Prediction of Junior High School Students' Problematic Internet Use: The Comparison of Neural Network Models and Linear Mixed Models in Longitudinal Study

Purpose

With the rise of big data, deep learning neural networks have garnered attention from psychology researchers due to their ability to process vast amounts of data and achieve superior model fitting. We aim to explore the predictive accuracy of neural network models and linear mixed models in tracking data when subjective variables are predominant in the field of psychology. We separately analyzed the predictive accuracy of both models and conduct a comparative study to further investigate. Simultaneously, we utilized the neural network model to examine the influencing factors of problematic internet usage and its temporal changes, attempting to provide insights for early interventions in problematic internet use.

Patients and Methods

This study compared longitudinal data of junior high school students using both a linear mixed model and a neural network model to ascertain the efficacy of these two methods in processing psychological longitudinal data.

Results

The neural network model exhibited significantly smaller errors compared to the linear mixed model. Furthermore, the outcomes from the neural network model revealed that, when analyzing data from a single time point, the influences of seventh grade better predicted Problematic Internet Use in ninth grade. And when analyzing data from multiple time points, the influences of sixth, seventh, and eighth grades more accurately predicted Problematic Internet Use in ninth grade.

Conclusion

Neural network models surpass linear mixed models in precision when predicting and analyzing longitudinal data. Furthermore, the influencing factors in lower grades provide more accurate predictions of Problematic Internet Use in higher grades. The highest prediction accuracy is attained through the utilization of data from multiple time points.

Progress and Prospects in Metallic FexGeTe2 (3 ≤ x ≤ 7) Ferromagnets

Thermal fluctuations in two-dimensional (2D) isotropy systems at non-zero finite temperatures can destroy the long-range (LR) magnetic order due to the mechanisms addressed in the Mermin-Wanger theory. However, the magnetic anisotropy related to spin-orbit coupling (SOC) may stabilize magnetic order in 2D systems. Very recently, 2D FexGeTe2 (3 ≤ x ≤ 7) with a high Curie temperature (TC) has not only undergone significant developments in terms of synthetic methods and the control of ferromagnetism (FM), but is also being actively explored for applications in various devices. In this review, we introduce six experimental methods, ten ferromagnetic modulation strategies, and four spintronic devices for 2D FexGeTe2 materials. In summary, we outline the challenges and potential research directions in this field.

Bi/Mn-Doped BiOCl Nanosheets Self-Assembled Microspheres toward Optimized Photocatalytic Performance

Doping engineering of metallic elements is of significant importance in photocatalysis, especially in the transition element range where metals possess empty 'd' orbitals that readily absorb electrons and increase carrier concentration. The doping of Mn ions produces dipole interactions that change the local structure of BiOCl, thus increasing the specific surface area of BiOCl and the number of mesoporous distributions, and providing a broader platform and richer surface active sites for catalytic reactions. The combination of Mn doping and metal Bi reduces the forbidden bandwidth of BiOCl, thereby increasing the absorption in the light region and strengthening the photocatalytic ability of BiOCl. The degradation of norfloxacin by Bi/Mn-doped BiOCl can reach 86.5% within 10 min. The synergistic effect of Mn doping and Bi metal can change the internal energy level and increase light absorption simultaneously. The photocatalytic system created by such a dual-technology combination has promising applications in environmental remediation.

Strain Engineering of Intrinsic Ferromagnetism in 2D van der Waals Materials

Since the discovery of the low-temperature, long-range ferromagnetic order in monolayers Cr2Ge2Te6 and CrI3, many efforts have been made to achieve a room temperature (RT) ferromagnet. The outstanding deformation ability of two-dimensional (2D) materials provides an exciting way to mediate their intrinsic ferromagnetism (FM) with strain engineering. Here, we summarize the recent progress of strain engineering of intrinsic FM in 2D van der Waals materials. First, we introduce how to explain the strain-mediated intrinsic FM on Cr-based and Fe-based 2D van der Waals materials through ab initio Density functional theory (DFT), and how to calculate magnetic anisotropy energy (MAE) and Curie temperature (TC) from the interlayer exchange coupling J. Subsequently, we focus on numerous attempts to apply strain to 2D materials in experiments, including wrinkle-induced strain, flexible substrate bending or stretching, lattice mismatch, electrostatic force and field-cooling. Last, we emphasize that this field is still in early stages, and there are many challenges that need to be overcome. More importantly, strengthening the guideline of strain-mediated FM in 2D van der Waals materials will promote the development of spintronics and straintronics.

The Progress on Magnetic Material Thin Films Prepared Using Polymer-Assisted Deposition

Polymer-assisted deposition (PAD) has been widely used in the preparation of high-quality oxides and sulfides for basic research and applications. Specifically, diverse PAD-prepared magnetic material thin films such as ZnO, Ga₂O₃, SrRuO₃, LaCoO₃, LaMnO₃, Y₃Fe₅O₁₂, MoS₂, MoSe₂, and ReS₂ thin films have been grown, in which thickness-dependent, strain-modulated, doping-mediated, and/or morphology-dependent room-temperature ferromagnetism (RTFM) have been explored. Inspired by the discovery of intrinsic low-temperature FM in two-dimensional (2D) systems prepared using mechanical exfoliation, the search for more convenient methods to prepare 2D ferromagnetic materials with high-temperature FM has seen explosive growth, but with little success. Fortunately, the very recent synthesis of 2D NiO by PAD has shed light on this challenge. Based on these abovementioned developments, the difficulties of PAD when preparing a-few-nanometer single-crystalline materials and the opportunities in PAD for novel materials such as chiral magnetic soliton material Cr_1/3NbS₂ are discussed.

Recycling of biogenic hydroxyapatite (HAP) for cleaning of lead from wastewater: performance and mechanism

In China, the utilization and recycling of chicken waste have become a significant environmental issue. In this study, we investigate the efficacy of biogenic hydroxyapatite (HAP) materials, recycled from chicken waste, for Pb(II) sequestration from wastewater. The results from batch experiments indicate that biogenic HAP could effectively remove Pb(II) from an aqueous solution. The maximum removal efficiency of Pb (more than > 99%) was observed under the following operational conditions: initial pH of 3.0, initial Pb(II) concentrations of 208 mg/L, and 1 g/L of HAP adsorbents. The presence of coexisting divalent ions, including Ca2+, Mg2+, and Mn2+, had no significant influence on Pb(II) removal. Spectroscopic analysis suggests that the dissolution-precipitation mechanism was mainly responsible for Pb(II) sequestration under acidic conditions (pH ≤ 3.0). Our findings indicate that biogenic HAP recycled from biowaste can be used as an efficient adsorbent for cleaning Pb(II) from wastewater.