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Abstract Low‐density lipoprotein receptor‐related protein‐1 (LRP1) is thought to be correlated with hepatocellular carcinoma (HCC) invasion and metastasis. However, the precise mechanism through which LRP1 contributes to HCC progression remains unclear. Here, lower LRP1 levels are associated with malignant progression, and poor prognosis in patients with HCC is shown. LRP1 knockdown enhances the tumorigenicity of HCC cells in vitro and in vivo, whereas overexpression of either LRP1 or its β‐chain has the opposite effect. Mechanistically, LRP1 knockdown promotes the binding of ubiquitin‐like modifier 1 ligating enzyme 1 (UFL1) to OGA and accelerates ubiquitin‐mediated OGA degradation, leading to increased O‐GlcNAcylation of nuclear factor‐kappa B (NF‐κB) and subsequent inhibition of pro‐apoptotic gene expression. Conversely, exogenously expressed truncated β‐chain (β∆) stabilizes OGA by disrupting the association between UFL1 and OGA, consequently abolishing the anti‐apoptotic effects of O‐GlcNAcylated NF‐κB. The findings identify LRP1, particularly its β‐chain, as a novel upstream control factor that facilitates the stabilization of the OGA protein, thereby suppressing NF‐κB signaling and attenuating HCC progression, thus suggesting a novel therapeutic strategy for HCC.

BackgroundRecent studies offer conflicting conclusions about the effectiveness of digital health interventions in changing physical activity behaviors. In addition, research focusing on digital health interventions for college students remains relatively scarce. ObjectiveThis study aims to examine the impact of digital health interventions on physical activity behaviors among college students, using objective measures as outcome indicators. MethodsIn accordance with the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a comprehensive literature search was conducted across several databases, including MEDLINE (PubMed), Web of Science, Cochrane Library, and EBSCO (CINAHL Plus with full text), to identify relevant intervention studies published up to June 6, 2023. The inclusion criteria specified studies that examined the quantitative relationships between digital health interventions and physical activity among adults aged 18 years to 29 years, focusing on light physical activity (LPA), moderate to vigorous physical activity (MVPA), sedentary time (ST), or steps. Non–randomized controlled trials were excluded. The quality of the studies was assessed using the Cochrane Risk of Bias tool. Results were synthesized both narratively and quantitatively, where applicable. When sufficient homogeneity was found among studies, a random-effects model was used for meta-analysis to account for variability. ResultsIn total, 8 studies, encompassing 569 participants, were included in the analysis. The primary outcomes measured were LPA, MVPA, ST, and steps. Among these studies, 3 reported on LPA, 5 on MVPA, 5 on ST, and 3 on steps. The meta-analysis revealed a significant increase in steps for the intervention group compared with the control group (standardized mean difference [SMD] 0.64, 95% CI 0.37-0.92; P

Laser cladding is a highly effective technique used in additive manufacturing to enhance the surface properties of workpieces. It is employed to improve wear resistance, corrosion resistance, and high-temperature resilience of materials. This study explores the utilization of laser cladding technology to repair the surface of AISI A2 tool steel by applying a coating of M2 steel. Sixteen experiments were designed using an orthogonal methodology to investigate the intricate relationship between various processing parameters, including laser power, scan speed, powder feed rate, and overlapping ratio. These parameters were examined in conjunction with key mechanical properties of the coating, such as micro-hardness, friction-wear characteristics, and shear bond strength.Additionally, analytical techniques such as Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and X-ray Diffraction (XRD) were employed to gain insights into the microstructure of the coatings and elucidate the underlying failure modes. Shear testing of the coatings indicated a tendency towards a brittle fracture mode within the coating, with the dominant wear mechanism involving a combination of abrasive and oxidative wear.Finally, a TOPSIS-Grey Relational Analysis (GRA) method was utilized to identify the optimal process parameters. These optimal parameters were determined to be a laser power of 1200 W, a scan speed of 5 mm/s, a powder feed rate of 14 g/min, and an overlapping ratio of 30 %. Subsequent validation experiments carried out with these parameters demonstrated superior performance compared to the optimal group identified in the orthogonal experiment.

Inconel 718 alloy (IN718) is a popular choice for aerospace hot-end components due to its exceptional mechanical properties. This study investigates the impact of processing parameters (i.e., laser power, powder feeding rate, and scanning speed) on the microhardness, bond strength, and tensile strength of layer-cladded IN718. The results show that IN718 coatings have high microhardness (277.15 HV0.1), strong metallurgical bonding strength (33.97 kN), substantial yield strength (794.09 MPa), impressive ultimate tensile strength (1171.81 MPa), and notable elongation at failure (8.24 %) under laser power is 1.2 kW, powder feeding rate is 250 mg/s, and scanning speed is 4.5 mm/s. In particular, decreased laser energy input enhances microhardness, yield strength, and ultimate tensile strength but reduces bonding strength and elongation. This is attributed to improved Nb element segregation, the reduction of the Laves phase, and grain refinement. However, inadequate energy input leads to cracks and unmelted powder, negatively affecting metallurgical bonding strength. The shear and tensile fracture mechanism of the IN718 coatings is a typical ductile fracture with a microvoid accumulation fracture. The study can facilitate the fabrication of the IN718 coatings with the excellent mechanical properties and the applications in the engineering field.

The addition of third elements may help transform brittle D022-structured lightweight Al3Ti to a relatively ductile L12-structured (Al, M)3Ti (where M represents the third elements), thus increasing the ductility at the expense of hardness. Such a transformation could benefit the wear resistance of the alloy due to improved toughness if a proper balance between the hardness and ductility is achieved. In this work, a D022-predominant Al3Ti alloy (S-Al3Ti) and an L12-predominant (Al, Fe)3Ti alloy (S-Al67Ti25Fe8) were fabricated by arc melting. Change in wear resistance, corresponding to a D022-to-L12 transformation, caused by the addition of Fe as a representative third element, was investigated and compared with the wear resistance of a commercial Al-matrix composite reinforced by 30 wt.% SiC particles (S-Al/SiCp) as a reference material. It was observed that wear of the S-Al3Ti resulted from abrasion involving synergistic oxidation, leading to a larger volume loss. In contrast, the softer S-Al67Ti25Fe8 showed enhanced wear resistance, benefiting from improved toughness with reasonable hardness. During the wear testing, both the alloys exhibited better performance than S-Al/SiCp, a well-known lightweight composite. This study highlights that D022-to-L12 transformation enhances wear resistance due to increased toughness which can be adjusted using the addition of a third element.

ObjectiveThe escalating prevalence of physical inactivity among college students represents a significant public health challenge, particularly in light of its correlation with detrimental health outcomes. A growing body of evidence underscores the necessity of adhering to recommended levels of regular physical activity to thwart the onset of chronic diseases. One primary aim of school physical education initiatives is to elevate physical activity levels and bolster student motivation toward engaging in physical exercise. Engagement in sports activities has demonstrated efficacy in augmenting students’ motor skills, elevating their self-efficacy, and enhancing cognitive competencies related to physical prowess, while also promoting sustained participation in physical activities. The Exercise Empowerment Scale (EES) has been formulated to quantitatively assess the degree of exercise empowerment. To date, no validated Chinese version of the EES has been reported in the literature. To address this, this present study developed and validated a Chinese version of the EES in a large sample of Chinese college students.MethodsA sample of Chinese college students (n = 885) was analyzed using Rasch analysis to examine the validity of the Exercise Empowerment Scale. In addition, physical activity and psychological resilience were used to investigate the potential associations with exercise empowerment.ResultsThe EES-C was found to be a unidimensional scale, and the distribution of item difficulty was relatively even. The scale had good reliability (individual reliability of 0.87, and item reliability of 0.99). No differential item functioning (DIF) was observed across genders for any of the 13 EES-C items, suggesting equitable and unbiased applicability for both male and female respondents. The five-point scoring method of the EES scale was consistent with the overall distribution of the items and subjects. Exercise empowerment was positively correlated with autonomous physical activity and psychological resilience.ConclusionThe results of the study indicate that the EES-C possesses robust psychometric properties, rendering it suitable for application among Chinese college student populations. The adapted version of the EES-C provides a basis for further exploration of the predictive factors of physical activity in Chinese samples. The generalizability of our findings should be further verified in other populations in the future.

ObjectiveThis study aims to evaluate the reliability and validity of the Chinese version of the Physical Activity Social Support Scale (PASSS-C) and its measurement invariance across different gender groups in a Chinese college student sample.MethodsA total of 1,689 Chinese college students participated in the study. We assessed the internal consistency of PASSS-C using Cronbach’s alpha and McDonald’s omega. A Confirmatory Factor Analysis (CFA) was conducted to test its five-factor model. Multi-group CFA was used to examine measurement equivalence between male and female groups. Convergent and criterion-related validity were assessed using Pearson correlation coefficients.ResultsThe overall internal consistency of PASSS-C was good with a Cronbach’s alpha of 0.952, and the subscales showed acceptable consistency. The CFA results supported the five-factor structure of PASSS-C in the college student sample, with values of CFI = 0.932, TLI = 0.917, RMSEA = 0.048, 90% CI [0.043 0.053], SRMR = 0.047. Scalar invariance was also supported across different gender groups, with ΔCFI = −0.003, ΔTLI = 0, ΔRMSEA = 0. PASSS-C demonstrated good convergent and criterion-related validity.ConclusionPASSS-C exhibits satisfactory psychometric properties and is a valid and reliable tool for assessing the perceived level of social support for physical activity among college students.

Springback error is a major obstacle in L-bending sheets via cold working. Although thermal processing can effectively reduce the springback phenomenon, it is challenging to heat the sheet globally due to the influence of working conditions. Therefore, this study applied local induction heating to reduce the springback of 45 steel sheets and investigated the effects of bending parameters on springback behavior. Initially, a thermodynamic coupling model and a static model were created utilizing the VOCE hardening model and the von Mises yield criterion in the ANSYS workbench 2022 R2 software. The springback behavior and stress distribution of the sheets were then investigated under different temperatures (room temperature and 800 °C) and bending angles (15°, 30°, 45°, 60°, 75°, and 90°). Simultaneously, the experiments were performed to investigate springback behavior and guarantee the accuracy of the model. The results indicate that the springback reached a minimum value at the 45° bending angle at room temperature while increasing with the increasing bending angle under 800 °C local heating. The springback under local heating can be decreased by 75.2% and the error of the bending angle can improve by 2–7° compared with samples processed in room temperature.

ObjectiveThis study aims to explore the association between health information preferences and specific health behaviors and outcomes, such as preventive measures and chronic disease management among college students. It assesses how different levels of health information preference influence individuals’ utilization, perception, and self-efficacy within healthcare and health information contexts. Given the rising prevalence of non-communicable chronic diseases among younger populations in China, this research seeks to understand how tailored health information preferences can support effective health education and behavioral interventions. The development of the Health Information Preference Questionnaire (HIPQ) aims to bridge the existing gap in tools for assessing health information preferences among Chinese college students, with a focus on collecting validity evidence to confirm the HIPQ’s applicability in this group.MethodsThe study employed a mixed-methods approach, beginning with an initial item pool derived from a comprehensive review of existing research tools, literature, and expert inputs. An expert review panel conducted item evaluations, leading to item reduction for clarity and relevance. The validation process utilized two independent samples of college students, detailing the sample size (n = 446 for preliminary testing, n = 1,593 for validation) and characteristics (age, major, urban vs. rural background) to enhance the understanding of the study’s generalizability.ResultsThe HIPQ, comprising 25 items across five dimensions—prevention-oriented approaches, relationship with healthcare providers, self-efficacy in obtaining health information, perception of the importance of health information, and health information behavior—demonstrated excellent content validity (ICVI ranged from 0.72 to 0.86). Factor analysis confirmed significant loadings for each item across the anticipated factors, with fit indices (RMSEA = 0.065, CFI = 0.942) supporting good model fit. The HIPQ’s reliability was underscored by Cronbach’s alpha coefficients (>0.8) for each subscale, with significant correlations across all subscales, indicating strong internal consistency and construct validity.ConclusionThe HIPQ proves to be a reliable and valid instrument for assessing health information preferences among Chinese college students, highlighting its potential for broader application in health education and intervention strategies. Recognizing the study’s focus on a specific demographic, future research should investigate the HIPQ’s adaptability and utility in broader populations and different cultural settings. The study’s limitations, including its concentrated demographic and context, invite further exploration into the HIPQ’s applicability across diverse groups. Additionally, potential future research directions could include longitudinal studies to assess the impact of tailored health information on actual health outcomes and behaviors.

Background/objectiveSocial physique anxiety (SPA) is a prevalent psychological issue among emerging adults, regardless of gender. Many studies have shown that high levels of SPA are associated with various negative consequences on both physical and mental well-being. Considering the potential severity of SPA’s consequences and its high prevalence among emerging adults, it is imperative to investigate the factors and mechanisms that contribute to SPA in this population. Although prior studies have identified associations between emerging adulthood, digital media use, and SPA in young individuals, the underlying mechanisms remain unclear. The objective of this study is to examine the associations between SPA, emerging adulthood characteristics, digital media dependency, and exercise empowerment.MethodsIn this cross-sectional study, Chinese college students were recruited using snowball sampling. The study utilized an online survey to assess SPA, emerging adulthood characteristics, digital media dependency, and exercise empowerment. The collected data was analyzed using path analysis.ResultsA total of 1,661 Chinese college students (mean age = 19.63 ± 0.32 years, 44.97% male) were included in this study. The results showed that SPA exhibited positive correlations with responsibility and instability in emerging adulthood characteristics, digital media dependency, and exercise empowerment. Additionally, digital media dependency showed positive correlations with responsibility and instability, as well as with exercise empowerment. Furthermore, exercise empowerment demonstrated positive correlations with self-exploration, responsibility, instability, and possibilities in emerging adulthood characteristics. SPA can be directly influenced by digital media dependency, self-exploration, and instability. Furthermore, digital media dependency has a positive indirect impact on SPA through exercise empowerment. Similarly, self-exploration also has a positive indirect impact on SPA through exercise empowerment. On the other hand, instability has a negative indirect impact on SPA through exercise empowerment.ConclusionThis study provides new insights into the complex correlations with emerging adulthood characteristics, digital media dependency, exercise empowerment, and SPA. Instability, self-exploration in emerging adulthood characteristics, as well as digital media dependency, have the potential to influence SPA among college students through exercise empowerment Interventions and strategies aimed at addressing these psychological factors may prove beneficial in reducing SPA among emerging adults, especially college students.

Abstract Ship path planning plays an important role in the intelligent decision-making system which can provide important navigation information for ship and coordinate with other ships via wireless networks. However, existing methods still suffer from slow path planning and low security problems. In this paper, we propose a second-order ship path planning model, which consists of two main steps, i.e., first-order static global path planning and second-order dynamic local path planning. Specifically, we first create a raster map using ArcGIS. Second, the global path planning is performed on the raster map based on the Dyna-Sarsa( $$\lambda$$ λ ) model, which integrates the eligibility trace and the Dyna framework on the Sarsa algorithm. Particularly, the eligibility trace has a short-term memory for the trajectory, which can improve the convergence speed of the model. Meanwhile, the Dyna framework obtains simulation experience through simulation training, which can further improve the convergence speed of the model. Then, the improved ship trajectory prediction model based on stacked bidirectional gated recurrent unit is used to identify the risk of ship collision and switch the path planning from the first order to the second order. Finally, the second-order dynamic local path planning is presented based on the FCC-A* algorithm, where the cost function of the traditional path planning A* algorithm is rewritten using the fuzzy collision cost membership function (fuzzy collision cost, FCC) to reduce the collision risk of ships. The proposed model is evaluated on the Baltic Sea geographic information and ship trajectory datasets. The experimental results show that the eligibility trace and the Dyna learning framework in the proposed model can effectively improve the planning efficiency of the ship’s global path planning, and the collision risk membership function can effectively reduce the number of collisions in A* local path planning and thus improve the navigation safety of encountering ships.

Laser cladding, an innovative surface modification and coating preparation process, has emerged as a research hotspot in material surface modification and green remanufacturing domains. In the laser cladding process, the interaction between laser light, powder particles, and the substrate results in a complicated mapping connection between process parameters and clad layer quality. This work aims to shed light on this mapping using fast evolving machine learning algorithms. A full factorial experimental design was employed to clad Inconel 718 powder on an A286 substrate comprising 64 groups. Analysis of variance, contour plots, and surface plots were used to explore the effects of laser power, powder feeding rate, and scanning speed on the width, height, and dilution rate of the cladding. The performance of the predictive models was evaluated using the index of merit (IM), which includes mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R ^2 ). By comparing the performance of the models, it was found that the Extra Trees, Random forest regression, Decision tree regression, and XGBoost algorithms exhibited the highest predictive accuracy. Specifically, the Extra Trees algorithm outperformed other machine learning models in predicting the cladding width, while the RFR algorithm excelled in predicting the associated height. The DTR algorithm demonstrated the best performance in predicting the cladding dilution rate. The R ^2 values for width, height, and dilution rate were found to be 0.949, 0.954, and 0.912, respectively, for these three models.

During the restoration of secondary forests in Northeast China, it is critically important to promote seed recruitment of Korean pine (Pinus koraiensis), which is highly dependent on rodents and significantly affected by spatially heterogeneous understory vegetation of forest gaps. Understanding the link between understory microhabitats and rodent-mediated seed dispersal, including post-dispersal seed predation and scatter-hoarding seed escaped predation, is essential to improve seed survival. Previous studies have focused on their qualitative relationships by roughly classifying understory vegetation characteristics, which cannot precisely predict regeneration direction. Quantifying the spatial heterogeneity of understory vegetation parameters (e.g., canopy cover, CC; gap fraction, GF) using terrestrial laser scanning (TSL) provides a vital way to determine quantitative relationships. In this study, we collected point cloud data in forest gaps with three sizes and six within-gap positions through TSL to quantify the understory microhabitats using CC and GF and integrated these parameters with spatial site data of Korean pine seeds scatter-hoarding and post-dispersal predation by rodents. The results showed that the influence of the within-gap position on the understory microhabitats was insignificant, and the spatial site selection of post-dispersal seed predation and seed storage was concentrated in the range of 0–22 m away from the seed station, irrelevant to the gap size. Considering the risk of predation by enemies and seed pilferage by competitors in forest gaps, rodents scatter-hoarded or post-dispersal predated seeds in the CC range of 0.2–0.3, and post-dispersal predated seeds less often in the CC range > 0.8. The ratio of post-dispersal seed predation to scatter-hoarding escaped predation firstly increased and then decreased along with the increase in CC and GF. Therefore, the spatial heterogeneity in understory microhabitats caused by gap treatment had an uncertain effect on rodent-mediated seed dispersal, depending on the relative ratio of post-dispersal seed predation to seed scatter-hoarding.

PurposeThe purpose of this study was to test the factor structure as well as the reliability of the Physical Education Teacher Job Satisfaction Scale (PETJSS).MethodThe scale’s structural validity, internal consistency and reliability were examined using CFA and Cronbach alpha. The predictive validity of the PETJSS was examined using Teacher Self-Efficacy (TSES-11) and the personal characteristics of the subjects.ResultThe three-factor structure of the PETJSS was confirmed. The PETJSS three-dimensional model had good internal consistency/reliability. The three dimensions of the PETJSS (colleague satisfaction, parent satisfaction and student behaviour satisfaction) explained 81.206% of the overall job satisfaction. Also, the PETJSS demonstrated the expected correlation with teachers’ self-efficacy, whilst the PETJSS test results were related to physical education teachers’ job titles.ConclusionThe PETJSS (Chinese version) can be considered as a valid and reliable method.

Warming and precipitation reduction have been concurrent throughout this century in most temperate regions (e.g., Northeast China) and have increased drought risk to the growth, migration, or mortality of tree seedlings. Coexisting tree species with different functional traits in temperate forests may have inconsistent responses to both warming and decreased precipitation, which could result in a species distribution shift and change in community dynamics. Unfortunately, little is known about the growth and physiological responses of coexisting species to the changes in these two meteorological elements. We selected two coexisting species in a temperate secondary forest of Northeast China: Quercus mongolica Fischer ex Ledebour (drought-tolerant species) and Fraxinus mandschurica Rupr. (drought-intolerant species), and performed an experiment under strictly controlled conditions simulating the predicted warming (+2°C, +4°C) and precipitation reduction (-30%) compared with current conditions and analyzed the growth and physiology of seedlings. The results showed that compared with the control, warming (including +2°C and +4°C) increased the specific area weight and total biomass of F. mandschurica seedlings. These were caused by the increases in foliar N content, the activity of the PSII reaction center, and chlorophyll content. A 2°C increase in temperature and reduced precipitation enhanced root biomass of Q. mongolica, resulting from root length increase. To absorb water in drier soil, seedlings of both species had more negative water potential under the interaction between +4°C and precipitation reduction. Our results demonstrate that drought-tolerant species such as Q. mongolica will adapt to the future drier conditions with the co-occurrence of warming and precipitation reduction, while drought-intolerant species will accommodate warmer environments.

BackgroundPhysical literacy (PL) is an important tool to promote physical activity of individuals, and the level of physical literacy of individuals affects their physical activity behaviors. Currently, the physical fitness of college students in China is a prominent issue, and assessing physical literacy among college students may provide tools and directions to further promote physical fitness and precisely intervene in physical activity behaviors of college students in the future. This study aimed to develop a college student physical literacy questionnaire (CSPLQ) to address the lack of currently available physical literacy assessment tools for Chinese college students. We hoped to collect validity evidence of this questionnaire to measure the validity of the physical literacy self-assessment questionnaire among Chinese university students.MethodsAn initial pool of items was obtained from existing research instruments, literature, and expert advice. An expert review panel evaluated its content. A subsequent validation process reduced the pool of items. We conducted a validation factor analysis of the CSPLQ using structural equation modeling. The relationship between physical literacy and other variables was also examined using correlation analysis.ResultsThe item content validity index (ICVI) of CSPLQ was 0.70–0.95. The CSPLQ was composed of a total of 38 items across 3 domains (physical and behavioral domain, affective domain, and cognitive domain) and 7 dimensions (motor skills, motor skills, physical activity, perceptions of healthy living, perceptions of physical activity, motivation to engage in physical activity, and confidence to engage in physical activity). The factor validity of the CSPLQ was determined by significant loading of all items on their expected factors, with good data model fit and good stability between two independent samples were demonstrated. Each subscale had a Cronbach α coefficient >0.9 and was strongly correlated with each other. The correlation coefficients between college students' physical literacy and other variables, including athletic ability, physical condition, physical attractiveness, physical fitness, frequency of physical activity, and length of physical activity, all reached a significance level of P < 0.05.ConclusionThe CSPLQ has sufficient evidence of validity. The development of the instrument showed evidence of validity for the content, response process, internal structure, and relationships with other variables.

With the continuous development of technologies such as the Internet of Things (IoT) and cloud computing, sensors collect and store large amounts of sensory data, realizing real-time recording and perception of the environment. Due to the open characteristics of WSN, the security risks during information transmission are prominent, and network attack or intrusion is likely to occur. Therefore, effective anomaly detection is vital for IoT systems to keep the system safe. The original Isolation Forest algorithm is an anomaly detection algorithm with linear time complexity and has a better detection effect on perceptual data. However, there are also disadvantages such as strong randomness, low generalization performance, and insufficient stability. This paper proposes a data anomaly detection method named BS-iForest (box plot-sampled iForest) for wireless sensor networks based on a variant of Isolation Forest to address the problems. This method first uses the sub-dataset filtered by the box graph to train and construct trees. Then, isolation trees with higher accuracy are selected in the training set to form a base forest anomaly detector. Next, the base forest anomaly detector uses anomaly detection to judge data outliers during the next period. These experiments were performed on datasets collected from sensors deployed in a data center of a university, and the Breast Wisconsin (BreastW) dataset, showing the performance of the variant of the Isolation Forest algorithm. Compared with the traditional isolation forest, the area under the curve (AUC) increased by 1.5% and 7.7%, which verified that the proposed method outperforms the standard Isolation Forest algorithm with the two datasets we chose.

With the widespread use of automatic identification systems (AISs), some ships use deceptive information or intentionally close their AISs to conceal their illegal activities or evade the supervision of maritime departments. Although radar measurements can be effectively utilized to evaluate the credibility of received AIS data, the propagation of non-line-of-sight (NLOS) signal conditions is an important factor that affects location accuracy. This study addresses the NLOS problem in a special geometric dilution of precision (GDOP) scenario on a coast and several base stations. We employed data augmentation and a deep residual shrinkage network in order to alleviate the adverse effects of NLOS errors. The results of our simulations demonstrate that the proposed method outperforms other range-based localization algorithms in a mixed LOS/NLOS environment. For a special GDOP scenario with four radars, our algorithm’s root-mean-square error (RMSE) was lower than 180 m.

AlCrFeNiTi0.5Mox (x = 0, 0.1, 0.2, 0.3 and 0.4) high-entropy alloys (HEAs) were prepared by arc melting and investigated in terms of microstructure, mechanical properties, and wear resistance. All the as-cast HEAs are composed of one disordered BCC phase (BCC) and one ordered BCC (B2) phase. The added Mo acted as a solid solute in the BCC phase. When Mo molar ratio was more than 0.3, a new type or modified BCC phase formed at the grain boundary, which was enriched with both Mo and Ti. Strength, hardness, and ductility of AlCrFeNiTi0.5 were markedly increased with the Mo addition. The increase in hardness was caused by Mo-solute strengthened disordered BCC phase and precipitation-strengthening by precipitation of hard (Mo, Ti)-rich BCC phase at grain boundaries. The improved ductility was largely attributed to reduced interfacial lattice mismatch between the BCC and B2 phase. The Mo-free AlCrFeNiTi0.5 showed the highest wear loss, about 2.5 times as large as that of AlCrFeNiTi0.5Mo0.4 alloy, which possessed the highest hardness, yield strength, maximum strength, and ductility.

In addition to the bulk properties of a workpiece material, characteristics of the tribofilms formed as a result of workpiece material mass transfer to the friction surface play a significant role in friction control. This is especially true in cutting of hardened materials, where it is very difficult to use liquid based lubricants. To better understand wear performance and the formation of beneficial tribofilms, this study presents an assessment of uncoated mixed alumina ceramic tools (Al2O3+TiC) in the turning of two grades of steel, AISI T1 and AISI D2. Both workpiece materials were hardened to 59 HRC then machined under identical cutting conditions. Comprehensive characterization of the resulting wear patterns and the tribofilms formed at the tool/workpiece interface were made using X-ray Photoelectron Spectroscopy and Scanning Electron Microscopy. Metallographic studies on the workpiece material were performed before the machining process and the surface integrity of the machined part was investigated after machining. Tool life was 23% higher when turning D2 than T1. This improvement in cutting tool life and wear behaviour was attributed to a difference in: (1) tribofilm generation on the friction surface and (2) the amount and distribution of carbide phases in the workpiece materials. The results show that wear performance depends both on properties of the workpiece material and characteristics of the tribofilms formed on the friction surface.

Purpose: The core component theory of addiction behavior provides a multidimensional theoretical model for measuring social networking addiction. Based on this theoretical model, the Social Networking Addiction Scale (SNAS) was developed. The aim of this study was to test the psychometric properties of the Chinese version of the SNAS (SNAS-C). Methods: This study used a sample of 3383 Chinese university students to conduct confirmatory factor analysis (CFA) to explore the structural validity of the SNAS-C. This study examined the Pearson correlations between the six subscales of the SNAS-C (i.e., salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse) and "social appearance anxiety (SAA)", and "parent and peer attachment (PPA)" to test the construct validity of the SNAS-C. Cronbach's alpha coefficient was used to evaluate the internal consistency of both the total and subscale scores. Results: The results of the CFA indicated that the six-factor model had an acceptable model fit (χ²/df = 10.954, p < 0.001; GFI = 0.946; AGFI = 0.928; IFI = 0.964; TLI = 0.955; CFI = 0.964; RMR = 0.041; SRMR = 0.037; RMSEA = 0.054 [90% CI [0.052-0.056]). Additionally, the total score of the SNAS-C was significantly positively correlated with the total score of SAA (r = 0.43, p < 0.01), and the subscales of the SNAS-C were significantly positively correlated with the total score of SAA to a medium degree (salience, r = 0.31, mood modification, r = 0.27, tolerance, r = 0.34, withdrawal symptoms, r = 0.39, conflict, r = 0.41, relapse, r = 0.40, p < 0.01). The results of the SNAS-C and PPA were somewhat different, as the SNAS-C was significantly negatively correlated with the PPA (r = -0.12, p < 0.01), and the four subscales were significantly negatively correlated with the PPA to a low degree (tolerance, r = -0.11, withdrawal symptoms, r = -0.15, conflict, r = -0.21, relapse, r = -0.15, p < 0.01). Finally, the SNAS-C also exhibited good internal consistency (Cronbach's a > 0.808). Conclusion: The results indicate that the six-factor model of the SNAS-C is acceptable, and its validity can meet the tendencies of social networking addiction among Chinese college students. In summary, the current translation and validation study of the SNAS-C provides an auxiliary tool for future research on social networking addiction in the Chinese context, but the generalizability of this scale in different populations requires further investigation. [ABSTRACT FROM AUTHOR]

The shift from natural mixed broadleaved forests to pure coniferous plantations results in soil degradation and the unsustainable development of plantations due to the simple stand structure and low species diversity. Thinning can practically sustain the forest structure and promote the regeneration and growth of broadleaved trees in these pure coniferous plantations. The growth of regenerated broadleaved trees is closely related to leaf ecological stoichiometry, which is strongly restricted by environmental factors such as light, soil moisture, and nutrients after thinning. However, the temporal effects of thinning on leaf C:N:P stoichiometry are still not well understood, which constrains our understanding of implementing thinning in coniferous plantations to promote the regeneration and growth of broadleaved species, and further forming the mixed larch-broadleaf forests. Here, we compared canopy openness (i.e., light availability) and the soil and leaf stoichiometry for regenerated broadleaved trees in larch (Larix keampferi) plantations in short-term (1–3 years), medium-term (4–9 years), and long-term (≥10 years) periods after thinning, taking natural mixed broadleaved forests as a control in Northeast China. The results showed that the temporal effects of thinning were not significant with respect to soil C concentrations, but significant with respect to soil C:P and N:P ratios. The regenerated broadleaved trees adjusted their leaf N concentrations and C:N ratios in response to the changed environmental conditions after thinning over time. The responses of soil and leaf stoichiometry to thinning and their significant correlation indicated a strong interaction between the soil and understory regeneration following thinning. Thus, thinning affects the soil and leaf stoichiometry of regenerated trees over time. These findings provide new insights into the conversion of pure coniferous plantations into mixed larch-broadleaf forests by controlling thinning intervals. [ABSTRACT FROM AUTHOR]