Does the experimental set affect TOEFL iBT reading performance?

This study investigates whether including an experimental set and test takers being aware of it influences TOEFL iBT reading performance. Before going into the experiment, the existence and the purpose of the experimental set is established based on several grounds. To discover a certain item or test functioning differently (DIF) in favor of some test takers or test layout that is meant to be comparable, the concepts of the Mantel-Haenszel procedure (Mantel and Haenszel, 1959) is borrowed. Test scores of participants who are designated into the reference group, focal group 1, and focal group 2 were compared but statistically revealed little regarding the effect of the experimental set. The qualitative approach taken after the test, however, exposed some critical issues related to fairness, performance, and ethics. Along with discussions, some implicit and improvable limitations finally conclude the paper

Insulin Secretion and Incretin Hormone Concentration in Women with Previous Gestational Diabetes Mellitus

BackgroundWe examined the change in the levels of incretin hormone and effects of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) on insulin secretion in women with previous gestational diabetes (pGDM).MethodsA 75-g oral glucose tolerance test (OGTT) was conducted on 34 women with pGDM. In addition, 11 women with normal glucose tolerance, matched for age, height and weight, were also tested. The insulin, GIP, GLP-1, and glucagon concentrations were measured, and their anthropometric and biochemical markers were also measured.ResultsAmong 34 women with pGDM, 18 had normal glucose tolerance, 13 had impaired glucose tolerance (IGT) and 1 had diabetes. No significant differences were found in GLP-1 concentration between the pGDM and control group. However, a significantly high level of glucagon was present in the pGDM group at 30 minutes into the OGTT. The GIP concentration was elevated at 30 minutes and 60 minutes in the pGDM group. With the exception of the 30-minute timepoint, women with IGT had significantly high blood glucose from 0 to 120 minutes. However, there was no significant difference in insulin or GLP-1 concentration. The GIP level was significantly high from 0 to 90 minutes in patients diagnosed with IGT.ConclusionGLP-1 secretion does not differ between pGDM patients and normal women. GIP was elevated, but that does not seem to induce in increase in insulin secretion. Therefore, we conclude that other factors such as heredity and environment play important roles in the development of type 2 diabetes

Ultrastrong Light-Matter Coupling in 2D Metal-Chalcogenates

Hybridization of excitons with photons to form hybrid quasiparticles, exciton-polaritons (EPs), has been widely investigated in a range of semiconductor material systems coupled to photonic cavities. Self-hybridization occurs when the semiconductor itself can serve as the photonic cavity medium resulting in strongly-coupled EPs with Rabi splitting energies > 200 meV at room temperatures which recently were observed in layered two-dimensional (2D) excitonic materials. Here, we report an extreme version of this phenomenon, an ultrastrong EP coupling, in a nascent, 2D excitonic system, the metal organic chalcogenate (MOCHA) compound named mithrene. The resulting self-hybridized EPs in mithrene crystals placed on Au substrates show Rabi Splitting in the ultrastrong coupling range (> 600 meV) due to the strong oscillator strength of the excitons concurrent with the large refractive indices of mithrene. We further show bright EP emission at room temperature as well as EP dispersions at low-temperatures. Importantly, we find lower EP emission linewidth narrowing to ~1 nm when mithrene crystals are placed in closed Fabry-Perot cavities. Our results suggest that MOCHA materials are ideal for polaritonics in the deep green-blue part of the spectrum where strong excitonic materials with large optical constants are notably scarce

Development of suction pipe design criterion to secure oil return to compressor

In the present work, phenomena associated with counter current flow limitation (CCFL) were experimentally investigated using small diameter tubes in order to suggest criterion for which the oil return is secured. The test section is made of Pyrex glass tube to allow visual observation. The inner diameter of the test tube is 7mm and the height is 1m. The inclination of test tubes varied from vertical to crank type with various horizontal lengths. Waterair flow and lubricant oil-air flow were examined through a series of experiment at various liquid flow rates. In this experimental study, flow reversal and flooding phenomena were visually observed and two-phase flow rate were measured. Flow reversal point represents the air flow rate when the liquid film begins to flow downwards in the tube below the liquid inlet location. Whole supplied liquid flows upward when the gas flow rate is larger than this value. So the flow reversal point can be interpreted as oil return criterion and the flow reversal points were measured using various shape of test section in a wide range of liquid flow rate. The gas velocities for the flow reversal point appeared to be similar over a certain range of liquid flow rate. Flooding point was defined as the air flow rate when liquid starts to flow above the liquid inlet part. The air flow rate needed to cause flooding is inversely proportional to the liquid flow rate. Both flow reversal and flooding velocity also depend on the inclination angle, horizontal length and liquid property

Multi-Stage Approach Using Convolutional Triplet Network and Ensemble Model for Fault Diagnosis in Oil Plant Rotary Machines

Ensuring the operational safety and reliability of rotary machinery systems, especially in oil plants, has become a focal point in both academic and industry arenas. Specifically, in terms of key rotary machinery components such as shafts, the diagnosis of these systems is paramount for achieving enhanced generalization capabilities in fault diagnosis, encompassing multiple sensor-derived variables with their respective fault patterns. This study introduces a multi-stage approach to generalize capabilities for fault diagnosis that considers multiple sensor-derived variables and their fault patterns. This method combines the Convolutional Triplet Network for feature extraction with an ensemble model for fault classification. Initially, vibration signals are processed to yield the most representative temporal and spatial features. Then, an ensemble approach is used to maximize both diversity and accuracy by balancing the contributions of the individual classifiers. The approach can detect three representative types of shaft faults more accurately than traditional single-stage machine learning models. Comprehensive experiments, detailed within, showcase the method’s efficacy in diagnosing rotary machine faults across diverse operational scenarios