Blending Process Research Articles

교직이론 과목에서 현장 역량 강화를 위한 혼합형 PBL 수업 사례 연구

This study attempted to present a specific case of blended Problem-Based Learning (PBL) in teacher education course to enhance the field competency of pre-service teachers. The participants were first-year adult learners majoring in Early Childhood Education who were enrolled in the educational psychology course. The blended PBL process was organized by appropriately combining face-to-face and online sessions, following the sequence of 'Course Introduction,' 'Problem Presentation,' 'Subsequent Problem Steps,' 'Presentation of Results and Discussion,' and 'Review and Evaluation of Learning Outcomes.' Five PBL problems were developed, and during the initial five weeks, students were assigned to individually contemplate one problem per week. In the 10th week, a face-to-face group discussion session was conducted. Subsequently, continuous online communication through Learning Management System (LMS) and Social Networking Services (SNS) was maintained, leading to the group presentation of the final project at the end of the semester. The analysis of reflection journals submitted by students after the class was conducted to assess the effectiveness of a blended PBL course. The case presented in this study proposes a form of instructional design that integrates real-world experiences, suggesting a hybrid approach to PBL in education. Furthermore, the application of blended PBL in educational psychology courses suggests the potential to enhance field competency in teacher education courses.

Porous Polymer Structures with Tunable Mechanical Properties Using a Water Emulsion Ink.

Recently, the manufacturing of porous polydimethylsiloxane (PDMS) with engineered porosity has gained considerable interest due to its tunable material properties and diverse applications. An innovative approach to control the porosity of PDMS is to use transient liquid phase water to improve its mechanical properties, which has been explored in this work. Adjusting the ratios of deionized water to the PDMS precursor during blending and subsequent curing processes allows for controlled porosity, yielding water emulsion foam with tailored properties. The PDMS-to-water weight ratios were engineered ranging from 100:0 to 10:90, with the 65:35 specimen exhibiting the best mechanical properties with a Young's Modulus of 1.17 MPa, energy absorption of 0.33 MPa, and compressive strength of 3.50 MPa. This led to a porous sample exhibiting a 31.46% increase in the modulus of elasticity over a bulk PDMS sample. Dowsil SE 1700 was then added, improving the storage capabilities of the precursor. The optimal storage temperature was probed, with -60 °C resulting in great pore stability throughout a three-week duration. The possibility of using these water emulsion foams for paste extrusion additive manufacturing (AM) was also analyzed by implementing a rheological modifier, fumed silica. Fumed silica's impact on viscosity was examined, revealing that 9 wt% of silica demonstrates optimal rheological behaviors for AM, bearing a viscosity of 10,290 Pa·s while demonstrating shear-thinning and thixotropic behavior. This study suggests that water can be used as pore-formers for PDMS in conjunction with AM to produce engineered materials and structures for aerospace, medical, and defense industries as sensors, microfluidic devices, and lightweight structures.

THE BENEFITS OF USING THE BLENDED LEARNING METHODOLOGY IN CONDITIONS OF WAR

In the context of a full-scale war, participants in the educational process are implementing innovative strategies for adapting to new realities, based on the development and application of models of blended learning. The purpose of the academic paper is to study the features of the blended learning methodology in crisis situations with the identification of advantages and risks. The research was conducted using general scientific methods of cognition: analysis, synthesis, comparison, abstraction, specification, generalization, and formalization. In the course of the research, the existing models of the mixed type of educational process and the means of their practical implementation in educational institutions were analyzed. The problems of blended learning in the crisis period of military conflict are actualized, its features are presented. The risks accompanying the process of implementing the blended learning methodology are identified, and variations of measures to prevent them are proposed. It has been proven that the quality of the blended learning process depends on the teacher’s digital competencies in the online process. It has been established that the trend under study enriches the students’ learning experience and stimulates their motivation to study. The level of efficiency of blended learning is analyzed in comparison with distance and traditional learning. It has been determined that blended learning is much more effective than traditional and distance learning subject to careful planning of the educational process and a reasonable selection of tools. The essence of the methodology of blended learning as an innovative technology of the educational process and its effective anti-crisis format is proven. The practical significance of the research results lies in the possibility of their productive use in the process of optimizing the system of education in war conditions by improving existing and developing new methods and algorithms of blended learning.

Polyamide 66/poly(2,6-dimethyl-1,4-phenylene oxide) compatibilization with styrene–acrylonitrile–glycidyl methacrylate: rheology, morphology, and mechanical properties

During the blending process, styrene–acrylonitrile–glycidyl methacrylate (SAG) was grafted through in-situ formation of polyamide 66 (PA66) as a compatibilizer for poly (2,6-dimethyl-1,4-phenoxy) (PPO) composites. SAG has an obvious advantage over the PA66/PPO blends in terms of terminal performance in the dynamic rheological analysis. Moreover, the gap between the PA66 and PPO glass-transition temperatures decreases with the SAG content increasing, which indicates improved compatibility. The particle morphology of the PA66/PPO/SAG blends had narrower size distributions and became smaller after adding SAG. In addition, the compatibilization improved the mechanical properties of blends significantly when SAG reached 5 by weight per hundred resins (phr). This is attributed to enhanced interfacial adhesion and a finer dispersion morphology. However, when 7 phr of SAG are added, the exceeded compatibilizer produces a limitation on the improvement of the mechanical properties. Our results indicate that the optimal concentration of the compatibilizer, SAG, is between 3 and 5 phr for PA66/PPO (60/40).

Study on Rheological Properties and Modification Mechanism of Budun Rock Asphalt/Nano-Silica Composite Modified Asphalt

To enhance the high and low-temperature performance of asphalt materials and extend the service life of asphalt pavement, two types of external admixtures, Butonite rock asphalt, and nano-silica are added to the asphalt. By conducting dynamic shear rheological tests and bending creep stiffness tests, the high and low-temperature rheological properties of Budun rock asphalt/nano-silica composite-modified asphalt were evaluated. The distribution of Budun rock asphalt and nano-silica in asphalt was studied using scanning electron microscopy and infrared spectroscopy tests, revealing the synergistic modification mechanism of Budun rock asphalt and nano-silica. The results show that the optimal dosage of Butonite rock asphalt and nano-silica composite-modified asphalt is 25% and 5%, respectively. At this dosage, the rutting factor G*/sinδ of composite-modified asphalt at 82 °C Compared with the matrix asphalt, the frequency main curve of Budun rock asphalt/nano-silica composite-modified asphalt is higher than that of the matrix asphalt and nano-silica-modified asphalt by 4 kPa. The creep modulus S at −18 °C decreases by 117.2 MPa, indicating that the high-temperature performance, low-temperature performance, and temperature sensitivity of Budun rock asphalt/nano-silica composite-modified asphalt are significantly improved compared to the matrix asphalt; The distribution of nano-silica particles in Budun rock asphalt/nano-silica composite-modified asphalt is uniform, and together with Budun rock asphalt, it forms a stable three-dimensional network skeleton structure; Budun rock asphalt/nano-silica composite-modified asphalt has generated new functional groups, and the blending process is mainly based on physical reactions, supplemented by weak chemical reactions.

Preparation and characterization of poly(vinyl alcohol)/poly(lactic acid) blends containing bio‐based plasticizers

AbstractThe bio‐based plasticizers‐glycerol and lactic acid were used to plasticize and compatibilize PVA/PLA blends during melt blending process. It was confirmed that lactic acid significantly improved the compatibility between glycerol‐plasticized PVA and PLA. Compared with pure PVA, the melting and crystallization temperatures and crystallinities decreased but the crystal form of PVA in the blends was not changed. The thermal stabilities of PVA/glycerol (G)/lactic acid (L)/PLA blends were better than PVA/G/PLA blends. Compared to PVA/G/PLA blends, the tensile and tear strength of PVA/G/L/PLA blends were improved, however, elongation at break decreased. The water absorptions and water vapor permeances of the blends decreased with the addition of hydrophobic PLA, but they increased by incorporation of hygroscopic lactic acid. The surface resistivities of the blends augmented in combination with PLA but declined by adding lactic acid. The melt flow rates of PVA/G/PLA blends were better than PVA/G/L/PLA blends because lactic acid enhanced the interactions among the components. After the addition of lactic acid, the transmittances of the blends increased due to the refined dispersed phases by the compatibilization. The compatibility between the components was predicated by Hansen solubility parameters. These blends showed potential as a novel barrier material for food and medicine packages.Highlights PVA, glycerol, and PLA blends were compatibilized by lactic acid. The melting temperatures decreased with addition of glycerol and lactic acid. The tensile and tear strengths were enhanced with addition of PLA and lactic acid. The hydrophobicity, melt fluidity, and surface resistivity were improved by PLA.

Experimental Investigations in the Processing of AISI H11 Powder Blends Enriched with Tungsten Carbide Nanoparticles for the Additive Manufacturing of Tailored Hot Working Tools in the Directed Energy Deposition (DED-LB/M)—Impact of Tungsten Carbide Nanoparticles on Microstructural and Mechanical Characteristics

In this study, the DED-LB/M process of AISI H11 tool steel powder blends modified by adding WC nanoparticles (WC-np) in concentrations of 1, 2.5 and 5 wt.-% was the object of scientific investigations. For this, 30-layer cuboid specimens were manufactured. The overall scientific aim was to examine how the WC-np interact with the steel melt and in the end, influence the processability, microstructure and mechanical properties of produced specimens. The examinations were carried out on both as-built and thermally post-processed specimens. An advanced microstructural analysis (SEM, EDS, EBSD and XRD) revealed that due to the high solubility of WC-np in the molten steel, most of the WC-np appear to have dissolved during the ongoing laser process. Furthermore, the WC-np favor a stronger distortion and finer grain size of martensite in the manufactured specimens. An increase in hardness from about 650 HV1 for the H11 specimen to 780 HV1 for the one manufactured using the powder blend containing 5 wt.-% of WC-np was observed in as-built conditions. In the same way, the compression yield strength enhanced from 1839 MPA to 2188 MPA. The hardness and strength increasing effect of WC-np remained unchanged even after heat treatments similar to those used in industry.

Drivers of undergraduate students’ learning perceptions in the blended learning environment: The mediation role of metacognitive self-regulation

In student-centric learning environments, such as blended learning, students’ metacognitive self-regulation is required to plan, monitor, and control their learning processes and achieve positive learning outcomes. The lack of metacognitive self-regulation may lead students to encounter difficulties that, eventually, affect their learning perceptions. Therefore, understanding how to drive students' metacognitive self-regulation is essential to delivering an effective blended learning process that supports students' learning perceptions. This study examines the structural relationships between academic self-efficacy, student–student interaction, student–lecturer interaction, metacognitive self-regulation (including planning, monitoring, and regulating), and perceived learning using structural equation modeling. The data were collected from 1675 undergraduate students who experienced blended learning at Egyptian universities. The findings revealed that academic self-efficacy, student–student interaction, and student–lecturer interaction have significant direct effects on the planning, monitoring, and regulating dimensions of metacognitive self-regulation. Furthermore, metacognitive self-regulation dimensions not only influence perceived learning but also mediate the effects of academic self-efficacy, student–student interaction, and student–lecturer interaction on perceived learning, except for monitoring, which has an insignificant mediation effect on the relationship between student–student interaction and perceived learning. The findings of this study may help researchers, practitioners, and stakeholders gain deep insights regarding how to promote tertiary students’ metacognitive self-regulation and learning perceptions during the blended learning experience.

Effective Knowledge Dissemination Modeling and Regulation in Blended Learning Networks

Blended learning networks (BLNs) based on the integration of online learning networks and offline learning environments provide new opportunities and platforms for people to acquire and update useful knowledge and carry out all kinds of learning activities anytime and anywhere. Effective modeling and regulation of the knowledge dissemination process can accurately grasp its dissemination process, promote knowledge innovation and collaborative sharing among learners, and accelerate the maximization of knowledge dissemination. However, it is a challenge to establish a comprehensive dynamics model and adopt the optimal regulation for the knowledge dissemination process under the constraints of a limited budget in large-scale BLNs with diverse learners. To this end, we first explore the evolution process of knowledge dissemination in BLNs and the blended learning interaction process of learners. Based on the system dynamics modeling theory, a dynamics model of knowledge dissemination is established. Second, two kinds of effective regulation strategies are proposed. We establish an optimal regulation system intending to maximize the dissemination of knowledge and use the optimal control theory to tackle the optimal solution distribution of regulation strategies. Then, we propose a knowledge dissemination regulation task allocation method based on the collaborative participation of users, and the reverse auction theory is used to quickly solve the task allocation scheme while ensuring performance. Finally, we demonstrate the effectiveness of proposed models and methods through extensive simulation experiments based on real datasets.

Reprocessing and Resource Utilization of Landfill Sludge—A Case Study in a Chinese Megacity

In the past, due to improper sludge treatment technology and the absence of treatment standards, some municipal sludge was simply dewatered and then sent to landfills, occupying a significant amount of land and posing a serious threat of secondary pollution. To free up land in the landfill area for the expansion of a large-scale wastewater treatment plant (WWTP) in Shanghai, in this study, we conducted comprehensive pilot research on the entire chain of landfill sludge reprocessing and resource utilization. Both the combination of polyferric silicate sulfate (PFSS) and polyetheramine (PEA) and the combination of polyaluminum silicate (PAS) and polyetheramine (PEA) were used for sludge conditioning before dewatering, resulting in dewatered sludge with approximately 60% moisture content. The combined process involved coagulation and sedimentation, flocculation, and oxidation to treat the leachate generated during dewatering. The treatment process successfully met the specified water pollutant discharge concentration limits for the leachate, with the concentration of ammonia nitrogen in the effluent as low as 15.6 mg/L. Co-incineration in a power plant and modification were applied to stabilize and harmlessly dispose of the dewatered sludge. The coal-generating system ran stably, and no obvious problems were observed in the blending process. In the modification experiment, adding 5% to 7% of the solidifying agent increased the sludge bearing ratio by 53% and 57%, respectively. This process effectively reduced levels of fecal coliforms and heavy metals in the sludge but had a less noticeable effect on organic matter content. The modified sludge proved suitable for use as backfill material in construction areas without requirements for organic matter. The results of this study provide valuable insights for a completed full-scale landfill sludge reclamation and land resource release project.

Biodegradable Nanocomposites Based on Blends of Poly(Butylene Adipate-Co-Terephthalate) (PBAT) and Thermoplastic Starch Filled with Montmorillonite (MMT): Physico-Mechanical Properties.

Poly(butylene adipate-co-terephthalate) (PBAT) is widely used for production of biodegradable films due to its high elongation, excellent flexibility, and good processability properties. An effective way to develop more accessible PBAT-based bioplastics for wide application in packaging is blending of PBAT with thermoplastic starch (TPS) since PBAT is costly with prices approximately double or even triple the prices of traditional plastics like polyethylene. This study is focused on investigating the influence of TPS/PBAT blend ratio and montmorillonite (MMT) content on the physical and mechanical properties and molecular mobility of TPS-MMT/PBAT nanocomposites. Obtained TPS-MMT/PBAT nanocomposites through the melt blending process were characterized using tensile testing, dynamic mechanical thermal analysis (DMTA), and X-ray diffraction (XRD), as well as solid-state 1H and 13C NMR spectroscopy. Mechanical properties demonstrated that the addition of TPS to PBAT leads to a substantial decrease in the tensile strength as well as in the elongation at break, while Young's modulus is rising substantially, while the effect of the MMT addition is almost negligible on the tensile stress of the blends. DMTA results confirmed the formation of TPS domains in the PBAT matrix. With increasing TPS content, mobility of starch-rich regions of TPS domains slightly increases. However, molecular mobility in glycerol-rich regions of TPS domains in the blends was slightly restricted. Moreover, the data obtained from 13C CP/MAS NMR spectra indicated that the presence of TPS in the sample decreases the mobility of the PBAT chains, mainly those located at the TPS/PBAT interfaces.

Engineering Dry Electrode Manufacturing for Sustainable Lithium-Ion Batteries

The pursuit of industrializing lithium-ion batteries (LIBs) with exceptional energy density and top-tier safety features presents a substantial growth opportunity. The demand for energy storage is steadily rising, driven primarily by the growth in electric vehicles and the need for stationary energy storage systems. However, the manufacturing process of LIBs, which is crucial for these applications, still faces significant challenges in terms of both financial and environmental impacts. Our review paper comprehensively examines the dry battery electrode technology used in LIBs, which implies the use of no solvents to produce dry electrodes or coatings. In contrast, the conventional wet electrode technique includes processes for solvent recovery/drying and the mixing of solvents like N-methyl pyrrolidine (NMP). Methods that use dry films bypass the need for solvent blending and solvent evaporation processes. The advantages of dry processes include a shorter production time, reduced energy consumption, and lower equipment investment. This is because no solvent mixing or drying is required, making the production process much faster and, thus, decreasing the price. This review explores three solvent-free dry film techniques, such as extrusion, binder fibrillation, and dry spraying deposition, applied to LIB electrode coatings. Emphasizing cost-effective large-scale production, the critical methods identified are hot melting, extrusion, and binder fibrillation. This review provides a comprehensive examination of the solvent-free dry-film-making methods, detailing the underlying principles, procedures, and relevant parameters.

Using AI/ML to predict blending performance and process sensitivity for Continuous Direct Compression (CDC)

Utilising three artificial intelligence (AI)/machine learning (ML) tools, this study explores the prediction of fill level in inclined linear blenders at steady state by mapping a wide range of bulk powder characteristics to processing parameters. Predicting fill levels enables the calculation of blade passes (strain), known from existing literature to enhance content uniformity. We present and train three AI/ML models, each demonstrating unique predictive capabilities for fill level. These models collectively identify the following rank order of feature importance: RPM, Mixing Blade Region (MB) size, Wall Friction Angle (WFA), and Feed Rate (FR). Random Forest Regression, a machine learning algorithm that constructs a multitude of decision trees at training time and outputs the mode of the classes (classification) or mean prediction (regression) of the individual trees, develops a series of individually useful decision trees. but also allows the extraction of logic and breakpoints within the data. A novel tool which utilises smart optimisation and symbolic regression to model complex systems into simple, closed-form equations, is used to build an accurate reduced-order model. Finally, an Artificial Neural Network (ANN), though less interrogable emerges as the most accurate fill level predictor, with an r2 value of 0.97. Following training on single-component mixtures, the models are tested with a four-component powdered paracetamol formulation, mimicking an existing commercial drug product. The ANN predicts the fill level of this formulation at three RPMs (250, 350 and 450) with a mean absolute error of 1.4%. Ultimately, the modelling tools showcase a framework to better understand the interaction between process and formulation. The result of this allows for a first-time-right approach for formulation development whilst gaining process understanding from fewer experiments. Resulting in the ability to approach risk during product development whilst gaining a greater holistic understanding of the processing environment of the desired formulation.

Experimental analysis of surface integrity in electro-discharge coating process

Utilising electro-discharge machining, powdered metallurgical tool materials are applied to coat the surface pattern-wise. The tool undergoes a thorough blending process followed by hydraulic pellet press. Essential evaluations encompass the determination of material deposition rate, tool wear rate, surface roughness, microhardness, layer thickness and wear rate. Characterisations confirm the presence of tool constituents, provide insights into its constituent's composition and reveal the formation of tungsten carbides on the uppermost surface of the deposit. Significantly, a substantially higher deposition rate of 4.9 mg/min is achieved when a compact load of 10 tons and a peak current of 2.5A are applied. Notably, the top surface exhibits a microhardness of 330.5 HV, while the base material maintains a hardness level of 98.7 HV. The maximum thickness of the deposited layer reaches 293.68 μm under identical conditions. These hard materials serve to mitigate the specific wear rate effectively.

Pectinase‐Driven Optimization of Pectin Hydrolysis for Enhanced Clarity, Anthocyanin Retention, and Consumer Appeal in Red Dragon Fruit Mint Flavored Beverage

This study is aimed at analyzing, evaluating, and optimizing the pectin hydrolysis process to improve the quality of carbonated beverages made from red dragon fruit combined with mint flavor. Red dragon fruit, rich in nutrients and antioxidants, presents challenges in beverage processing due to its high pectin content, which affects clarity and anthocyanin stability. The research investigates the impact of various parameters, including enzyme concentration, hydrolysis time, and temperature, on juice clarity and anthocyanin content. Using a central composite design model, optimal conditions were determined to maximize juice clarity and anthocyanin content. Sensory evaluation during the blending process was also conducted to assess consumer acceptance, focusing on clarity, color, flavor, taste, and total acceptability. The optimum conditions were found to yield maximum clarity (52.763%) and anthocyanin content (224.414 mg C3G/L). Sensory evaluation indicated that 20% dragon fruit juice concentration with 0.12% citric acid, 13°Bx, and 0.30% mint flavor provided the best consumer acceptance. This research demonstrates the potential for producing high‐quality, appealing, and nutritious carbonated beverages from red dragon fruit, contributing to healthier and more sustainable consumption trends.

The Impact of Chitosan Incorporation on the Mechanical Characteristics of Biodegradable Packaging based on PLA/PCL Blend

The development of environmentally sustainable plastics has gained prominence due to their eco-friendliness and renewable nature. In this research, eco-friendly plastic was formulated by blending Polylactic Acid (PLA) and Polycaprolactone (PCL) with the incorporation of chitosan as a filler. The primary objective of this study is to scrutinize and delineate the influence of varying compositions of PLA/PCL/chitosan on the mechanical attributes of eco-friendly plastics. This was achieved through hot pressing methods at a temperature of 200°C for a duration of 1 hour. The composition ratios for PLA/PCL were set at 2/8 g, 3/7 g, 5/5 g, 7/3 g, and 8/2 g, while chitosan compositions ranged from 0.2 g to 0.6 g. Comprehensive assessment of the eco-friendly plastics involved biodegradability tests, tensile strength measurements, elongation evaluations, functional group analyses, and examination of plastic film morphology. Optimal performance, ascertained through characterization, was achieved with a composition of PLA/PCL/Chitosan at 8/2/0.6 g, yielding a 38.8% degradation rate, a tensile strength of 42.53 MPa with a composition of PLA/PCL/Chitosan at 8/2/0.4 g, and an elongation of 6.96% with a composition of PLA/PCL/Chitosan at 8/2/0.2 g. The functional groups identified included N-H, C-H, C=O, and C-O groups, indicating a blending process without the formation of new functional groups. Morphology testing revealed a smooth surface, although some undissolved chitosan particles were evident, likely due to non-uniform blending.

Does a blended learning implementation package enhance HIV index case testing in Malawi? A protocol for a cluster randomised controlled trial

IntroductionIndex case testing (ICT) is an evidence-based approach that efficiently identifies persons in need of HIV treatment and prevention services. In Malawi, delivery of ICT has faced challenges due to...

Investigation on mechanical, electrical and morphological of high-density polyethylene (HDPE) reinforced with different particle size and composition of graphene nanoplatelets (GNP)

Graphene nanoplatelets (GNP) are just one of the attractive graphene-based nanomaterials that are rapidly emerging and have sparked the interest of many industries. These small stacks of platelet-shaped graphene sheets have a unique size and morphology that quickly disperse into other materials such as polymers, resulting in higher-value composite materials with improved thermal, conductivity, and mechanical capabilities. A detailed analysis of reinforced High-Density Polyethylene (HDPE) using different sizes (2, 15, 25 µm) and compositions (8, 10, 15 wt.%) of Graphene Nanoplatelets (GNP) has been conducted. The microstructure of the HDPE/GNP nanocomposites was extensively examined during the melt blending and injection moulding processes. Based on the results, the nanocomposites with different sizes of GNP exhibited dissimilar behaviour with different compositions. Furthermore, scanning electron microscope (SEM) results indicated a homogeneous dispersion for GNP in melt mixing. Moreover, thermogravimetric (TG) data demonstrate that increasing filler showed a slight increase in the material's thermal stability. The use of GNP improved mechanical properties, as evidenced by the increases in Young's modulus of yield strength from around 100 MPa to over 400 MPa. This study provides a practical reference for the industrial preparation of polymer-based graphene nanocomposites.

Nursing Undergraduate Students' Experiences and Perceptions of Blended Learning in Pediatric Nursing: A Mixed Methods Study.

Blended learning is a teaching approach that integrates online self-learning and classroom teaching. It emphasizes students' self-directed learning, actively engaging, as well as communication and collaboration. Blended learning develops the qualities in nursing undergraduate students with problem-solving ability, clinical thinking, and communication skills as nurses have. Currently, learners' experience has become an important factor in determining the success of blended learning. To learn about the experiences and perceptions of undergraduate nursing students regarding blending learning in pediatric nursing. A mixed methods design beginning with a quantitative data collection and analysis phase to inform the subsequent qualitative phase was utilized. This study was conducted among undergraduate nursing students at one university in China. In the quantitative study phase, a convenience sample of 59 students completed the online survey while the qualitative study phase included nine students recruited by purposive sampling. The qualitative data were collected using individual semistructured in-depth interviews. Audio data were transcribed and subjected to thematic analysis. The findings from those two phases were integrated into the final analysis. The majority (89.8%) of students reported satisfaction with blended learning. Among various teaching methods, case-based learning (CBL) was the most preferred (98.3%). Regarding the qualitative data, students reported positive experiences with blended learning including well-organized course structure, resourceful course content, and high teacher quality. They stated that blended learning improved the learning outcomes such as improving problem-solving ability and developing clinical thinking. They also provided suggestions for achieving better learning outcomes, including providing stressful learning activities, optimizing online course design, and improving the quality of group learning. The blended learning model of pediatric nursing based on the Community of Inquiry framework provides a positive learning experience for nursing undergraduate students. However, ongoing assessment and improvement of the blended learning process are also needed.

Escalating the use of jute (Robi-1)-cotton blended yarn rather than entirely made of cotton yarn

The process of blending involves the mixing of two different fibers to achieve the desired percentage. Various compositions, lengths, diameters, or colors may be intermingling to produce a blended yarn in a ring spinning system. This system entails the combination of different fibers lots into a homogeneous mass before spinning the mass into a staple fiber yarn. Typically, BJRI Tossa Pat-8 (Robi-1) and cotton fibers are combined to create jute-cotton blended yarn. Jute can be utilized in various ways, which is one approach to blending yarn. The jute-cotton blended yarn was produced in a ratio of 30% and 70%. Both jute-cotton blended yarn and totally cotton yarn were produced on a cotton spinning line using a ring frame. The physical characteristics of both yarns, such as count, yarn Lea strength, and CSP were measured. The average count of fully cotton yarn and jute-cotton blended yarn was found to be roughly equal at 12.16 and 11.82, respectively. However, the yarn lea strength and CSP of both samples, which are significantly different from one another, were 232 lb, 140 lb, and 2835, 1670, respectively. Along with entirely made of yarn, blended yarn also exhibits consistency in terms of CV%, SD, and PMD. This study compared the physical characteristics of both yarns after Robi-1 was first introduced for the blending process with cotton to produce a jute-cotton blended yarn.