The Effects of "Flipped Classroom" Concept on the Effectiveness of Teaching

A lesson study project is carried out to examine various teaching methodologies on the students’ learning through support from the Office of Professional and Instructional Development (OPID) of University of Wisconsin System. The study involves a diverse body of faculty and students affiliated with three different programs on campus. One of the methodologies of interest is the “flipped classroom” concept in the teaching community. In this work, flipped classroom activities are conducted in teaching one engineering and technology course titled with “Fundamentals of Plastics Materials and Processing” (MFGT‐251). Particularly, the concept is incorporated in two series of lectures on injection molding, blow molding and thermoforming. Student’s performance is evaluated through laboratory assignments, quizzes, and exams. Results on students’ learning and the feedbacks from the students are presented. The implication of the results will also be discussed

Preparation of Redispersible Chitin Nanofibers and Its Application in Stabilizing Pickering Emulsion

Chitin nanofibers (ChNFs) with both amino and carboxyl groups were obtained by carboxymethylation of partially deacetylated chitin (DE-chitin) with chloroacetic acid. ChNFs could be dispersed again in deionized water after drying and removing the dispersing medium. The aspect ratio of ChNFs had little change before and after dispersion. Further, ChNFs could effectively stabilize oil-in-water (O/W) Pickering emulsions. The emulsion (comprising 10% oil) stabilized with ChNFs at concentrations greater than 0.5% was stabile for 90 days. In addition, ChNFs could stabilize the emulsion in a wide pH range (3–11). Overall, ChNFs is expected to be used as a novel Pickering stabilizer to protect and deliver pH-sensitive active substances in the field of food biology

A clinical study of the effects of lead poisoning on the intelligence and neurobehavioral abilities of children

BACKGROUND: Lead is a heavy metal and important environmental toxicant and nerve poison that can destruction many functions of the nervous system. Lead poisoning is a medical condition caused by increased levels of lead in the body. Lead interferes with a variety of body processes and is toxic to many organs and issues, including the central nervous system. It interferes with the development of the nervous system, and is therefore particularly toxic to children, causing potentially permanent neural and cognitive impairments. In this study, we investigated the relationship between lead poisoning and the intellectual and neurobehavioral capabilities of children. METHODS: The background characteristics of the research subjects were collected by questionnaire survey. Blood lead levels were detected by differential potentiometric stripping analysis (DPSA). Intelligence was assessed using the Gesell Developmental Scale. The Achenbach Child Behavior Checklist (CBCL) was used to evaluate each child’s behavior. RESULTS: Blood lead levels were significantly negatively correlated with the developmental quotients of adaptive behavior, gross motor performance, fine motor performance, language development, and individual social behavior (P < 0.01). Compared with healthy children, more children with lead poisoning had abnormal behaviors, especially social withdrawal, depression, and atypical body movements, aggressions and destruction. CONCLUSION: Lead poisoning has adverse effects on the behavior and mental development of 2–4-year-old children, prescribing positive and effective precautionary measures

The Effect of Cardiac Rehabilitation on Lipid Levels in Patients with Coronary Heart Disease. A Systematic Review and Meta-Analysis

Background: Cardiac rehabilitation (CR) is a multidisciplinary medical program. Most studies have emphasized the effect of exercise-based CR in lowering lipid levels; however, the effect of CR as a comprehensive program on lipid levels remains unclear. Methods: Electronic database were searched up to 2022. Randomized controlled trials with lipid profile indicators were included. Standardized mean differences (SMDs) and 95% CIs were used to evaluate the effect size. Begg’s funnel plot and Egger’s linear regression test were used to assess publication bias. Results: CR remarkably reduced low-density lipoprotein cholesterol (LDL-C) levels (SMD = –0.23; 95%CI: [–0.38, –0.08]; P < 0.001), triglyceride (TG) levels (SMD = –0.17; 95%CI: [–0.28, –0.06]; P < 0.001), and total cholesterol (TC) levels (SMD = –0.30; 95%CI: [–0.43, –0.16]; P < 0.001) and increased high-density lipoprotein cholesterol (HDL-C) levels (SMD = 0.19; 95%CI: [0.10, 0.29]; P < 0.001). Conclusions: CR reduce TC, TG, and LDL-C levels while improving HDL-C levels. CR should be promoted and more trials should be conducted for long-term CR

High Internal Phase Pickering Emulsion Stabilized by Natural Biomacromolecules and Its Application in Foods

In recent years, high internal phase Pickering emulsions (HIPPEs) has attracted much attention due to its unique organizational properties and has a wide application prospect in the food field. Natural biomacromolecules, active components in organisms, possess good biocompatibility, degradability, no or low toxic effects, which are excellent stabilizers for HIPPEs. In this paper, the potential of natural biomacromolecules to stabilize HIPPEs and recent progress on the application of biopolymer-stabilized HIPPEs in the inhibition of lipid oxidation, as a substitute for trans fatty acids, and in the encapsulation and delivery of nutrients, the 3D printing of foods and encapsulation of probiotics are briefly reviewed in order to provide a reference for the application of HIPPEs stabilized by natural biomacromolecules in foods

TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems

Root Cause Analysis (RCA) is becoming increasingly crucial for ensuring the reliability of microservice systems. However, performing RCA on modern microservice systems can be challenging due to their large scale, as they usually comprise hundreds of components, leading significant human effort. This paper proposes TraceDiag, an end-to-end RCA framework that addresses the challenges for large-scale microservice systems. It leverages reinforcement learning to learn a pruning policy for the service dependency graph to automatically eliminates redundant components, thereby significantly improving the RCA efficiency. The learned pruning policy is interpretable and fully adaptive to new RCA instances. With the pruned graph, a causal-based method can be executed with high accuracy and efficiency. The proposed TraceDiag framework is evaluated on real data traces collected from the Microsoft Exchange system, and demonstrates superior performance compared to state-of-the-art RCA approaches. Notably, TraceDiag has been integrated as a critical component in the Microsoft M365 Exchange, resulting in a significant improvement in the system's reliability and a considerable reduction in the human effort required for RCA