Demands and Development Strategies for Support Services of Autonomous Learning at Chinese Universities

In recent years, autonomous learning has become one of the most popular ways for Chinese university students to obtain new knowledge and skills, which requires more support services from their affiliated institutions. However, few previous studies combined investigation of the students’ needs and learning support services. Our study conducted online survey to analyze the status quo of Chinese students’ autonomous learning and the much-needed support services from their schools. We sent out the survey in October 2019 and received 458 valid responses. All participants were undergraduate students from 195 universities/colleges in China. The following information was collected: 1. School/Grade/Major of participant; 2. Autonomous learning time/goals/methods/main concerns of these students; 3. Existing support services, e.g., spaces, resources, counseling, procedures, activities; 4. The students’ degree of satisfaction with the available support services. Chinese students showed strong and diversified needs of support services to fulfill their autonomous learning tasks, which cannot be met by their schools. We proposed a development framework and some strategies for higher education institutions in China to launch more innovative learning support services

Design of the Reverse Logistics System for Medical Waste Recycling Part I: System Architecture, Classification & Monitoring Scheme, and Site Selection Algorithm

With social progress and the development of modern medical technology, the amount of medical waste generated is increasing dramatically. The problem of medical waste recycling and treatment has gradually drawn concerns from the whole society. The sudden outbreak of the COVID-19 epidemic further brought new challenges. To tackle the challenges, this study proposes a reverse logistics system architecture with three modules, i.e., medical waste classification & monitoring module, temporary storage & disposal site selection module, as well as route optimization module. This overall solution design won the Grand Prize of the "YUNFENG CUP" China National Contest on Green Supply and Reverse Logistics Design ranking 1st. This paper focuses on the description of architectural design and the first two modules, especially the module on site selection. Specifically, regarding the medical waste classification & monitoring module, three main entities, i.e., relevant government departments, hospitals, and logistics companies, are identified, which are involved in the five management functions of this module. Detailed data flow diagrams are provided to illustrate the information flow and the responsibilities of each entity. Regarding the site selection module, a multi-objective optimization model is developed, and considering different types of waste collection sites (i.e., prioritized large collection sites and common collection sites), a hierarchical solution method is developed employing linear programming and K-means clustering algorithms sequentially. The proposed site selection method is verified with a case study and compared with the baseline, it can immensely reduce the daily operational costs and working time. Limited by length, detailed descriptions of the whole system and the remaining route optimization module can be found at https://shorturl.at/cdY59.Comment: 8 pages, 6 figures, submitted to and under review by the IEEE Intelligent Vehicles Symposium (IV 2023

[OIII] 5007A Emission Line Width as a Surrogate for stellar dispersion in Type 1 AGNs?

We present a study of the relation between the [OIII] 5007A emission line width (sigma_{[OIII]}) and stellar velocity dispersion (sigma_{*}), utilizing a sample of 740 type 1 active galactic nuclei (AGNs) with high-quality spectra at redshift z < 1.0. We find the broad correlation between the core component of [OIII] emission line width (sigma_{[OIII,core]}) and sigma_{*} with a scatter of 0.11~dex for the low redshift (z < 0.1) sample; for redshift (0.3 < z < 1.0) AGNs, the scatter is larger, being 0.16~dex. We also find that the Eddington ratio (L_{bol}/L_{Edd}) may play an important role in the discrepancies between sigma_{[OIII,core]} and sigma_{*}. As the L_{bol}/L_{Edd} increases, sigma_{[OIII,core]} tends to be larger than sigma_{*}. By classifying our local sample with different minor-to-major axis ratios, we find that sigma_{*} is larger than sigma_{[OIII,core]} for those edge-on spiral galaxies. In addition, we also find that the effects of outflow strength properties such as maximum outflow velocity (V_{max}) and the broader component of [OIII] emission line width and line shift (sigma_{[OIII,out]} and V_{[OIII,out]}) may play a major role in the discrepancies between sigma_{[OIII,core]} and sigma_{*}. The discrepancies between sigma_{[OIII,core]} and sigma_{*} are larger when V_{max}, V_{[OIII,out]}, and sigma_{[OIII,out]} increase. Our results show that the outflow strengths may have significant effects on the differences between narrow-line region gas and stellar kinematics in AGNs. We suggest that caution should be taken when using sigma_{[OIII,core]} as a surrogate for sigma_{*}. In addition, the substitute of sigma_{[OIII,core]} for sigma_{*} could be used only for low luminosity AGNs.Comment: 17 pages, Accepted for publication in Ap

Design of the Reverse Logistics System for Medical Waste Recycling Part II: Route Optimization with Case Study under COVID-19 Pandemic

Medical waste recycling and treatment has gradually drawn concerns from the whole society, as the amount of medical waste generated is increasing dramatically, especially during the pandemic of COVID-19. To tackle the emerging challenges, this study designs a reverse logistics system architecture with three modules, i.e., medical waste classification & monitoring module, temporary storage & disposal site (disposal site for short) selection module, as well as route optimization module. This overall solution design won the Grand Prize of the "YUNFENG CUP" China National Contest on Green Supply and Reverse Logistics Design ranking 1st. This paper focuses on the design of the route optimization module. In this module, a route optimization problem is designed considering transportation costs and multiple risk costs (e.g., environment risk, population risk, property risk, and other accident-related risks). The Analytic Hierarchy Process is employed to determine the weights for each risk element, and a customized genetic algorithm is developed to solve the route optimization problem. A case study under the COVID-19 pandemic is further provided to verify the proposed model. Limited by length, detailed descriptions of the whole system and the other modules can be found at https://shorturl.at/cdY59.Comment: 6 pages, 4 figures, under review by the 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023

DilatedFormer: dilated granularity transformer network for placental maturity grading in ultrasound

Placental maturity grading (PMG) is often utilized for evaluating fetal growth and maternal health. Currently, PMG often relied on the subjective judgment of the clinician, which is time-consuming and tends to incur a wrong estimation due to redundancy and repeatability of the process. The existing methods often focus on designing diverse hand-crafted features or combining deep features and hand-crafted features to learn a hybrid feature with an SVM for grading the placental maturity of ultrasound images. Motivated by the dominated performance of end-to-end convolutional neural networks (CNNs) at diverse medical imaging tasks, we devise a dilated granularity transformer network for learning multi-scale global transformer features for boosting PMG. Our network first devises dilated transformer blocks to learn multi-scale transformer features at each convolutional layer and then integrates these obtained multi-scale transformer features for predicting the final result of PMG. We collect 500 ultrasound images to verify our network, and experimental results show that our network clearly outperforms state-of-the-art methods on PMG. In the future, we will strive to improve the computational complexity and generalization ability of deep neural networks for PMG

Negaton and Positon solutions of the soliton equation with self-consistent sources

The KdV equation with self-consistent sources (KdVES) is used as a model to illustrate the method. A generalized binary Darboux transformation (GBDT) with an arbitrary time-dependent function for the KdVES as well as the formula for $N$-times repeated GBDT are presented. This GBDT provides non-auto-B\"{a}cklund transformation between two KdV equations with different degrees of sources and enable us to construct more general solutions with $N$ arbitrary $t$-dependent functions. By taking the special $t$-function, we obtain multisoliton, multipositon, multinegaton, multisoliton-positon, multinegaton-positon and multisoliton-negaton solutions of KdVES. Some properties of these solutions are discussed.Comment: 13 pages, Latex, no figues, to be published in J. Phys. A: Math. Ge

Acupuncture modulates temporal neural responses in wide brain networks: evidence from fMRI study

<p>Abstract</p> <p>Background</p> <p>Accumulating neuroimaging studies in humans have shown that acupuncture can modulate a widely distributed brain network, large portions of which are overlapped with the pain-related areas. Recently, a striking feature of acupuncture-induced analgesia is found to be associated with its long-last effect, which has a delayed onset and gradually reaches a peak even after acupuncture needling being terminated. Identifying temporal neural responses in these areas that occur at particular time -- both acute and sustained effects during acupuncture processes -- may therefore shed lights on how such peripheral inputs are conducted and mediated through the CNS. In the present study, we adopted a non-repeated event-related (NRER) fMRI paradigm and control theory based approach namely change-point analysis in order to capture the detailed temporal profile of neural responses induced by acupuncture.</p> <p>Results</p> <p>Our findings demonstrated that neural activities at the different stages of acupuncture presented distinct temporal patterns, in which consistently positive neural responses were found during the period of acupuncture needling while much more complex and dynamic activities found during a post-acupuncture period. These brain responses had a significant time-dependent effect which showed different onset time and duration of neural activities. The amygdala and perigenual anterior cingulate cortex (pACC), exhibited increased activities during the needling phase while decreased gradually to reach a peak below the baseline. The periaqueductal gray (PAG) and hypothalamus presented saliently intermittent activations across the whole fMRI session. Apart from the time-dependent responses, relatively persistent activities were also identified in the anterior insula and prefrontal cortices. The overall findings indicate that acupuncture may engage differential temporal neural responses as a function of time in a wide range of brain networks.</p> <p>Conclusions</p> <p>Our study has provided evidence supporting a view that acupuncture intervention involves complex modulations of temporal neural response, and its effect can gradually resolve as a function of time. The functional specificity of acupuncture at ST36 may involve multiple levels of differential activities of a wide range of brain networks, which are gradually enhanced even after acupuncture needle being terminated.</p

Advances of hafnium based nanomaterials for cancer theranostics

Hafnium-based nanomaterials (Hf-NMs) have attracted the interest of numerous biomedical researchers by their unique properties. Recent years have witnessed significant advancements in the field of Hafnium-based nanomaterials, particularly in the context of cancer diagnosis and treatment. However, research in this area, especially concerning the clinical application of Hafnium-based nanomaterials, has not been thoroughly reviewed. This review will cover: 1) Classification and synthesis of Hafnium-based nanomaterials including Hafnium oxide nanomaterials, Hafnium Metal-Organic Frameworks/nanoscale coordination polymers (MOFs/NCPs); 2) Hafnium-based nanomaterials act as contrast enhancement agent for cancer imaging, and hafnium-based nanomaterials used for diagnosis in cancer liquid biopsy; 3) hafnium-based nanomaterials for cancer therapy, including hafnium-based nanomaterials for radiotherapy, hafnium-based nanomaterials for photodynamic therapy, hafnium-based nanomaterials for various combined therapy; and 4) Translation, toxicity, and safety for Hf-NMs in human and preclinical animal models. More attention will be given to the clinical translation of Hf-NMs in cancer