patients. We found no information about a valid translated Romanian version of this score neither for the upper limb nor for the lower limb. We proposed in this study to translate the original version of the MSTS Score into Romanian and to perform validation analysis of the Romanian-language MSTS Score. Materials and Methods: We selected 48 patients who underwent limb-salvage surgery after resection of bone sarcomas. Patients were interrogated twice according to the translated Romanian version of the MSTS Score during their follow-up. The translation was performed according to the recommended guidelines. A total number of 96 questionnaires were valid for statistical analysis. Results: Internal consistency and reliability were good for both sets of questionnaires’ analytic measurements, with Cronbach’s alpha values of 0.848 (test) and 0.802 (retest). The test-retest evaluation proved to be statistically strong for reproducibility and validity with Spearman’s rho = 0.9 (p < 0.01, 95% CI). Conclusions: This study permitted the translation of this score and the validation of psychometric data. Our results showed that the Romanian version of the MSTS is a reliable means of assessment of the functional outcome of patients who received limb-salvage surgery for the upper and lower extremities.

The Literature Course Mapping in the Undergraduate Curricula of EFL Education: A Case Study in Several Countries in Asia

This study aims to map the literature course in the undergraduate curricula of English as a Foreign Language (EFL) education in Asia, particularly in Indonesia, Thailand, and Taiwan[1], and analyze the literature course mapping in the Indonesian, Thai, and Taiwanese undergraduate curricula of EFL education. The significance of the study lies in its contribution to the structure of the undergraduate curriculum of EFL education, addressing global higher education challenges in the twenty-first century. This research employed a case study approach in Asia involving quantitative mapping of curricula documents from several universities in Indonesia, Thailand, and Taiwan, followed by qualitative analysis of curricula documents. The results indicate that, on average, the twelve target universities allocate 6% of the total obligatory completed semester credits to the literature course for a Bachelor of Teaching degree. Most of these universities position the literature course at a moderately low level with their curricula. Ideally, the literature course allocation could be increased to 15% if the linguistics and general language skills course group is also set at 15%, while the elective course group should be at 6%. Since the data were validated using time triangulation, future research should explore additional data validation techniques, such as in-depth interviews or questionnaires. [1] Taiwan is a part of China.