Validation Of Results Research Articles

Solid Minerals as Alternate means of Nigeria’s Economy Recovery Using Artificial Intelligence

Nigeria is one of the nations blessed with vast number of mineral resources which can make its economy one of best in the world. However, very little attention is directed to this sector as the sector contributes less than 10% to the country's Gross Domestic Product (GDP). Therefore, this study evaluates the economic potentials of Nigeria mineral resources as means of liberating the country from its current economic woes. Data obtained from the existing company, internet sources, U.S. Geological Survey, Nigeria Geological Survey Agency among others were used to form the bases for the analyses. The economic indicators were first computed to determine the dependency of Nigeria mineral demands on the import and forecasting was also done using the moving average method and forecast command. The obtained import reliance and self-sufficiency indicated that Nigeria still depend largely on the importation to meet its mineral requirements and hence not self- sufficient. The Net Profit Value (NBP), Internal Rate of Return (IRR) and Payback Period (PBP) revealed that the minerals investigated are economically viable. To enhance the easy assessment of the NPV, artificial intelligence approach, Artificial Neural Network (ANN) was used to develop models for barite and iron ore. The model was validated, and the validation results are compared with the actual values. They were found to be very close to the actual NPV and can be used for the NPV predictions. Therefore, ANN model was transformed through the weights and biases to mathematical form. Hence, the study has revealed the dependency of Nigeria on import and the economic viability of the minerals in Nigeria.

Digital Teaching Materials of Logical Thinking - Oriented Exposition Text for X Graders of SMA/MA/SMK

This research aims to develop a logical thinking-oriented exposition digital teaching material product that is feasible and effective for Indonesian Language learning in grade X students of SMA/MA/SMK. This research uses a research and development method (Research and Development) with the ADDIE (Analysis Design Development Implementation Evaluation) model. Data collection in the study was carried out and analyzed descriptively, both quantitative and qualitative. The result of the design and development of this digital teaching material is a digital module in the form of pdf and a Flipbook consisting of a cover, concept map, learning objectives, until author biodata. It also contains materials in videos to practice listening, reading and writing that can be accessed in youtube by scanning the link. The results of product validation by language, material and media validators and practitioners stated that the digital teaching materials of logical thinking-oriented exposition texts for SMA/MA/SMK with a result of 80.79% mean "Feasible" to use. The results of the implementation of digital teaching materials for logical thinking-oriented exposition texts for 63 grade X students at SMAN 1 Gantar, SMAN 1 Gantar and MA Ma'had al-Zaytun, showed that there was a significant development between student learning outcomes before and after the use of digital teaching materials after being assessed using the T-Test (Paired sample Test), meaning "effective" for learning exposition text materials. Thus, digital teaching materials for logical thinking-oriented exposition texts for teachers and students of class X SMA/MA/SMK are feasible and effective in learning.

A “Region-Specific Model Adaptation (RSMA)”-Based Training Data Method for Large-Scale Land Cover Mapping

An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data for timely and accurate land cover classifications in Alaska over longer time periods (e.g., greater than 10 years). Specifically, we designed the “Region-Specific Model Adaptation (RSMA)” method for training data. The method integrates land cover information from the National Land Cover Database (NLCD), LANDFIRE’s Existing Vegetation Type (EVT), and the National Wetlands Inventory (NWI) and machine learning techniques to generate robust training samples based on the Anderson Level II classification legend. The assumption of the method is that spectral signatures vary across regions because of diverse land surface compositions; however, despite these variations, there are consistent, collective land cover characteristics that span the entire region. Building upon this assumption, this research utilized the classification power of deep learning algorithms and the generalization ability of RSMA to construct a model for the RSMA method. Additionally, we interpreted existing vegetation plot information for land cover labels as validation data to reduce inconsistency in the human interpretation. Our validation results indicate that the RSMA method improved the quality of the training data derived solely from the NLCD by approximately 30% for the overall accuracy. The validation assessment also demonstrates that the RSMA method can generate reliable training data on large scales in regions that lack sufficient reliable data.

Pengembangan Model Sistem Penjaminan Mutu Internal di Pondok Pesantren

The community has the right and responsibility for the existence of quality educational institutions. similar to the regulations contained in Law Number 18 of 2019 concerning Islamic boarding schools that the implementation of an internal quality assurance system absolutely must be carried out well. However, based on the results of research conducted in several Islamic boarding schools in Bogor, we do not fully understand the stages of quality assurance. Several existing Islamic boarding schools have a quality assurance team but they are not the oldest in the organizational structure. This means that the human resources appointed as the quality assurance team include but are not legally formalized in a decision letter, this means that the Islamic boarding school implements quality assurance components but is not implemented administratively. This research aims to first, analyze the need for developing an internal quality assurance system model in Islamic boarding schools. Second, to develop an internal quality assurance system model in Islamic boarding schools. Third, to test the feasibility of the internal quality assurance system model in Islamic boarding schools. The research uses the Research and Development method, using the ADDIE model. The results of the research findings showed that the analysis of the need for developing an internal quality assurance system in Islamic boarding schools was carried out in the first two stages of the field needs analysis consisting of 9 Islamic boarding schools with 11 respondents. The conclusion was that 100% of respondents needed an internal quality assurance system model for Islamic boarding schools to guarantee the quality of education. boarding school. Second, document analysis consisting of internal quality assurance system documents issued by the Ministry of Education and Culture's primary and secondary education, as well as internal quality assurance system regulations issued by law number 18 of 2019 concerning Islamic boarding schools, became a reference in preparing a model for the internal quality assurance system in Islamic boarding schools. . The Islamic boarding school internal quality assurance system model produces a product in the form of the SPMI model in Islamic boarding schools which explains the internal quality assurance cycle including planning the quality of Islamic boarding school education, preparing plans to improve the quality of Islamic boarding schools, implementing plans to improve the quality of Islamic boarding schools, monitoring and evaluating the implementation of plans to improve the quality of Islamic boarding schools, setting standards. new quality and developing strategies to improve the quality of Islamic boarding schools. Third, a one to one test was carried out with educational management experts, linguists and experts in the field of Islamic boarding school with validation test results by experts in educational management of 81% "decent", language experts of 88% "very worthy", experts in the field of Islamic boarding school of 76%. "worthy". Then revisions were made based on the experts' assessments and suggestions to produce a second prototype. The next stage is implementation in the form of implementation, carrying out a feasibility test on practitioners with an average validation result of practitioners of 90% "very feasible", then producing a third prototype. Next, it goes to the final stage, namely evaluating the third prototype by carrying out revisions based on previous expert assessments so that a product is produced. end. As for the evaluation stage, which is the final stage, you get the assessment results with an assessment result in the range of 80-100 "very good"..

Pengembangan E-Modul Fisika Berbasis PBL Untuk Meningkatkan Keterampilan Kolaborasi Peserta Didik

The study aims to: 1) develop of PBL-based e-module to improve students collaboration skills, 2) the feasibility of PBL-based e-module to enhance students collaboration skills, and 3) the effectiveness of the PBL-based e-module to enhance students collaboration skills. The research method used Research and Development (R&D) with ADDIE model by Dick and Carry (1996). Research procedures were carried out in four initial stages: analysis, design, development and implementation. The conclusions are: 1) an e-module based PBL characteristics has been successfully developed, 2) based on validation results, e-module meets the criteria to be utilized in learning activities, and 3) this e-module received N-Gain score 0,6053, indicating it is effective for enhancing students collaboration skills. Key words: e-module, PBL, collaboration skills

Aplikasi E-Modul Suhu dan Kalor sebagai Rancangan Bahan Ajar Fisika di SMA

Physics learning in SMA Negeri 1 Lumajang often uses textbooks rather than learning modules as learning resources, so it is necessary to develop physics e-modules. This study aims to determine the development design and the validity of physics e-modules of temperature and heat material in senior high school. The research method used is descriptive which describe phenomena or characteristics of the population under the study. The research instrument is a validation questionnaire, interview guidelines, and documentation. The data obtained were the results of validation conducted by 3 expert validators and 2 user validators. The results showed that the average value of the five validators covering four aspect of eligibility namely content, construct, language, the content feasibility aspect gets a score of 83%, the construct feasibility aspect gets a score of 83%, the language feasibility aspect gets a score of 90%, the display feasibility aspect gets a score of 86%. The overall average validation aspects of the five validators get a value of 85,8% with very valid criteria. Based on the research results obtained, it can be concluded that the physics e-module of temperature and heat material gets validity results with very valid criteria and can be tested for development to students at the research school.

A-316 A quantitative gas chromatography tandem mass spectrometry method for metabolic profiling of urine organic acids and acylglycines

Abstract Background The analysis of urine organic acids (UOA) and acylglycines (UAG) are an essential investigation for the diagnosis inborn errors of metabolism (IEMs). The vast majority of methods for these analytes use gas chromatography mass spectrometry (GC-MS) and are only qualitative. Gas chromatography tandem mass spectrometry (GC-MS/MS) offers greater sensitivity and selectivity and enables the combination of qualitative screening with quantitative analysis. We describe the development and validation results of a quantitative GC-MS/MS method. Methods Urine creatinine concentrations were measured (CobasPro, Roche Diagnostics) and normalized to 1.25 mmol/L. After internal standard addition, each urine specimen, calibration standard and QC were incubated with a hydroxylamine solution followed by a liquid-liquid extraction. Further sample concentration permitted the isolated UOA and UAG to be derivatized using N,O-bis(trimethylsilyl)trifluoroacetamine (BSTFA) with 1% chlorotrimethylsilane (TMCS) prior to injection. GC-MS/MS analysis was performed using a GC-MS-TQ8050 triple quadrupole system (Shimadzu) with a 30 m DB-5MS (Agilent J&W) capillary column (0.25 mm, ID of 0.25 µm). Split injection mode was deployed with an initial column temperature of 70°C. The mass spectrometer was operated in electron ionization (EI) and multiple reaction monitoring (MRM) modes. Results The optimal temperature gradient for high-resolution UOA and UAG separations was derived and their respective retention times determined. MS/MS detection parameters were optimized to permit the identification of precursor and production ions for all (N=36) derivatized analytes. Total analysis time was 33.8 min per injection. This method permits the measurement of 11 samples in one batch and is highly linear for all analytes (R^2 >0.99 and average slope 1.04). The limit of quantification (LOQ) was established and ranged from <0.05 to 2.1 µmol/mmol creatinine. Intra- and inter-day imprecision (CV%) was determined using matrix-matched abnormal and normal QC. Intra-day imprecision (N=10) ranged from 1.3% (2-ketoglutaric acid) to 9.7% (3-hydroxybutyric acid). Inter-day imprecision (N=30 over 15 days) ranged from 2.2% (ethylmalonic acid and methylmalonic acid) to 20.5% (3-hydroxy-3-methylglutaric acid). The method had an average accuracy of 113±14% for analytes included in the ERNDiM quantitative organic acids (urine) external quality assurance program. For analytes not included in this proficiency testing, the method showed good agreement when compared to a national reference laboratory, with average Deming correlation coefficients and regression slopes being 0.9944 and 1.1, respectively. No interferences were detected when monitoring the analyte quantifier and qualifier ion ratios in patient urine. Conclusions The devised GC-MS/MS protocol permits the unbiased identification and quantification of UOA and UAG used to investigate IEMs. The method has acceptable sensitivity, specificity, precision and accuracy for clinical routine clinical testing.

B-018 Design and Development of MASTM Diabetes Max Controls, Ready-to-Use Plastic Tube Format

Abstract Background The Thermo Scientific™ MAS™ Controls are assayed controls to monitor assay performance within clinical laboratory settings. The user can compare observed results of controls with their expected ranges as a means of assuring consistent performance of both reagent and instrument. The objective of developing MAS™ Ready-to-Use Tube Controls is to provide MAS™ controls in a new automation-friendly plastic tube format, as an alternative to the current glass vials. Diabetes Max Control is the first MAS™ product designed and developed in this ready-to-use format to be placed directly on the analyzer. The new format will increase efficiency and allow for on-board refrigerated storage, and it is expected to reduce material loss and contamination. It contains Hemoglobin A1c formulated in whole blood matrix to mimic patient specimens. In this presentation we summarize the Feasibility, Development, Verification, and Validation results of MAS™ Diabetes Max Controls. Methods The performance was assessed by conducting the following studies for MAS™ Diabetes Max Tube Controls. The analyte Hemoglobin A1c was measured in functional studies to evaluate and verify the product performance. Other studies were also designed and performed to assess the product usability. Results MAS™ Diabetes Max Control results demonstrated comparable performance and Fit/Form/Function criterion on specified platforms, particularly the TOSOH™ platform. All feasibility studies provided very promising results passing per protocol criterion. Design Verification and Validation studies ensured product integrity and passed specifications for proposed claims. Process Validation is in progress with data being collected for both Value Assignments and Real Time Stability. Conclusions MAS™ Diabetes Max Controls provided in ready-to-use tubes met the design specification criteria. We believe that MAS™ Diabetes Max Controls will contribute to the increased efficiency of core lab workflow by allowing the analyzer(s) to aspirate controls directly from the tube and allow for control storage in an on-board refrigeration unit.

A-317 Development of a patient-focused volumetric absorptive microsampling strategy to assess urinary amino acid excretion

Abstract Background Biochemical determinations of urinary amino acid excretion patterns can diagnose specific inborn errors of metabolism (IEM). Clinical management of these genetic metabolic patients may require frequent urine amino acid tests. A simplified process for transporting home collected urine specimens would benefit the IEM community. Volumetric absorptive microsampling (VAMS) is an emergent alternative sampling technique for the collection of dried biological specimens. We describe the development and preliminary validation results of a VAMS strategy for the analysis of creatinine and amino acids (N=22) from microsampled dried urine. Methods Urine creatinine and amino acids were respectively measured in a clinical laboratory setting using established assays on a CobasPro (Roche) and a MassTrak ultra-performance liquid chromatography (UPLC) amino acid analysis (AAA) solution (Waters). Two 30 µL VAMS tips from a Mitra device (Neoteryx) were used to sample each random urine specimen. An ultrasonication-based solvent extraction procedure was optimized to extract the amino acids and creatinine from the VAMS tips. Solvent extracts were subsequently dried by centrifugal evaporation. Extract from one tip was re-dissolved in water and tested for creatinine using an enzymatic method. The other extract was re-dissolved in 0.02 N sodium hydroxide and tested according to the MassTrak AAA procedure, which deploys pre-column AccQTag derivatization with reversed-phase UPLC on a C18 column (2.1 × 150 mm; 1.7 µm) and UV detection at 260 nm. Accuracy, within-batch precision and short-term stability of the optimized VAMS protocol were determined. Results Extraction solvent with a 60:40 (v/v) water:methanol mixture provided the highest average amino acid recovery. This extraction solvent produced higher average amino acid recoveries at pH 11 (89±13%), than pH 3 (82±10%) or pH 7 (72±11%). Creatinine measured from the VAMS tips (N=44) had a consistent negative bias of 20% relative to neat urine (R=0.9905, slope=0.802, intercept=0.02). The creatinine corrected urine amino acid results from the Mitra device were corrected for this observed concentration bias. The accuracy of the amino acid results derived from the VAMS tip vs neat urine was 104 ± 14%. The average within-batch precision (CV%) of the amino acids was 9.8% (range=6.7% (cystine) to 17.6% (arginine)) and 6.2% for creatinine. The average 1 week storage stability at ambient temperature was 91% (range=73% (ornithine) to 107% (glycine)) for the amino acids and 107% for creatinine. The devised VAMS strategy was applied to the analysis of microsampled dried urine from a patient with cystinuria (OMIM no. 220100). Marked elevations in arginine, cystine, lysine and ornithine were respectively observed and are consistent with the biochemical diagnosis of the patient. Conclusions Creatinine corrected amino acid results from the devised VAMS strategy exhibit good precision and accuracy when compared to tradition analyses of neat urine. The potential use of microsampled dried urine for the diagnosis and monitoring of selected IEM has been demonstrated. The analytical and clinical performance of this VAMS protocol must be further validated, including the use of microsampled dried urine from home specimen collections.

A 2001–2022 global gross primary productivity dataset using an ensemble model based on the random forest method

Abstract. Advancements in remote sensing technology have significantly contributed to the improvement of models for estimating terrestrial gross primary productivity (GPP). However, discrepancies in the spatial distribution and interannual variability within GPP datasets pose challenges to a comprehensive understanding of the terrestrial carbon cycle. In contrast to previous models that rely on remote sensing and environmental variables, we developed an ensemble model based on the random forest method (denoted ERF model). This model used GPP outputs from established models: Eddy Covariance Light Use Efficiency (EC-LUE), GPP estimate model based on Kernel Normalized Difference Vegetation Index (GPP-kNDVI), GPP estimate model based on Near-Infrared Reflectance of Vegetation (GPP-NIRv), Revised-EC-LUE, Vegetation Photosynthesis Model (VPM), and GPP estimate model based on the Moderate Resolution Imaging Spectroradiometer (MODIS). These outputs were used as inputs to estimate GPP. The ERF model demonstrated superior performance, explaining 85.1 % of the monthly GPP variations at 170 sites and surpassing the performance of selected GPP estimate models (67.7 %–77.5 %) and an independent random forest model using remote sensing and environmental variables (81.5 %). Additionally, the ERF model improved accuracy across each month and with various subranges, mitigating the issue of “high-value underestimation and low-value overestimation” in GPP estimates. Over the period from 2001 to 2022, the global GPP estimated by the ERF model was 132.7 PgC yr−1, with an increasing trend of 0.42 PgC yr−2, which is comparable to or slightly better than the accuracy of other mainstream GPP datasets in terms of validation results of GPP observations independent of FLUXNET (i.e., ChinaFLUX). Importantly, for a growing number of GPP datasets, our study provides a way to integrate these GPP datasets, which may lead to a more reliable estimate of global GPP.

Designing Student Worksheets Based on Local Wisdom Using a Detailed Learning Model Integrated Discovery Learning on Biodiversity Material

The research that has been carried out is intended to produce student worksheets, which in Indonesian are abbreviated as LKPD. for Biology Learning based on Kerinci local wisdom, which is integrated with the Discovery Learning model on biodiversity material. This research is development research using the 4D model. The subject of this research is the class used in class X SMAN 2 Kerinci which consists of small group trials (9 people) and product trials (33 people). The data collection instrument in this research was a questionnaire where, at the development stage, the student worksheets were validated by material experts and design experts and assessed through responses from biology subject teachers. The data analysis technique used in this research uses a Likert scale. The research results show that material expert validation, with a percentage of 88.33%, is in the very good category. Furthermore, the design validation results are with a percentage of 98.33% in the very good category. The research results also showed that biology teachers responded to the developed student worksheets with a percentage of 87.50% in the "very good" category. The results of the small group trial of students were 76.62% in the "good" category, while the results of the large group trial were 80.37% in the "very good" category. Based on the results of validation and field trials, the LKPD based on Kerinci local wisdom, which is integrated with the Discovery Learning learning model on biodiversity material, is good and suitable for application in biology learning, especially on biodiversity material.

Flood Hazard Mapping in Cimandiri Watershed using Fuzzy Logic Method Based on Multi-Source Geospatial Datasets

Abstract Flood is a frequent disaster in the Cimandiri watershed. This is evidenced by the fact that during 2017-2022, 37 floods occurred in this area. This condition causes losses to the community and damage to the environmental ecosystem. Therefore, disaster management is needed to overcome and reduce the impact of this flood. One management that can be done is by mapping flood hazard areas. However, until now there is no map available that presents the flood hazard study area in the Cimandiri watershed. If available, the maps generally cover Regency, sub-Regency, or large-scale maps covering the entire territory of Indonesia. This condition causes deficiencies or misinformation on the map because the scale of the study is irrelevant. Based on this, this study attempts to conduct flood hazard mapping in the Cimandiri watershed with a scale of analysis of 100,000. This study uses fuzzy logic method to generate hazard maps based on spatial parameters, rainfall, distance from the river, elevation, slope, vegetation density, land cover, soil type, and topographic wetness. The results of this method produce a hazard map with a class range of 0 to 1, a class that is close to 1 means that it has a high level of hazard. To see the correctness of this map, a validation test was carried out using flood data from 2017-2022 which contained 37 flood event data. Based on the validation results, 86% of flood points are in the non-0 hazard class (low hazard), only 13% are incorrect because they are in the 0-hazard class.

Position query-guided cross-modal flow field prediction model of a transonic compressor cascade

The gradient of flow parameters in a transonic compressor cascade flow field varies significantly, especially in the region of shock waves, which causes a significant challenge to its high-precision flow field prediction. In this study, the position query-guided cross-modal flow field prediction model (PGCM) is proposed to effectively predict the flow field parameter distribution of a transonic compressor cascade. The PGCM utilizes the self-attention mechanism for the global and deep geometric feature extraction of configurations, which contributes to an in-depth understanding of the spatial relationships between coordinate points within the flow field, accurately capturing and analyzing the structural complexity of a compressor cascade flow. In addition, the PGCM integrates the cross-attention mechanism that establishes correlations between different input sequences, which enhances the performance of the model in querying and interpreting flow parameters at specific coordinates. The flow field prediction models are developed to predict the flow parameter distributions of different cascade geometries at Mach numbers of 0.78 and 0.93, respectively. The validation results indicate that the PGCM performs significantly better than the existing convolutional neural network and vision transformer, especially in the prediction of the pressure coefficient Cp distribution. The PGCM is adaptable to the variation of flow conditions and geometrical configurations efficiently and accurate in predicting the flow field of a compressor cascade. This paper demonstrates the promising potential of conducting the multi-modal information fusion to enhance the capability of flow field prediction.

Автоматизований метод перевірки та налагодження тестових сценаріїв на основі формальної моделі

Introduction. Model-based test cases generation is a popular strategy for test automation. It helps to reduce time spent on the development of a test suite and can improve level of coverage. However, many reports show shortage of such test cases in poor quality and doubtable efficiency. Purpose. The main goal of the proposed method is cost-effective validation, assessment, debugging and concretization of generated test cases. The method helps improve quality and efficiency of the test cases, make their scenario meaningful and goal-oriented. The method also develops debugging facilities and simplifies data dependency analysis and test scenario editing. Methods. We propose an automated post-processing method which allows to evaluate path that is examined by the test case, and to make safe changes to the path which will eliminate the shortcomings while leaving the coverage targets of the test case unharmed. The method is based on visualization of the path along the control flow graph of the model with additional information about factual evaluation history of all variables and possible alternative variants of behavior. For consistent substitution of certain values in the signal parameters, which would determine the artifacts of the test environment (such as, for example, files, databases, etc.) and check boundary cases (in predicates of conditions, indexing of arrays, etc.), a method of interactive specification of symbolic traces has been developed. Results. The role of the user in deciding whether to add a test case to the project test suite and make changes to it remains crucial, but to reduce labor intensity, the following processes are automated: evaluation of test scenarios according to certain objective characteristics (level of coverage, ability to detect defects, data cohesion, etc.); highlighting of possible alternatives for making corrections; consistent updating of computations for the corresponding corrections. A prototype was developed based on the proposed methods. The empirical results demonstrated a positive impact on the overall efficiency (ability to detect defects and reduce resource consumption) and quality (meaningfulness, readability, maintenance, usefulness for debugging, etc) of the generated test suites. The method allows to make automatically generated test cases trustable and usable. Conclusion. The proposed toolkit significantly reduces the time spent on researching the results of test generation and validation of the obtained tests and their editing. Unlike existing simulation methods, the proposed method not only informs about the values of variables, but also explores the history of their computations and additionally provides information about admissible alternatives. Further we plan to improve the process of localizing the causes of test failure at execution phase to speed up the search for defects.

Evaluation of mechanical properties of natural fiber based polymer composite

Natural fiber based polymer composites are eco-friendly alternatives to synthetic materials, with greater mechanical properties, biodegradability, availability, ease of access, and affordability. Jute fiber is widely recognized as one of the most important and beneficial natural fibers due to its strength, durability, and biodegradability. In this study, the jute composite is designed and fabricated using a 5-layer jute and epoxy resin, utilizing the manual hand lay-up technique. The combination of 52.5 % jute and 47.5 % of epoxy resin and harder is found optimized to achieve the goals of improving the tensile strength and flexural strength, reducing the cost of epoxy resin, and promoting eco-friendliness and sustainability. Tensile testing was performed on a universal testing machine, while flexural testing was done with a three-point bending test. Experimentally, the composites reinforced with jute and epoxy resin were capable of achieving the required levels of tensile strength (42.91 MPa) and bending strength (69.30 MPa). To validate and visualize specimens, numerical analysis was performed on the ABAQUS simulation software. The numerical simulation utilized ASTM D3039 and ASTM D7264 as the specified requirements for tensile and flexural behavior. For validation, these tensile and flexural test results were then numerically analyzed and compared to the experimental data. Finally, composite design, fabrication, and optimization can improve mechanical properties, reduce composite weight, lower resin cost, and increase sustainability. The proposed design and composition can be implemented to achieve lightweight properties in various applications, such as car components, door handle sheets, bicycle seat backs, and luggage covers.

Validation of OceanSat-3 sea surface winds for their utilization in the NCMRWF NWP assimilation systems

The Indian Space Research Organization (ISRO) launched OceanSat-3, the third-generation satellite in the OceanSat series, carrying a Ku-band scatterometer in November 2022. The novelty of the OceanSat-3 scatterometer (OSCAT-3) is its high-resolution sea surface wind products generated at 12.5 km in addition to 25 km. This study aims to check the quality of OSCAT-3 winds for their possible assimilation in the National Centre for Medium Range Weather Forecasting (NCMRWF) operational Numerical Weather Prediction (NWP) models. The newly available high-resolution OSCAT-3 wind products are validated against in-situ buoy winds and NCMRWF NWP model equivalents for six months from July to December 2023. The validation results of OSCAT-3 winds are also compared with those of the Advanced Scatterometer (ASCAT) onboard the Meteorological Operational Satellite-C (MetOp-C) using the same method. Validation of OSCAT-3 winds against buoy winds shows that the Root Mean Square Errors (RMSEs) in wind speed (direction) is less than 2 m/s (15°) over the Tropics (20° N − 20° S) and slightly higher than 2 m/s (20°) over the Northern Hemisphere (20° N − 90° N), which is closer to the satellite’s mission specifications of 1.8 m/s and 20°. The RMSE in the wind speed/direction in both the scatterometer winds are less than 2 m/s (20°) over the three different geographical regions: the Tropics, Northern Hemisphere, and Southern Hemisphere, but with lower errors for ASCAT winds. The better agreement of ASCAT winds with the NWP equivalents can be attributed partially to the routine assimilation of ASCAT winds in the NCMRWF operational NWP models and also due to the frequency of operation, C-band compared to the OSCAT-3 operated in the Ku band. Since there are three distinct datasets, scatterometer winds, buoy winds, and the NWP equivalents, triple collocation is also carried out in this study. Triple collocation also shows that the errors in OSCAT-3 winds are within the mission goal. The findings from this study indicate that the OSCAT-3 vector winds are of similar quality as its predecessors (OSCAT-2 and SCATSAT-1) and can be assimilated operationally in the NCMRWF NWP models as well as in other global operational NWP models.

Pengembangan Media E-Flipbook Materi Keragaman Sosial Budaya terhadap Sikap Toleransi Peserta Didik Kelas IV

This research aims to formulate learning media in the form of e-flipbooks of socio-cultural diversity material on tolerance attitudes in grade 4th students in elementary school. Research method applied in this study is research and development (RnD), utilizing ADDIE development model which includes stages of analysis, design, development, implementation, evaluation. The feasibility level of e-flipbook learning media is based on validation results of material and media experts, while the results of its use are measured through a self-assessment sheet on tolerance attitudes to students. The feasibility results assessed by material experts acquired an average score 84% with category “very feasible” while the feasibility results assessed by media experts acquired an average score 90% with category “very feasible”. The conclusion of this study, based on the results of the self-assessment sheet on the tolerance attitude of students carried out after using the e-flipbook learning media, showed an average score of 84% which is categorized as very good. Recommendations for further researchers to develop research that improves tolerance attitudes or other affective attitudes to improve future research.

Shape considerations for the design of propellers with trailing edge serrations

Noise reductions due to trailing edge serrations of several representative unmanned air vehicle propellers are calculated using a low-order methodology based on RANS simulations coupled with an extension of Ayton’s model proposed by Li and Lee, which provides a heuristic three-dimensional model for finite span applicable to rotor blades. The latter model is validated in the limit of zero serration amplitude against Amiet’s and Schlinker and Amiet’s models, finding good agreement at high frequencies for both airfoils and rotating blade elements. Similar good validation results are obtained for finite serrations by comparing with experiments achieved on the Controlled Diffusion airfoil at Université de Sherbrooke, and with calculations for a serrated blade element by Tian and Lyu. The coupled methodology is then validated both aerodynamically and acoustically with ISAE measurements for a representative drone propeller at different rotational speeds. The corresponding serrated model is then used to calculate noise reductions caused by different shapes. The square wave serration is shown to outperform the sawtooth and sinusoidal shapes for all frequencies and observer angles for small propeller blades typically used for drones. Yet, for larger chord blades typically used for ducted fans, combinations of sawtooth and sinusoidal serrations provide better noise reductions.

International Validation of the Vascular Registry of Switzerland, Swissvasc: A VASCUNET Report

Data validity and completeness is essential for registry data, and a meaningful interpretation of differences between countries can only be made if the data are robust within each of the countries. Therefore, the VASCUNET collaboration has performed validation of several vascular registries and has so far published the validation results of national vascular registries of Sweden, Denmark, and Malta. The findings of the validation of the Swissvasc Registry, the vascular registry of Switzerland, are presented here. Five of 34 hospitals participating in Swissvasc were visited by two international validators. Independent evaluation of the procedures of carotid endarterectomy, infrarenal abdominal aortic aneurysm (AAA) repair, and bypass surgery for lower extremity arterial disease (LEAD) was performed. Local administrative data and Swissvasc Registry data were compared for external validation, as well as registry data of 15 randomly picked cases within each group with data from individual patient records for internal validation. Hospital administrative data identified 265 carotid, 399 AAA, and 399 LEAD procedures, whereas Swissvasc identified 265 carotid, 398 AAA, and 395 LEAD procedures. Four LEAD procedures were found in hospital administrative data but not in Swissvasc. External validity was 100% for carotids, 99.8% for AAA, and 99% for LEAD. In internal validation, 5.2% of the variable data were missing in Swissvasc, and 2.4% were different from data in patient records, resulting in external validity of 92.8% for carotids, 94.4% for AAA, and 90.1% for LEAD. The VASCUNET template was used for international validation of registry data, and demonstrated that Swissvasc is a reliable system of quality data collection for the participating vascular centres, with excellent external validity and good internal validity. Quality in the Swissvasc registry data was clearly superior to local administrative data.

Deep learning-aided temporal downscaling of GRACE-derived terrestrial water storage anomalies across the Contiguous United States

The Gravity Recovery And Climate Experiment (GRACE) and GRACE-FollowOn (GRACE(−FO)) satellites have been monitoring Earth’s changes in terrestrial water storage (TWS) or surficial mass changes at monthly sampling and a spatial scale longer than ∼330 km (half wavelength) over the past two decades. At monthly sampling or revisit time, the use of satellite gravimetry is difficult to effectively monitor abrupt extreme weather events which are high-frequency, including the climate-induced hurricanes/cyclones, flash floods and droughts. The majority of the contemporary studies have focused on satellite gravimetry spatial downscaling, and not on reducing the temporal resolution of Earth’s mass change. Here, we developed a Deep Learning (DL) algorithm to downscale monthly GRACE/ GRACE(−FO) Mass Concentration (Mascon) TWS anomaly (TWSA) solutions to daily sampling over the Contiguous United States (CONUS), with the aim of monitoring rapidly evolving natural hazard episodes. The simulative performance of the DL algorithm is validated by comparing the modeling to an independent observation and the land hydrology model (LHM) predicted TWSA. To confirm that our daily and monthly simulations captured the climatic variations, we first compared our simulations with El Niño/La Niña Southern Oscillation (ENSO) circulation system index, which has a dominant climatological and socioeconomic impact across CONUS, and results reveal high correlations which are statistically significant. Next, we assessed the feasibilities to detect long- and short-term variations in the TWSA signals triggered by hydrological extremes, including the 2011 and 2019 Missouri River Floods, the August 2017 Atlantic Hurricane Harvey landfalls in Texas, the 2012–2017 drought in California, and the flash drought in the Northern Great Plains in 2017. Additional validation results using independent in situ observations reveal that our DL-aided gravimetry downscaled daily simulations are capable of elucidating hazards and water cycle evolutions at high temporal resolution.