La sobrecarga de información percibida por los estudiantes universitarios y su influencia en el síndrome de respuesta inmediata al smartphone durante la pandemia de la COVID-19: Tomando la perspectiva de la personalidad

The COVID-19 pandemic has affected university students’ learning and social interaction to a large level, causing different degrees of negative emotions and made them extremely sensitive to smartphone information. However, little is known about the link between personalities, perceived information overload (PIO) and smartphone immediate response syndrome (SIRS) during students' learning process in this specific emergency social context. Therefore, based on the person-environment fit model, this study investigated 482 university students from mainland China during the epidemic by a snowball sampling approach, and analyzed the relationship between their personalities, PIO and SIRS by structural equation modeling. Results indicated that individuals with extraversion and neuroticism formed SIRS from different psychological paths. PIO plays a partial mediating role between neuroticism and SIRS and a fully mediating role between extraversion and SIRS. These findings validate the association among individual personality, PIO and SIRS in the non-conventional environment and highlights the difference exist in cellphone-related psychological path between extraverted and neurotic students. Therefore, it is recommended that PIO should be controlled in a targeted manner for individuals with different personality and guide them using cellphones rationally during the epidemic.La pandemia causada por la COVID-19 ha afectado en gran medida al aprendizaje y a la interacción social de los estudiantes universitarios, provocando emociones negativas de diferentes grados y haciéndoles extremadamente sensibles a la información de los smartphones. Sin embargo, se sabe poco sobre la relación entre la personalidad, la sobrecarga de información percibida (SIP) y el síndrome de respuesta inmediata al smartphone (SIRS) durante el proceso de aprendizaje de los estudiantes en este contexto social de emergencia específico. Por lo tanto, basándose en el modelo de ajuste persona-ambiente, este estudio investigó a 482 estudiantes universitarios de China continental durante la epidemia mediante un enfoque de muestreo de bola de nieve, y analizó la relación entre su personalidad, SIP y SIRS mediante un modelo de ecuaciones estructurales. Los resultados indicaron que los individuos con extraversión y neuroticismo formaron el SIRS a partir de diferentes vías psicológicas. La SIP desempeña un papel mediador parcial entre el neuroticismo y el SIRS y un papel totalmente mediador entre la extraversión y el SIRS. Estos resultados validan la asociación entre la personalidad individual, la SIP y el SIRS en el entorno no convencional y pone de manifiesto la diferencia que existe en la trayectoria psicológica relacionada con el teléfono móvil entre los estudiantes extrovertidos y los neuróticos. Por lo tanto, se recomienda controlar la SIP de forma específica para los individuos con personalidad diferente y guiarlos en el uso racional de los teléfonos móviles durante la epidemia

Sensor Fault Detection for Rail Vehicle Suspension Systems with Disturbances and Stochastic Noises

This paper develops a sensor fault detection scheme for rail vehicle passive suspension systems, using a fault detection observer, in the presence of uncertain track regularity and vehicle noises which are modeled as external disturbances and stochastic process signals. To design the fault detection observer, the suspension system states are augmented with the disturbances treated as new states, leading to an augmented and singular system with stochastic noises. Using system output measurements, the observer is designed to generate the needed residual signal for fault detection. Existence conditions for observer design are analyzed and illustrated. In term of the residual signal, both fault detection threshold and fault detectability condition are obtained, to form a systematic detection algorithm. Simulation results on a realistic vehicle system model are presented to illustrate the observer behavior and fault detection performance

University students' perceived information overload mediates smartphone immediate response syndrome during COVID-19 outbreak: Taking the perspective of personality

The COVID-19 pandemic has affected university students’ learning and social interaction to a large level, causing different degrees of negative emotions and made them extremely sensitive to smartphone information. However, little is known about the link between personalities, perceived information overload (PIO) and smartphone immediate response syndrome (SIRS) during students' learning process in this specific emergency social context. Therefore, based on the person-environment fit model, this study investigated 482 university students from mainland China during the epidemic by a snowball sampling approach, and analyzed the relationship between their personalities, PIO and SIRS by structural equation modeling. Results indicated that individuals with extraversion and neuroticism formed SIRS from different psychological paths. PIO plays a partial mediating role between neuroticism and SIRS and a fully mediating role between extraversion and SIRS. These findings validate the association among individual personality, PIO and SIRS in the non-conventional environment and highlights the difference exist in cellphone-related psychological path between extraverted and neurotic students. Therefore, it is recommended that PIO should be controlled in a targeted manner for individuals with different personality and guide them using cellphones rationally during the epidemic

Calculation of Sound Insulation for Hybrid CLT Fabricated with Lumber and LVL and comparison with experimental data.

The insulated predictions were carried out for LVL, CLT and HCLT in order to evaluate their sound properties, in which the theoretical value of sound insulation was predicted by regarding the substances in wood cell wall as equivalence to specific medium based on Biot model, and the wood anatomical characteristics, such as the length and diameter of tracheid, diameter of pit, and porosity, were taken into account for determining the equivalent density and bulk modulus of elasticity of wood cell wall. By comparing the tested and predicted values of sound insulation, the conclusion were drawn as follows: the predicted values of sound insulation were significantly correlated with the tested values for LVL, CLT and HCLT. As for Masson pine and Southern pine, the adjacent of earlywood and latewood was considered as sandwich structure for the calculation of sound insulation. Meanwhile, the bonding interface was creatively introduced to improve the accuracy of sound insulation prediction. The transfer function involved in sound insulation prediction provide an effective method to characterize the sound insulation volume of wood composite in construction and decoration areas

Comparison of Bonding Performance Between Plywood and Laminated Veneer Lumber Induced by High Voltage Electrostatic Field.

High voltage electrostatic field (HVEF) was applied in order to improve wood surface characteristics, bonding and mechanical properties of wood composites. Masson pine (Pinus massoniana Lamp.) plywood and laminated veneer lumber (LVL) were selected in this study. Surface characteristics were conducted by the electron spin resonance (ESR) and X-ray photoelectron spectra (XPS). Bonding interphase and mechanical properties were investigated by fluorescence microscopy and vertical density profile (VDP), bonding strength, wood failure ratio, MOE and MOR. The results indicated that more increments were obtained in free radicals, O/C ratios and C2-C4 components. This is because electrons broke more wood chemical groups and new ions occurred among wood surface under HVEF. Significantly decreased PF adhesive penetration depth (PD) and increased density at bonding interphase was achieved in HVEF treated composites. More decrease of PD and increment of density were observed in plywood than that of LVL. This was attributed to cross linked wood fibers among bonding interphase in plywood. Mechanical properties of bonding strength, wood failure ratio, MOE and MOR were significantly increased under HVEF treatment both for two composites. Higher bonding strength, MOE and MOR were obtained in plywood and their increments were as 98.53%, 33.33%, 18.55% and 12.72%

Repair of fingertip defect with reverse digital artery island flap and repair of donor site with digital dorsal advancement flap

ObjectiveThe reverse digital artery island flap (RDAF) is widely used in repairing fingertip skin defects based on its good appearance and practicability. However, the donor area of the flap needs skin grafting, which can lead to complications. This retrospective study explored the clinical application of digital dorsal advance flap (DDAF) in repairing the donor site of the reverse digital artery island flap.MethodFrom June 2019 to February 2022, 17 patients with a soft tissue defect of the finger had been restored with the reverse digital artery island flap, and at the same time, the donor area was repaired with digital dorsal advance flap (DDAF). The sensitivity, the active range of motion (ROM) and patient satisfaction were assessed after the operation.ResultsAll flaps survived completely without skin grafting with only one linear scar. The sensory and motor functions of all patients recovered well. Assessment based on the Michigan Hand Outcomes Questionnaire (MHQ) showed satisfactory functional recovery for all patients.ConclusionsReconstruction using RDAF combined with DDAF represents an effective alternative for repairing fingertip skin defects

Sustainability Education in Massive Open Online Courses: A Content Analysis Approach

The purpose of this study was to investigate the current status of sustainability education in Massive Open Online Courses (MOOCs). Sample MOOCs were searched for from seven popular platforms and three search engines. After screening, 51 courses were identified as the final sample. Course description, content outlines, reading materials, recommended textbooks and discussion threads were coded to obtain insights into sustainability education learning contents, pedagogical methods, and interaction situations. Results indicated that: (1) Edx and Coursera are platforms that incorporated the most sustainability-related courses, and most instructors were senior academics with the title of professor. American and European countries outperformed other English speaking countries as early birds in sustainability education using MOOCs. The average course length of our MOOC samples is 7.6 weeks, which is much shorter than a typical face-to-face college course; (2) Current MOOCs provided mainly introductory-level courses without prerequisites. Fourteen sustainability-related hot topics and five most popular textbooks were identified; (3) The pedagogical means used most frequently were discussion forums and lecture videos, while pedagogies such as team-based learning were not used to a large extent; (4) Learner interaction flourished in MOOCs, and sub-forums regarding Lecture Reflection, Welcome and Introduction were posted with most threads, replies, and votes. Our findings suggest that the MOOC is an innovative method in sustainability education and research. A variety of information and strategies could be used when preparing sustainability-related MOOCs

Online Learners’ Reading Ability Detection Based on Eye-Tracking Sensors

The detection of university online learners’ reading ability is generally problematic and time-consuming. Thus the eye-tracking sensors have been employed in this study, to record temporal and spatial human eye movements. Learners’ pupils, blinks, fixation, saccade, and regression are recognized as primary indicators for detecting reading abilities. A computational model is established according to the empirical eye-tracking data, and applying the multi-feature regularization machine learning mechanism based on a Low-rank Constraint. The model presents good generalization ability with an error of only 4.9% when randomly running 100 times. It has obvious advantages in saving time and improving precision, with only 20 min of testing required for prediction of an individual learner’s reading ability

Subject integration and theme evolution of STEM education in K-12 and higher education research

Abstract Over the past two decades, the field of STEM education has produced a wealth of research findings. This study systematically reviewed the published literature from the perspective of subject integration and theme evolution, considering both K-12 and higher education. It was found that STEM education originated from higher education, but the main emphasis is gradually shifting to the K-12 stage. There were mainly sixteen subjects involved in STEM education, showing the gradual in-depth integration of science, engineering, technology, math, humanities, and social sciences, in which humanism is increasingly emphasized. Culture is a new perspective for understanding the diversity of participants, which also gives STEM education a distinctive regional character. In addition, in the K-12 stage, research related to computer science and art stands out alongside the four main subjects, demonstrating relatively even distribution across research themes. Conversely, in higher education, engineering, and chemistry garner considerable attention, with research themes predominantly concentrated on learning outcomes and social relevance. On a holistic scale, researchers exhibit a pronounced interest in learning outcomes, yet relatively less emphasis is placed on pedagogical aspects. Regarding prospective trends, there should be a heightened focus on the cultivation of students’ thinking competencies, students’ career development, and pedagogy

Course Recommendation Based on Enhancement of Meta-Path Embedding in Heterogeneous Graph

The main reason students drop out of online courses is often that they lose interest during learning. Moreover, it is not easy for students to choose an appropriate course before actually learning it. Course recommendation is necessary to address this problem. Most existing course recommendation methods depend on the interaction result (e.g., completion rate, grades, etc.). However, the long period required to complete a course, especially large-scale online courses in higher education, can lead to serious sparsity of interaction results. In view of this, we propose a novel course recommendation method named HGE-CRec, which utilizes context formation for heterogeneous graphs to model students and courses. HGE-CRec develops meta-path embedding simulation and meta-path weight fusion to enhance the meta-path embedding set, which can expand the learning space of the prediction model and improve the representation ability of meta-path embedding, thereby avoiding tedious manual setting of the meta-path and improving the effectiveness of the resulting recommendations. Extensive experiments show that the proposed approach has advantages over a number of existing baseline methods