Large-scale Tests Research Articles

Liver cancer in ovo models for preclinical testing.

Immunotherapies have significantly improved the prognosis of patients with advanced hepatocellular carcinoma (HCC), although more than 70% of patients still do not respond to this first-line treatment. Many new combination strategies are currently being explored, which drastically increases the need for preclinical models that would allow large-scale testing of new immunotherapies and their combinations. We developed several in ovo (in the egg) human liver cancer models, based on human tumor xenografts of different liver cancer cell lines on the chicken embryo's chorioallantoic membrane. We characterized the angiogenesis, as well as the collagen accumulation and tumor immune microenvironment, and tested atezolizumab (anti-PD-L1) plus bevacizumab (anti-VEGF) treatment. Our results show the involvement of chicken immune cells in tumor growth, reproducing a classical non-inflamed "cold" as well as inflamed "hot" tumor status, depending on the in ovo liver cancer model. The treatment by atezolizumab and bevacizumab was highly efficient in the "hot" tumor model PLC/PRF/5 in ovo with the reduction of tumor size by 76% (p ≤ .0001) compared with the control, whereas the efficacy was limited in the "cold" Hep3B in ovo tumor. The contribution of the anti-PD-L1 blockade to the anti-tumoral effect in the PLC/PRF/5 in ovo model was demonstrated by the efficacy of atezolizumab monotherapy (p = .0080, compared with the control). To conclude, our study provides a detailed characterization and rational arguments that could help to partially replace conventional laboratory animals with a more ethical model, suited to the current needs of preclinical research of new immunotherapies for liver cancer.

Development of wall volley digital test in badminton

Abstract: Introduction. Badminton is a sport that is popular with all levels of society, because it is easy to play and does not require a large field, and can even be played indoors or outdoors. Therefore, the game of badminton in Indonesia can develop rapidly. One of the tests in badminton definitely uses the wall volleyball test to determine the skill level of training children or students. As is known, the wall volleyball test is a very good test to see how far a person’s hitting ability in badminton is. The form of solving existing problems is by conducting research and developing wall volleyball tests so that teachers and coaches, especially athletes, no longer have doubts about their badminton skills. Objective. To develop one of the skills test tools in badminton, namely wall volleyball. Method. This research uses the research and development method which is used to produce certain product designs, test the effectiveness and validity of the designs that have been created so that the product is tested and can be used by the public. Results. Questionnaire results from small-scale tests on the development of digital-based wall volleyball tests in PB. Persada Kulon Progo Yogyakarta, showed an assessment percentage of 95.38% and was categorized as “Decent”. With such results, it is very feasible to continue this development to large-scale testing to see how feasible the results are with more people trying it and from different places. Large-scale trials were carried out at the PB club. PWS Godean Sleman and PB. Arjuna Bantul with a total of 35 athletes who met the criteria. Questionnaire results from a large-scale test of the development of a digital-based wall volleyball test in PB. PWS Godean Sleman and PB. Arjuna Bantul showed an assessment percentage of 99.56% and was categorized as “Decent”. With such results, this development is very feasible to continue to the next stage, namely effectiveness. Testing the validity of this digital-based wall volleyball test instrument includes testing material with a score of 11 out of 13 maximum scores and getting a percentage of 84.61% (Decent). Practitioner testing with a score of 11 out of 13 maximum scores and obtained a percentage of 84.61% (Layal). Meanwhile, testing the validity of test equipment experts with a score of 30 out of 32 maximum scores received a percentage of 93.75% (Decent). Based on the results of the data percentage above, what has been developed by the researchers received the title “feasible” and was declared valid. The first trial test between digital and manual tests was not significant because the results obtained were the same. Meanwhile, for the 2 digital and manual experimental tests, t = 4.779 and sig = 0.000 Sig < α (0.000 < 0.05), thus meaning that the 2 digital experimental tests are significantly different from the 2 manual tests. Conclusion. The development of a digital-based wall volleyball test was stated to be significant in achieving better results than the manual one.

Multi-guided population co-evolutionary algorithm based on multiple similarity decomposition for large-scale flexible job shop scheduling problem

As manufacturing shifts towards large-scale production, the size of the workshop increases, and its search space exponentially expands. It is difficult for existing algorithms to obtain an ideal scheduling solution in an acceptable time. For the large-scale flexible job shop scheduling problem (LSFJSP), a multi-guided population co-evolutionary algorithm based on multiple similarity decomposition (MPCSD) is designed. Faced with the problem of high dimensionality and complex solution space, a multiple similarity decomposition strategy is proposed. It proceeds to group based on similarity information at the dimension and population level. To obtain convergence-preferred and diversity-preferred dimension groupings, a training-set solution selection method is proposed. Inspired by the idea of divide-and-conquer, a multi-guided co-evolutionary strategy is proposed. It improves the exploration efficiency of the algorithm in the search space. To test effectiveness on more complex LSFJSP, a set of large-scale test problems including LS1-12 are designed. On LS1-12, MPCSD is compared with seven other algorithms to demonstrate its superiority. MPCSD performed best on 11, 7, and 10 of the 12 test problems on Inverted Generational Distance (IGD), Hypervolume (HV) and Schott’s Spacing Metric (SP), respectively. Meanwhile, the Relative Deviation (RD) results showed that MPCSD obtained the best fitness performance.

Tracking the pre-clinical progression of transthyretin amyloid cardiomyopathy using artificial intelligence-enabled electrocardiography and echocardiography.

Diagnosing transthyretin amyloid cardiomyopathy (ATTR-CM) requires advanced imaging, precluding large-scale testing for pre-clinical disease. We examined the application of artificial intelligence (AI) to echocardiography (TTE) and electrocardiography (ECG) as a scalable strategy to quantify pre-clinical trends in ATTR-CM. Across age/sex-matched case-control datasets in the Yale-New Haven Health System (YNHHS) we trained deep learning models to identify ATTR-CM-specific signatures on TTE videos and ECG images (area under the curve of 0.93 and 0.91, respectively). We deployed these across all studies of individuals referred for cardiac nuclear amyloid imaging in an independent population at YNHHS and an external population from the Houston Methodist Hospitals (HMH) to define longitudinal trends in AI-defined probabilities for ATTR-CM using age/sex-adjusted linear mixed models, and describe discrimination metrics during the early pre-clinical stage. Among 984 participants referred for cardiac nuclear amyloid imaging at YNHHS (median age 74 years, 44.3% female) and 806 at HMH (69 years, 34.5% female), 112 (11.4%) and 174 (21.6%) tested positive for ATTR-CM, respectively. Across both cohorts and modalities, AI-defined ATTR-CM probabilities derived from 7,423 TTEs and 32,205 ECGs showed significantly faster progression rates in the years before clinical diagnosis in cases versus controls (p time × group interaction ≤0.004). In the one-to-three-year window before cardiac nuclear amyloid imaging sensitivity/specificity metrics were estimated at 86.2%/44.2% [YNHHS] vs 65.7%/65.5% [HMH] for AI-Echo, and 89.8%/40.6% [YNHHS] vs 88.5%/35.1% [HMH] for AI-ECG. We demonstrate that AI tools for echocardiographic videos and ECG images can enable scalable identification of pre-clinical ATTR-CM, flagging individuals who may benefit from risk-modifying therapies.

Effective design of sustainable energy productivity based on the experimental investigation of the humidification-dehumidification-desalination system using hybrid optimization

Reliable and cost-effective industrial-based sustainable desalination technologies are crucial for efficient and effective desalination of saline water. Seawater desalination emerges as a vital treatment, with humidification-dehumidification identified as a promising technology due to its simple, low-maintenance design and compatibility with renewable energy sources. The present work was developed using a large-scale experimental test rig based on the performance of a humidification-dehumidification system operated by the heat pump. As such, the study presents an advanced approach for optimizing humidification-dehumidification desalination systems using hybrid machine learning optimization techniques. The effectiveness of a neuro-fuzzy model, a decision algorithm based on a boosted tree, and a simple averaging ensemble in enhancing the performance of humidification-dehumidification systems were investigated. Experimental data includes cold water flowrate (L/min), hot water flowrate (L/min), inlet air temperature (°C), inlet cold water temperature (°C), inlet hot water temperature (°C), and inlet air relative humidity (%) as input variables combination and freshwater productivity (L/h), recovery ratio (%) as target variables. Several statistical indicators were used to evaluate the models’ prediction skills; similarly, a 2-dimensional Taylor diagram and error-radial plot were also utilized. In the calibration phase, boosted tree models slightly outperform neuro-fuzzy models, particularly for recovery ratio, demonstrating high accuracy and low bias. However, all models exhibit robust predictive accuracy in the verification phase, especially for recovery ratio, emphasizing their potential in generalizing to unseen data. The result indicated that the boosted tree outperformed others with Nash–Sutcliffe Efficiency = 94 % and 88 % for recovery ratio and freshwater productivity, respectively. The simple averaging ensemble shows marginal improvement with 95 % accuracy for the recovery ratio. Integrating hybrid artificial intelligence optimization with humidification-dehumidification desalination systems marks a transformative step in addressing freshwater shortages. By utilizing cutting-edge machine learning techniques, we achieve a more efficient, accurate, and reliable prediction of desalination performance.

Investigating the contribution of student engagement and foreign language enjoyment to English majors’ TEM4-related positive emotions: A positive reinforcement perspective

With the rise of Positive Psychology, there have been abundant studies concerning positive emotions in English teaching and learning. However, the attention paid to positive emotions related to large-scale English tests as well as the influential factors of such emotions has been scarce. To this end, the present study, from the perspective of Positive Reinforcement, investigated to what extent Student Engagement (SE) and Foreign Language Enjoyment (FLE), as reinforcers, contribute to positive emotions related to Test for English Majors-Band 4 (TEM4). Altogether 580 English majors from universities across China were invited to complete three questionnaires as research instruments. Confirmative Factor Analysis was conducted with AMOS 24.0 to guarantee the construct, discriminant and convergent validity of each instrument, after which structural equation modeling and regression analysis were conducted to explore the contribution of SE and FLE to English majors’ TEM4-related positive emotions. The results of structural equation modeling indicated that both SE and FLE contribute significantly to TEM4-related positive emotions, respectively explaining 44.8 % and 51.8 % of the variance. The results of the present study were discussed, and some implications were offered at the end, concerning efforts that need to be made to promote SE and FLE, which ultimately foster English majors’ TEM4-related positive emotions.

Sliding Shear Failure of Basement-Clamped Reinforced Concrete Shear Walls.

After an earthquake struck Chile in 1985, sliding shear failure was observed in the clamping zone of stabilising walls. Even houses with only four storeys can fail due to sliding shear below basement ceilings. This type of failure has received little attention in the past; however, it leads to premature failure of the clamping effect in the basement box. Bending deformations cannot fully develop, which significantly reduces the seismic safety; it is thus important to learn more about the sliding shear failure of basement-clamped shear walls. The overall behaviour is analysed based on three large-scale shear wall tests. The deformation states around the sliding shear zone are evaluated and a simple estimate is given of when sliding shear failure can occur.

Load–displacement behavior of helical pile using Frustum Confining vessel (FCV) and full-scale testing in Babolsar sand

Nowadays, the use of deep foundations in various civil engineering projects, especially in marine and coastal structures, has been increasing. One type of deep foundations are helical pile foundations, which have gained significant attention in recent decades. This research investigates the load–displacement behavior of different helical pile configurations regarding geometry, i.e., helix diameter and spacing ratio (S/D) in two different soil densities under pullout and compressive loading conditions via the FCV-AUT device. Babolsar sand from the southern coast of the Caspian Sea was utilized for advancing this study. Additionally, four full-scale pile tests were conducted on the Caspian Sea coast under both grouted and non-grouted conditions for pullout and compressive loading. The results indicate that increasing the helix diameter, soil density, and S/D ratio enhances the compressive load-bearing capacity. However, in tensile loading, the ultimate load decreases with an increase in the spacing ratio. Furthermore, the grouting process in the three-helix pile exhibits better performance compared to the two-helix pile, potentially increasing the pile capacity up to 30%. In conclusion, the results obtained from the FCV device, utilizing scale theory, have been generalized to the large-scale pile test results in the field, are representative of in agreement and compatible.

Multi-scale experimental investigation on the structural behaviour of novel nanocomposite/natural textile-reinforced mortars

Natural fibre composites present a very appealing area of research for the structural strengthening of masonry structures. Natural fibres possess several drawbacks, such as low initial stiffness and poor interfacial bond behaviour with inorganic matrices that hinder their functions. Such challenges were overcome by applying an innovative nanocomposite-based impregnation system that was pre-engineered and presented by the authors previously. In this paper, a full experimental study involving pullout, tensile tests and large-scale testing via diagonal compression test was carried out to evaluate the structural efficiency of the developed system. Remarkable improvement at yarn-to-matrix level upon nanocomposite coating was observed. At a medium bond length, yarn rupture was observed, highlighting the great anchorage provided by the nanocomposite coating within the matrix. Coupons cast with the developed system demonstrated outstanding composite behaviour and multicracking under tensile loading. Finally, wallets strengthened with the developed system displayed multiple cracks and maintained high shear capacity (40–60 % of τmax) at remarkably large displacements developed at later stages of the test. Such ductility is crucial for retrofitting masonry structures, especially in seismic areas.

Development of Digital Biology Book on Antioxidant Activity of Red Dragon Fruit Extract (Hylocereus polyrhizus) for Class XI High School Students

With technological advances, digital-based learning resources are needed that can be studied by students independently. The results of the research can be used as a learning resource, one of which is in the form of a digital book. This study aims to determine the quality and feasibility of digital books compiled as learning resources. The type of research is research and development (R&D) which refers to the 4D development model (Define, Design, Development and Disseminate). Data collection techniques with instruments in the form of expert assessment questionnaires and response questionnaires. The research subjects consisted of material experts, media experts, biology teachers and 37 students of SMA N 1 Koba class XI. Product data were analyzed descriptively qualitatively to determine the quality and feasibility of the compiled digital book. The results of research and development (R&D) obtained a Digital Book product for high school students class XI bioprocess material. Product assessment by material experts 88.64% (very good), media experts 86.11% (very good), biology teacher experts 100% (very good). The results of the small-scale test of students were 94.29% (very good) and the large-scale test was 98% (very good). Results Based on this research, digital books are appropriate to be used as a learning resource for class XI cell bioprocess materials.

(Invited) Multi-Modal Solid-State Gas Sensors-Based Breath Analysis System with Convolutional Neural Network (CNN) for Early Detection of Lung Cancer

Currently, digital healthcare technologies based on Internet of Things (IOT) are emerging, and the market for digital healthcare was estimated to be 151.5 billion dollars by 2020. Among the digital healthcare technologies, disease diagnosis is attracting maximum attention. Traditional diagnostic methods, such as radiology and human biological material analysis, have limitations of long study time, high cost, radiation exposure, and pain. Therefore, non-invasive diagnostics methods, for early diagnosis of specific diseases and personal healthcare management, have attracted attention.Breath sensors are one of the promising candidates for the realization of non-invasive diagnosis owing to their ease of use, safety, and cost effectiveness. The exhaled breath analysis technique holds great promise as a non-invasive method for diagnosing lung cancer. In the breath of lung cancer patients, various volatile organic compounds (VOCs) markers are generated during metabolic processes. Analyzing these VOCs markers presents a compelling avenue for early and non-invasive lung cancer diagnosis. Solid state gas sensors capable of measuring specific VOCs are currently being researched and utilized as commercial gas sensors for this purpose. However, the concentration of lung cancer VOCs markers in exhaled breath is commonly very low, and individual commercial gas sensors often lack the necessary sensitivity and selectivity to accurately diagnose lung cancer. In this study, we propose a multimodal solid state electronic biosensor system designed to differentiate lung cancer VOCs characteristics among multiple VOCs, enabling exhalation-based lung cancer diagnosis. Initially, we developed multimodal biosensors using more than 20 gas sensors, consisting of metal oxide semiconductor sensors, electrochemical sensors, photoionized detectors, metalorganic frame sensors and so on. And each exhibiting varying sensitivity profiles for complex gas mixtures. Additionally, we designed a classification algorithm based on convolutional neural networks (CNN) and multi-layered perceptron (MLP) to distinguish between lung cancer patients and healthy individuals using the output from these diverse multimodal gas sensors. To evaluate the system's performance, we collected exhaled air samples from 74 lung cancer patients and 107 normal subjects, conducting clinical trials with our developed system. We did model evaluation with confusion matrix and ROC curve. The results of these tests confirmed that our system achieved a high predictive accuracy of over 95% in classifying lung cancer patients. The simplicity of the sensor configuration in our developed system makes it suitable for large-scale screening tests to identify potential candidates for precise lung cancer diagnosis. This technology has the potential to contribute to reduced national welfare costs and improved patient survival rates through early diagnosis.

Lentiviral vector packaging and producer cell lines yield titers equivalent to the industry-standard four-plasmid process

Lentiviral vector (LVV)-mediated cell and gene therapies have the potential to cure diseases that currently require lifelong intervention. However, the requirement for plasmid transfection hinders large-scale LVV manufacture. Moreover, large-scale plasmid production, testing and transfection all contribute to operational risk and the high cost associated with this therapeutic modality. Thus, we developed LVV packaging and producer cell lines, which reduce or eliminate the need for plasmid transfection during LVV manufacture. To develop a packaging cell line, lentiviral packaging genes were stably integrated by random integration of linearised plasmid DNA. Then, to develop EGFP- and anti-CD19 chimeric antigen receptor-encoding producer cell lines, transfer plasmids were integrated by transposase-mediated integration. Single cell isolation and testing were performed to isolate the top-performing clonal packaging and producer cell lines. Production of LVV that encode various cargo genes revealed consistency in the production performance of the packaging and producer cell lines compared to the industry-standard four-plasmid transfection method. By reducing or eliminating the requirement for plasmid transfection, while achieving production performance consistent with the current industry standard, the packaging and producer cell lines developed here can reduce costs and operational risks of LVV manufacture, thus increasing patient access to LVV-mediated cell and gene therapies.

Microdissected tumor cuboids: a microscale cancer model for large-scale testing that retains a complex tumor microenvironment.

Current cancer disease models fail to faithfully recapitulate key features of the human tumor microenvironment (TME), such as immune and vascular cells, while simultaneously enabling high-throughput drug tests. We have recently developed a precision slicing method that optimizes the yield of large numbers of cuboidal microtissues ("cuboids", ∼(400 µm) 3 ) from a single tumor biopsy. Here we demonstrate that cuboids from syngeneic mouse tumor models and human tumors retain a complex TME, making them amenable for drug and immunotherapy evaluation. We characterize relevant TME parameters, such as cellular architecture, cytokine secretion, proteomics profiles, and response to drug panels in multi-well arrays. Despite the cutting procedure and the time spent in culture (up to 7 days), the cuboids display strong cytokine and drug responses, including to immunotherapy. Overall, our results suggest that cuboids could provide invaluable therapeutic information for personalized oncology applications, and could help the development of TME-dependent therapeutics and cancer disease models, including for clinical trials.

Improving clay-geogrid interaction: Enhancing pullout resistance with recycled concrete aggregate encapsulation

In this study, Recycled Concrete Aggregate (RCA) was employed as a sandwich technique around the geogrid to enhance the pullout resistance of the geogrid in clayey backfills. Large-scale pullout tests were conducted on three configurations: geogrid-reinforced clay, geogrid-reinforced RCA, and geogrid sandwiched between layers of RCA, aimed at investigating pullout resistance and deformation. The experiments encompassed two different geogrid types (designated as G1 and G2), varying normal pressures ranging from 10 to 50 kPa, and RCA layers with thicknesses of 40, 80, 160, and 320 mm. Results from the experiments revealed that the inclusion of RCA layers around the geogrid substantially enhanced pullout resistance, with improvements ranging from 1.5 to 3 times compared to clay specimens. Optimal RCA thicknesses were determined in order to enhance soil-geogrid bonding and pullout resistance. For G1 geogrid, a thickness of 160 mm (equivalent to replacing 25% of clay volume with RCA) was identified as optimal, while for G2 geogrid, an 80 mm thickness (equivalent to replacing 15% of clay volume with RCA) was found to be sufficient. These thicknesses were established to achieve over 80% of the pullout force compared to full RCA specimens.

Analysis of thermally-induced fracture of Callovo-Oxfordian claystone: From lab tests to field scale

Argillaceous rocks are a suitable host rock for the deep geological disposal of exothermic High-Level Radioactive Waste (HLW) and Spent Fuel (SF). Excess pore pressures develop in this type of rocks when subject to increased temperatures that, in some circumstances, may lead to the fracturing of the rock. The paper explores this phenomenon by means of coupled numerical analyses carried out within a fully coupled thermo-hydro-mechanical (THM) framework. The general THM formulation is described as well as the anisotropic elastic and anisotropic elastoviscoplastic constitutive laws employed. Thermal extension triaxial tests are simulated as a check on the performance of the numerical formulation and to provide calibration data for the tensile strength of the material. Selected results from a comprehensive set of three-dimensional analyses of a large-scale field heating test, designed to study the possibility of thermal-induced failure in the rock, are presented and discussed. The analyses reproduce satisfactorily the observed patterns of behaviour. The effects of the constitutive law, material parameters and the presence of the excavation damage zone (EDZ) around the main drift and around the heater boreholes are studied. In particular, their effects on the state of the stress in the heated area are examined in the context of the potential for thermal fracturing of the rock.

Is the use of multiple-choice items and a holistically-scored paragraph translation task fair? Examining a large-scale translation subtest

AbstractThis study investigated the test fairness of the translation section of a large-scale English test in China by examining its Differential Test Functioning (DTF) and Differential Item Functioning (DIF) across gender and major. Regarding DTF, the entire translation section exhibits partial strong measurement invariance across female and male test takers, while exhibiting full measurement invariance across test takers in (1) arts & humanities and social sciences (A&HSS) and (2) science, technology, engineering or mathematics (STEM) majors. No major-based DIF was detected in this study. Objective test items tend to favor male test takers, while direct translation test task was more favorable to females. Combining the DIF and DTF results, there may be a cancelation effect in our case. However, the effect size of DIF is either negligible or slight to moderate, indicating minimal impact on the overall fairness of the translation test task. This study further discusses the necessity of exploring the source of DIF and the importance of combining DIF and DTF for test fairness research.

True and false positive HIV point of care test results in a prospective multinational study of at-risk African women: implications for large-scale repeat HIV testing in HIV prevention programs.

Accurate HIV point of care testing is the cornerstone of prevention and treatment efforts globally, though false (both negative and positive) results are expected to occur. We assessed the spectrum of true and false positive HIV results in a large prospective study of HIV incidence in African women using three contraceptive methods tested longitudinally in Eswatini, Kenya, South Africa, and Zambia. HIV serologic testing was conducted quarterly using two parallel rapid HIV tests. When one or both tests were positive, additional confirmatory testing was conducted, including HIV enzyme immunoassay (EIA) and ribonucleic acid (RNA). 7730 women contributed 48,234 visits: true positive results occurred at 412 visits (0.9%) and false positives at 96 visits (0.2%). Of 412 women with HIV seroconversion, 10 had discordant (i.e., one negative and one positive) rapid tests and 13 had undetectable HIV RNA levels. Of 62 women with false positive rapid HIV results, most had discordant rapid testing but six (9.7%) had dually-positive rapid results and four (6.5%) had false positive or indeterminate EIA results. The positive predictive value of dual positive rapid results was 98.3%. Although the majority of rapid test results were accurate, false positive results were expected and occurred in this population of initially HIV seronegative individuals tested repeatedly and prospectively. When HIV infection occurred, not all cases had textbook laboratory results. Our findings highlight the importance of confirmatory testing, particularly for individuals undergoing repeat testing and in settings where the point prevalence is expected to be low.

DEVELOPMENT OF TEACHING MATERIALS E-BOOK THEME 8 SUBTEMA 1 IN CLASS VI SOCIAL STUDY

This research was carried out to produce a product in the form of e-book format (electronic book) teaching materials that discuss ASEAN topics in social studies learning theme eight subthemes 1, uploaded on the Issuu platform. This research uses research and development (R&D) methods with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. Data was collected through two types of questionnaires: 1) a Validation questionnaire filled out by expert validators (teaching materials, material, language) to assess the suitability of the teaching materials. and 2) a User questionnaire filled out by class teachers and students. The teaching materials developed in this research have gone through a validation process by experts and users with the following results: Material experts gave a score of 80% with "decent" criteria, Linguist experts gave a score of 95% with "very decent" criteria, Media experts gave a score of 90.66% with "very decent" criteria and Users (class teachers) gave a score of 94.78 % with "very feasible" criteria. This teaching material has also been tested on students with the following results: an individual test was carried out on three female students with a result of 90.27%, a scale trial was carried out on eight female students with a result of 91.59%, and a large scale test: carried out on 20 students with a result of 83.09%. Based on the results of expert validation and positive user responses, it can be concluded that the ASEAN e-book developed using the ADDIE model is successful and suitable for social studies learning for class VI elementary school.

Large-scale direct shear testing for assessing interfacial parameters of natural and recycled sand with geosynthetic reinforcements

The demand for infrastructure projects is being driven by urbanization, which led to scarcity of natural sand (NS), which prompts exploration of alternative sustainable construction materials due to environmental concerns. Recycled sand (RS), processed from construction and demolition waste (C&DW), is an alternative material in infrastructure applications. Investigating interfacial shear behaviour between geosynthetic reinforcements with RS as a sustainable alternative material is crucial for infrastructure projects. This study presents the comprehensive large-scale direct shear testing (LSDST) on RS, NS, and its interfaces with ten types of geosynthetic reinforcements (i.e., polypropylene geogrids (GRD1 – GRD3), polyester geogrids (GRD4 – GRD6), and geotextiles (GT1 – GT4). LSDST were carried out using self-fabricated direct shear testing equipment of size equal to 500 mm x 500 mm x 300 mm (L x B x H). The findings indicate that the RS and NS exhibit similar shear strength parameters, sand-GRD interface demonstrates greater resistance compared to the sand-GT interface. RS and NS-GRD4 - GRD6 interfaces with transverse ribs and rough texture and NS-GRD1 interface with triangular apertures, exhibit significant shear strength parameters than the unstabilized case due to the mobilization of passive thrust. Interfacial shear coefficients for NS and RS range from 0.94 – 1.27 and 0.80 – 1.15 for GRD interfaces, and 0.89 – 1.06 and 0.86 – 0.99 for GT interfaces, respectively. Therefore, the RS can be a sustainable alternative for NS.

Jointly exploring mathematics ability and speed in large-scale computer-based testing

AbstractIn large-scale tests, the implementation of computer-based testing (CBT) allows to automatically collect data not only on the students’ response accuracy (RA) based on item responses of the test, but also on their response time (RT). RTs can provide a more comprehensive view of a test-taker’s performance beyond just what is obtainable based on correct responses alone. In this paper a joint approach is considered to improve the estimation of ability scores involving complex data coming from computer-based test administration. The study focuses on analysing the data of Italian grade 10 mathematics national assessment administered by the National Institute for the Evaluation of the Education and Training System (INVALSI). In addition, a bivariate multilevel regression with speed and ability estimates, obtained by joint model, is developed including individual covariates to evaluate the contribution of individual and contextual variables in predicting test-taking speed and ability. Overall, the main results indicate that mathematics ability and speed are significantly and negatively correlated, and that the hierarchical data structure (students nested into classes) should be taken into account when explaining the dependency of ability and speed on explanatory variables, such as prior achievement, test anxiety, sociodemographic covariates, class compositional variables, school tracks and geographical area.