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Internet addiction and mobile phone addiction are both forms of technology addiction, and thus would be expected to show similarities and differences. This study investigated the association between the Internet Addiction Test (IAT) and the Mobile Phone Dependence Questionnaire (MPDQ) as a test of concurrent validity. Participants were 1,072 students aged between 9 and 18 years old (63% male and 37% female) from three primary schools and three secondary schools in Hong Kong. Correlations showed that scores on the two measures were moderately correlated, providing further evidence of each measure's validity. Confirmatory factor analysis that the IAT's factor structure was similar in both younger and older samples, suggesting that it is developmentally appropriate for primary and secondary school students. Latent Class Analysis showed that 4 classes or 5 classes are appropriate for IAT's score classification. ROC analyses showed similar rates of participants with high scores on the IAT and on the MPDQ. The outcomes have implications for the prevention and treatment of Internet and mobile phone addiction. Future research can establish norms for different ages, genders and cultural groups.

Background Mobile phone dependence (MPD) is a serious public health concern in schools. To advance cross-cultural understanding of MPD, this study examined factor structure, measurement invariance, and latent mean differences of the mobile phone dependence questionnaire (MPDQ) across mainland Chinese and Hong Kong adolescents. Methods The present cross-sectional study included a total of 918 middle school students (588 boys and 310 girls; M age  = 13.58, SD  = 1.46), comprising 367 adolescents from two Shenzhen schools and 551 adolescents from three Hong Kong schools. Confirmatory factor analysis, measurement invariance test, latent mean comparisons, and multidimensional item response theory analysis were employed for data analyses. Results The three-factor structure of the MPDQ, proposed by previous research conducted in Hong Kong adolescents, was also supported in mainland Chinese adolescents. Configural, partial metric, and partial scalar cross-cultural measurement invariance were all achieved. Mainland Chinese adolescents reported higher scores on all MPD factors than their Hong Kong counterparts. Conclusions The findings highlight the cross-cultural similarities and differences of MPD among adolescents in mainland China and Hong Kong. The MPDQ is culturally sensitive to measure MPD in both regions, while certain items may need further cultural adaptation. Moreover, Hong Kong adolescents demonstrated more disordered thoughts and behaviors associated with MPD than mainland Chinese adolescents. Implications for using the MPDQ for assessing and understanding the MPD from diverse cultural backgrounds are discussed. Clinical trial number Not applicable.

Miniscrews are used in orthodontic treatment and can be applied immediately after implantation, making their initial stability crucial. However, clinical reports show that the success rate is not 100%, and many researchers have tried to identify the factors influencing success and optimize designs. A review of the literature reveals that studies on the same geometric parameter of miniscrews using different indicators and different brand samples have led to conflicting results. This study will use consistent miniscrew conditions to verify whether the design differences in the literature are reasonable. This study employs the Taguchi method and ANOVA for optimization analysis. The four control factors comprise thread pitch, thread depth, tip taper angle, and self-tapping notch. Using an L9(34) orthogonal array, the experimental models are reduced to nine. The primary stability indicators for the miniscrew include bending strength, pull-out strength, insertion torque, and self-tapping performance. The results of the single-objective experiments in this study align with the findings from the other literature. However, when analyzed collectively, they do not yield the same optimal solution. Under equal weighting, the combined multi-objective optimal solution is A2B2C1D1. This study exhibits minimal experimental error, ensuring high analytical reliability. The findings confirm that the optimal design does not converge across four single-objective analyses, as different stability indicators yield contradictory trends in design parameters. Given that these four indicators already demonstrate notable discrepancies, the influence of additional stability factors would be even more pronounced. Therefore, a multi-objective optimization approach is essential for the rational design of miniscrews.

The transplantation of CD34 + hematopoietic stem-progenitor cells (HSPCs) derived from cord blood serves as the standard treatment for selected hematological, oncological, metabolic, and immunodeficiency disorders, of which the dose is pivotal to the clinical outcome. Based on numerous maternal and neonatal parameters, we evaluated the predictive power of mathematical pipelines to the proportion of CD34 + cells in the final cryopreserved cord blood product adopting both parametric and non-parametric algorithms. Twenty-four predictor variables associated with the cord blood processing of 802 processed cord blood units randomly sampled in 2020–2022 were retrieved and analyzed. Prediction models were developed by adopting the parametric (multivariate linear regression) and non-parametric (random forest and back propagation neural network) statistical models to investigate the data patterns for determining the single outcome (i.e., the proportion of CD34 + cells). The multivariate linear regression model produced the lowest root-mean-square deviation (0.0982). However, the model created by the back propagation neural network produced the highest median absolute deviation (0.0689) and predictive power (56.99%) in comparison to the random forest and multivariate linear regression. The predictive model depending on a combination of continuous and discrete maternal with neonatal parameters associated with cord blood processing can predict the CD34 + dose in the final product for clinical utilization. The back propagation neural network algorithm produces a model with the highest predictive power which can be widely applied to assisting cell banks for optimal cord blood unit selection to ensure the highest chance of transplantation success.

FEA of orthodontic miniscrews has predominantly assumed isotropic, homogeneous bone, neglecting directional variations in mechanical properties. This study investigated the biomechanical behavior of miniscrews under different insertion angles and loading directions using both isotropic and orthotropic mandibular bone models. The results indicated that isotropic modeling may underestimate miniscrew displacement and associated instability, whereas orthotropic material properties better reflect the true mechanical response of bone. Oblique insertion at 60° (U60°) led to higher strain and greater variability, which may compromise osseointegration; aligning the loading direction parallel to the insertion plane is therefore recommended when oblique placement is unavoidable. Screw thread design had minimal influence on displacement, von Mises stress, or bone strain during vertical insertion. Stress and strain distributions exhibited symmetry, suggesting that analyzing partial loading directions can predict the overall biomechanical response. All predicted values remained below bone and material strength limits, confirming the mechanical safety of the current miniscrew design under a 2 N load. Implant failure is likely attributable to poor osseointegration or inflammation rather than structural limitations.

BackgroundFragmentation and habitat loss can restrict species movement and reduce connectivity, negatively impacting biodiversity. Characterising the overall connectivity of an area can inform better management of human modified landscapes. Contemporary connectivity modelling methods seldom incorporate fine-scale movement patterns associated with movement between fine-scaled structural connectivity elements such as scattered trees, roadside corridors and small patches of habitat. This study aims to characterise connectivity within the Karuah-Myall catchments, a typical woodland ecosystem that is fragmented by agriculture, using least-cost path analysis and a graph-theoretic approach; it focuses on how fine-scaled vegetation such as scattered trees support connectivity. We mapped scattered (and paddock) trees within this agricultural landscape where the main human modified land use was pasture. We modelled connectivity for a general representative woodland species using an interpatch dispersal distance and gap crossing threshold, and resistance from different land cover types. The gap crossing distance threshold was used to model movement between fine-scaled vegetation features. We compared the least-cost paths modelled with and without scattered trees.ResultsOur results show that by excluding scattered trees, least-cost paths across the cleared pasture landscape did not reflect the types of movement patterns typically observed from field studies, such as those associated with a foray-search strategy used by small and medium mammals and birds. The modelling also shows that the Karuah-Myall catchments are well connected and provide value to biodiversity beyond the catchment borders, by connecting coastal vegetation to the Great Eastern Ranges national wildlife corridor initiative.ConclusionConnectivity models that exclude fine-scale landscape features such as scattered trees and small, linear patches risk misrepresenting connectivity patterns. Models of regional-scale connectivity can be influenced by the presence or absence of even the smallest features, such as scattered trees.

To cut the cost of the laser powder bed fusion (LPBF) process, which is much higher than that of the traditional manufacturing process, an effective implementation of optimization analysis is needed. The study investigated the optimization of the LPBF Inconel 718 alloy with the Taguchi method and principal component analysis (PCA), covering four control factors at three levels in the manufacturing process. It focused on four mechanical properties, namely tensile strength, elongation, impact energy, and hardness. The results show that the highest tensile strength is obtainable at a laser power of 140 W, scanning speed of 800 mm/s, scanning pitch of 70 μm, and interlayer angle of 45 degrees. The optimal combination of process parameters for multiobjective optimization is just the same as that for single-objective optimization for tensile strength. The difference between the predicted and experimental average tensile strength is 1.2%, and the error of the predicted optimal strength index is 12.6%. The most important control factor for tensile strength and multiple responses is the angle between layers, with a contribution rate exceeding 90%. With a given volume energy density of the LPBF process, the higher the power and scanning speed, the higher the accumulated energy and the larger the amount of dendritic or cellular crystals formed.

Background Valid and reliable measures for assessing health activation in school-aged children are currently lacking. This study aimed to develop a scale to measure health activation and evaluate its psychometric properties among English-speaking primary school children in Singapore. Methods The development of the Health Activation Scale for Children (HAS-C) involved an extensive literature review, expert consultations, cognitive interviews with primary school children, and thorough discussions for dimension and item refinement. A cross-sectional study was conducted with 597 children aged 8 to 12 years, recruited from four mainstream primary schools, comprising 50.1% boys and 64.8% Chinese students. The potential scale, along with other measures, was independently completed by the children. Descriptive statistics were provided for individual scale items. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to assess factorial validity. Convergent validity was examined by correlating the scale scores with scores of health confidence and self-efficacy measures. Hypothesis-testing validity was evaluated by assessing the scale’s correlation with self-reported health behaviours, including daily consumption of vegetables and fruits, time spent on sedentary activities and physical activities. Internal consistency reliability was measured using Cronbach’s alpha. Results EFA suggested a three-factor structure for the 12-item HAS-C, which was subsequently confirmed by CFA with a good model fit. All three HAS-C dimension scores demonstrated moderate correlations (rho = 0.34–0.52) with health confidence and self-efficacy measures, indicating good convergent validity. They were positively correlated with more vegetable and fruit intakes, more time spent on exercises, and negatively correlated with time spent on sedentary activities, supporting hypothesis-testing validity. Internal consistency reliability for individual HAS-C dimensions was generally acceptable, with Cronbach’s alpha values of 0.70 or above. Conclusion The 12-item multi-dimensional HAS-C exhibited good validity and reliability, making it a valuable tool for assessing health activation in primary school-aged children.

This study proposes a design for unmanned chemical factories and implementation based on ultra-low-cost Internet of Things technology, to combat the impact of COVID-19 on industrial factories. A safety and private blockchain network architecture was established, including a three-layer network structure comprising edge, fog, and cloud calculators. Edge computing uses a programmable logic controller and a single-chip microcomputer to transmit and control the motion path of a four-axis robotic arm motor. The fog computing architecture is implemented using Python software. The structure is integrated and applied using a convolutional neural network (CNN) and a fractional-order proportional-integral-derivative controller (FOPID). In addition, edge computing and fog computing signals are transmitted through the blockchain, and can be directly uploaded to the cloud computing controller for signal integration. The integrated application of the production line sensor and image recognition based on the network layer was addressed. We verified the image recognition of the CNN and the robot motor signal control of the FOPID. This study proposes that a CNN + FOPID method can improve the efficiency of the factory by more than 50% compared with traditional manual operators. The low-cost, high-efficiency equipment of the new method has substantial contribution and application potential.

Remimazolam is a short‐acting benzodiazepine that was approved by the United States Food and Drug Administration (FDA) in 2020 for the induction and maintenance of procedural sedation in adults undergoing procedures lasting 30 min or less. Given its recent introduction, the use of remimazolam for general anesthesia and monitored anesthesia care (MAC) remains an area of ongoing investigation. In this report, we present the first documented case demonstrating that remimazolam can achieve hemodynamic stable burst suppression in a critically ill patient undergoing emergent craniectomy and aneurysm clipping. Additionally, this manuscript reviews the reported off‐label applications of remimazolam in both the operating room and the intensive care unit (ICU) settings.