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Exploring second-grade students' experiences through design-based learning in science education
No full textThis study examined second-grade students' experiences and learning outcomes during design-based learning (DBL) activities, along with the nurturing and thought-provoking strategies employed by educators. Using a qualitative case study design, data were collected from 15 s-grade students, varying academic achievement levels and learning styles, at a private primary school over six weeks, guided by the Stanford Design Thinking Model. Data sources included pre- and post-interviews, observation forms, and student documents. Thematic analysis revealed that students became more confident in solving complex problems, valued teamwork, and developed creative confidence and a growth mindset. They showed improvement in prototyping, testing, and refining ideas. Nurturing strategies, such as scaffolding, guidance, and feedback, supported student engagement, while thought-provoking approaches like promoting reflection and collaboration, enhanced learning. This study offers valuable insights for early science education, highlighting how structured support combined with open-ended inquiry can foster creativity, problem-solving, and motivation
Evaluating confidence in geometric matching between 3D point clouds and BIM models by integrating coverage, distance, and distribution metrics
No full textAccurate and objective assessment of the matching of a Building Information Model (BIM) with 3D point cloud data (PCD) is critical to Scan-to-BIM and Scan-vs-BIM workflows. However, existing methods for PCD-BIM matching evaluation do not fully and robustly account for geometric accuracy and spatial completeness. This paper introduces a statistically-grounded method that combines three indices that complementarily assess matching Coverage, Distribution, and Distance. The proposed method also accounts for inter-element occlusions when calculating each element's theoretically visible surface, which increases the metrics' reliability. Validation is conducted across 46 PCD-BIM pairs, encompassing 4000+ elements from ISPRS, CV4AEC, BIMNET and custom datasets, as well as a residential building case study comparing manual and automated BIM model reconstructions, and demonstrating the applicability of the method to any type of element. Results show practical value for both Scan-to-BIM and Scan-vs-BIM practice and enable quantitative assessment of benchmark dataset quality via the proposed indices
Firearm brand classification using deep learning on cartridge case images
No full textWhen a firearm is discharged, it leaves characteristic marks on the cartridge case, which are analyzed in forensic ballistics to identify the firearm. Conventional ballistic examination systems rely on high-quality images of cartridge cases and bullets, scanning databases to generate ranked candidate lists based on similarity scores. However, these systems often overlook the distinctive signatures of the firearm brand, which could refine search spaces and improve identification accuracy. In this study, we propose a deep learning-based approach leveraging normalized height maps and shape index transformation of cartridge cases for firearm brand classification. Using the BALISTIKA system, we generated high-resolution surface representations from over 350,000 cartridge cases representing the most populous 21 firearm brands, representing 97% of firearms encountered in criminal cases in T & uuml;rkiye, including handcrafted firearms and converted blank pistols (CBPs). By oversampling the minority classes in the dataset using rotated samples, we expanded it to over a million samples and mitigated class imbalance. We evaluated both traditional machine learning (SVM, Random Forest) and deep learning models (ResNet, Vision Transformer), with deep learning approaches achieving superior performance of up to 92% accuracy. These findings demonstrate that automated firearm brand classification enables forensic examiners to confidently prioritize cartridge cases from the same brand during ballistic comparisons. This approach is expected to substantially reduce examination time and enhance the efficiency of forensic investigations
In situ growth of S-scheme Zn2SnO4/Tb2O3 heterostructures for highly efficient visible-light-driven photocatalytic degradation and bacterial inactivation
No full textIt is critical to develop highly effective photocatalysts capable of efficiently utilizing visible light and promoting the rapid movement of photoinduced charge carriers to effectively eliminate the infection-causing bacteria. For this reason, we developed S-scheme Zn2SnO4/Tb2O3 heterostructures through in situ growth by incorporating terbium (Tb3+) ions to Zn2SnO4 host matrix. We also explored in detail their photodynamic activities on the degradation of Rhodamine B (RhB) organic pollutant and elimination of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria. Photodegradation experiments demonstrated that the Tb5@ZTO sample exhibited a superior photocatalytic degradation efficiency of 99.7 % under visible light within just 80 min, along with excellent reusability. This performance is 2.6 times higher than that of the pristine Tbfree@ZTO sample. Notably, Tb5@ZTO sample demonstrated 100 % and 96.5 % antibacterial activity under visible light after 3 h of incubation against E. coli, and for 5 h of incubation against S. aureus, representing 2.78- and 2.53-fold improvements compared to the pristine sample. The strong antibacterial activity was attributed to the efficient separation of photoinduced electron-hole (e−/h+) pairs, suppression of recombination, increased oxygen vacancies, and the high surface area of the porous structures, all of which collectively enhance the generation of reactive oxygen species (ROS). Furthermore, the cytocompatibility of the heterostructures was confirmed. Based on these findings, Zn2SnO4/Tb2O3 heterostructures are regarded as promising antibacterial therapeutic agents and may possess significant potential in the healing of bacteria-infected wounds
Facile and Cost-Effective Production of High-Performance Bi<sub>2</sub>Te<sub>3</sub>-Based Thermoelectric Materials
No full textThermoelectrics have the potential to be utilized for localized power generation and refrigeration by enabling direct conversion between heat and electrical energy. In this study, we present a simple and affordable approach for the synthesis of high-performance Bi2Te3-based thermoelectric (TE) materials using cold press (CP) and cold isostatic press (CIP) methods. The results indicate that Bi2Te3-based materials synthesized using this approach exhibit remarkable TE performance, with cost-effective and simple production. A notable enhancement in power factor (PF) values was observed upon transition from CP to CIP. The PF increased from 0.57 mW/mK-2 to 1.0 mW/mK-2 for the n-type BiTeSe sample and from 1.0 mW/mK-2 to 2.34 mW/mK-2 for the p-type BiSbTe sample. In samples subjected to consecutive CP and CIP processes, a simultaneous enhancement in electrical conductivity and reduction in thermal conductivity contributed to an enhanced ZT value at room temperature, increasing from 0.4 to 0.8 for the n-type BiTeSe sample and from 0.4 to 1.5 for the p-type BiSbTe sample. This approach thus provides an alternative solution for the scalable and cost-effective production of Bi2Te3-based TE materials, which have potential applications in waste heat recovery and solid-state cooling
Effect of microdamage on the failure of open-hole UD GFRP laminates: A combined experimental and numerical study
No full textThe effect of microdamaging on the failure of unidirectional Interglas 92145/CR80 GFRP laminates is studied through experiments and a numerical approach combining Enhanced Schapery Theory (EST) and Crack Band Theory (CBT). Open-hole tension tests with various layer configurations, along with flat tensile tests were conducted to examine failure modes and their progression. The initiation and development of failure mechanisms were tracked experimentally using DIC imaging. In the numerical model, the matrix microdamage is represented through dissipated energy-dependent functions derived from standardized mechanical tests. Without discretely modeling splitting cracks, the numerical approach captured narrow zones of fiber and matrix failure coincident with experimentally observed crack paths. Axial, transverse, and shear strain fields from the physical and virtual tests were compared at the critical stages of the testing regimen. Comparison of the strain fields, as well as stressstrain curves from the numerical and experimental studies showed good agreement, suggesting that incorporation of microdamage modeling-rarely implemented in progressive failure analyses-offers potential for improving failure predictions in GFRP laminates
Fish promote stronger functional changes in microcrustaceans than macroinvertebrates in artificially vegetated mesocosms in both subtropical and temperate lakes
No full textPredation by fish and macroinvertebrates may differentially shape the functional traits of microcrustaceans to avoid predation. To test this, we conducted a 49-day mesocosm experiment in shallow lakes in temperate (Denmark) and subtropical (Uruguay) regions. Treatments included (1) fish only, (2) macroinvertebrates only, (3) both predators, and (4) a control with no predators. Microcrustaceans were identified to species level and classified by functional traits (predator escape tactics, body size, and feeding strategy), with data analyzed using generalized linear mixed models. Fish predation strongly targeted large, rapid swimming microcrustaceans, with significant differences in density between treatments containing fish (alone or combined with macroinvertebrates) and the control and macroinvertebrate-only treatments. Contrary to predictions and previous studies, macroinvertebrates showed minimal effects on microcrustacean functional traits, even in warmer systems. We conclude that fish play a dominant role in structuring microcrustacean functional diversity compared to macroinvertebrates, although further experimental validation is needed to generalize these findings
Mindset and achievement in general chemistry: insights from Turkish undergraduate students
No full textChemistry-specific mindsets have been shown to influence student engagement, self-efficacy, goal orientation, and academic achievement in chemistry. These beliefs are increasingly recognized as context-dependent, shaped through interactions within specific social and educational environments. The present study investigated the extent to which Turkish undergraduates have a growth chemistry mindset and how these beliefs relate to academic performance in chemistry across engineering and natural sciences majors. A total of 817 second-semester general chemistry students participated, completing surveys after the second midterm and prior to the final exam. The Chemistry Mindset Instrument (CheMI; Santos D. L., Barbera J. and Mooring S. R., (2022), Chem. Educ. Res. Pract., 23(3), 742-757) was used to assess students' mindsets, while grade records provided measures of exam performance. Confirmatory factor analysis (CFA) supported the unidimensional structure of the CheMI, consistent with previous findings, providing evidence for its validity in this cultural and educational context. Structural equation modeling (SEM) examined whether chemistry mindset mediated the relationship between midterm and final exam performance across majors. Additional regression analyses explored how mindset influenced the midterm-final performance relationship among students with low, medium, and high levels of achievement. SEM results indicated that second midterm performance did not significantly predict mindset for either major. However, mindset significantly predicted final exam performance for engineering students, whereas this relationship was nonsignificant for natural sciences students. Furthermore, mindset emerged as a significant predictor only among the highest-performing students, suggesting that it may play a differentiating role at the upper end of achievement. These findings underscore the importance of considering mindset in instructional design and provide insights for targeted strategies to enhance student success in chemistry
First Exclusive Reconstruction of the (Formula presented), (Formula presented), and (Formula presented) Mesons and Precise Measurement of Their Masses
No full textUsing proton-proton collision data collected by the CMS experiment at (Formula presented) in 2016-2018, corresponding to an integrated luminosity of (Formula presented), the first full reconstruction of the three vector (Formula presented) meson states, (Formula presented), (Formula presented), and (Formula presented), is performed. The mass differences between the excited mesons and their corresponding ground states are measured to be (Formula presented), (Formula presented), and (Formula presented), where the first uncertainties are statistical and the second are systematic. These results improve on the precision of previous measurements by an order of magnitude