The Relation between Teacher Gender and Student Academic Achievements: From the Perspective of Teacher-student Gender Matches

According to existing research findings, there is a significant gender difference in student academic performance at the basic education level, with girls outperforming boys on average. Student educational attainments are affected by multiple factors. Among all school-related factors, teachers have been viewed as the most impactful in student academic progress. In China, female teachers predominate in the basic education teacher staff. Therefore, the investigation of how teacher-student gender matches impact student academic performance is of theoretical and practical significance

A mechanistic model of a PWR-based nuclear power plant in response to external hazard-induced station blackout accidents

Natural hazard-induced nuclear accidents, such as the Fukushima Daiichi Accident that occurred in Japan in 2011, have significantly increased reactor safety studies in understanding nuclear power plant (NPP) responses to external hazard events such as earthquakes and floods. Natural hazards could cause the loss of offsite power in nuclear power plants, potentially leading to a Station Blackout (SBO) accident that significantly contributes to the overall risk of nuclear power plant accidents. Despite the fact that extensive research has been conducted on the station blackout accident for nuclear power plant, further understanding of these events is needed, particularly in the context of the dynamic nature of external hazards such as external flooding. This paper estimates the progression of station blackout events for a generic pressurized water reactor (PWR) in response to external flooding events. The original RELAP5-3D model of the Westinghouse four-loop design pressurized water reactor was adopted and modified to simulate the external flood-induced station blackout accident, including the short-term and long-term station blackout scenarios. A sensitivity analysis of long-term station blackout, examining reactor operation times and analyzing key parameters over time, was also conducted in this work. The results of the analyses, especially the critical timing parameters of key event sequences, provide useful insights about the time during the external flooding event, which is important for plant operators to make timely decisions to prevent potential core damage. This paper represents significant progress toward developing an integrated risk assessment framework for further identifying and assessing the effects of the critical sources of uncertainties of nuclear power plant under external hazard-induced events

Modeling the protein binding non-linearity in population pharmacokinetic model of valproic acid in children with epilepsy: a systematic evaluation study

Background: Several studies have investigated the population pharmacokinetics (popPK) of valproic acid (VPA) in children with epilepsy. However, the predictive performance of these models in the extrapolation to other clinical environments has not been studied. Hence, this study evaluated the predictive abilities of pediatric popPK models of VPA and identified the potential effects of protein binding modeling strategies.Methods: A dataset of 255 trough concentrations in 202 children with epilepsy was analyzed to assess the predictive performance of qualified models, following literature review. The evaluation of external predictive ability was conducted by prediction- and simulation-based diagnostics as well as Bayesian forecasting. Furthermore, five popPK models with different protein binding modeling strategies were developed to investigate the discrepancy among the one-binding site model, Langmuir equation, dose-dependent maximum effect model, linear non-saturable binding equation and the simple exponent model on model predictive ability.Results: Ten popPK models were identified in the literature. Co-medication, body weight, daily dose, and age were the four most commonly involved covariates influencing VPA clearance. The model proposed by Serrano et al. showed the best performance with a median prediction error (MDPE) of 1.40%, median absolute prediction error (MAPE) of 17.38%, and percentages of PE within 20% (F20, 55.69%) and 30% (F30, 76.47%). However, all models performed inadequately in terms of the simulation-based normalized prediction distribution error, indicating unsatisfactory normality. Bayesian forecasting enhanced predictive performance, as prior observations were available. More prior observations are needed for model predictability to reach a stable state. The linear non-saturable binding equation had a higher predictive value than other protein binding models.Conclusion: The predictive abilities of most popPK models of VPA in children with epilepsy were unsatisfactory. The linear non-saturable binding equation is more suitable for modeling non-linearity. Moreover, Bayesian forecasting with prior observations improved model fitness

15.34% efficiency all-small-molecule organic solar cells with an improved fill factor enabled by a fullerene additive

Solution processed organic solar cells (OSCs) composed of all small molecules (ASM) are promising for production on an industrial scale owing to the properties of small molecules, such as well-defined chemical structures, high purity of materials, and outstanding repeatability from batch to batch synthesis. Remarkably, ASM OSCs with power conversion efficiency (PCE) beyond 13% were achieved by structure improvement of the electron donor and choosingY6as the electron acceptor. However, the fill factor (FF) is an obstacle that limits the further improvement of the PCE for these ASM OSCs. Herein, we focus on the FF improvement of recently reported ASM OSCs withBTR-Cl:Y6as the active layer by miscibility-induced active layer morphology optimization. The incorporation of fullerene derivatives, which have good miscibility with bothBTR-ClandY6, results in reduced bimolecular recombination and thus improved FF. In particular, whenca.5 wt% ofPC(71)BMwas added in the active layer, a FF of 77.11% was achieved without sacrificing the open circuit voltage (V-OC) and the short circuit current density (J(SC)), leading to a record PCE of 15.34% (certified at 14.7%) for ASM OSCs. We found that the optimized device showed comparable charge extraction, longer charge carrier lifetime, and slower bimolecular recombination rate compared with those of the control devices (w/o fullerene). Our results demonstrate that the miscibility driven regulation of active layer morphology by incorporation of a fullerene derivative delicately optimizes the active layer microstructures and improves the device performance, which brings vibrancy to OSC research

A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data

To address the instability of phylogenetic trees in morphological datasets caused by missing values, we present a phylogenetic inference method based on a concept decision tree (CDT) in conjunction with attribute reduction. First, a reliable initial phylogenetic seed tree is created using a few species with relatively complete morphological information by using biologists’ prior knowledge or by applying existing tools such as MrBayes. Second, using a top-down data processing approach, we construct concept-sample templates by performing attribute reduction at each node in the initial phylogenetic seed tree. In this way, each node is turned into a decision point with multiple concept-sample templates, providing decision-making functions for grafting. Third, we apply a novel matching algorithm to evaluate the degree of similarity between the species’ attributes and their concept-sample templates and to determine the location of the species in the initial phylogenetic seed tree. In this manner, the phylogenetic tree is established step by step. We apply our algorithm to several datasets and compare it with the maximum parsimony, maximum likelihood, and Bayesian inference methods using the two evaluation criteria of accuracy and stability. The experimental results indicate that as the proportion of missing data increases, the accuracy of the CDT method remains at 86.5%, outperforming all other methods and producing a reliable phylogenetic tree

The Effect of Migrant Students on Local Students' Academic Performance

Whether the aggregation of migrant students in schools will affect the academic development of local students is a valuable and practical problem. Based on the survey data of grade 9 students collected by CEPS2013-2014 (China Education Panel Survey) and the balance test, this article simulated scenario of random class-division within the same school by adding the fixed effect and deleting samples of non-random class-division, estimated the effect of the proportion of migrant students on the academic performance of local students

Tetrahedron-Based Porous Scaffold Design for 3D Printing

Tissue repairing has been the ultimate goal of surgery, especially with the emergence of reconstructive medicine. A large amount of research devoted to exploring innovative porous scaffold designs, including homogeneous and inhomogeneous ones, have been presented in the literature. The triply periodic minimal surface has been a versatile source of biomorphic structure design due to its smooth surface and high interconnectivity. Nonetheless, many 3D models are often rendered in the form of triangular meshes for its efficiency and convenience. The requirement of regular hexahedral meshes then becomes one of limitations of the triply periodic minimal surface method. In this paper, we make a successful attempt to generate microscopic pore structures using tetrahedral implicit surfaces. To replace the conventional Cartesian coordinates, a new coordinates system is built based on the perpendicular distances between a point and the tetrahedral faces to capture the periodicity of a tetrahedral implicit surface. Similarly to the triply periodic minimal surface, a variety of tetrahedral implicit surfaces, including P-, D-, and G-surfaces are defined by combinations of trigonometric functions. We further compare triply periodic minimal surfaces with tetrahedral implicit surfaces in terms of shape, porosity, and mean curvature to discuss the similarities and differences of the two surfaces. An example of femur scaffold construction is provided to demonstrate the detailed process of modeling porous architectures using the tetrahedral implicit surface