Understanding Distributed Leadership and Insights for Chinese Educational Institutions in the Context of Digital Transformation: A Literature Review

When education across all levels, is no exception for meeting the needs of industry 4.0 and the new demand of the digital economy and society, distributed leadership is an effective reform strategy for organization's transition to digital transformation. 174 articles related to distributed leadership were selected from eight core-international journals in the field of educational leadership and management with an average h-index of 45, and 64 articles with the keywords of distributed leadership published in the CSSCI and core journals were found. The 248 articles in total were reviewed for analysis with three aspects (research themes and theories; research methodology and analytical methods; discovery and revelation) which were synthesized from the systematic conceptual framework of literature review by Hallinger (2013,2014), the research conclusion frameworks by Bennett et al. (2003) and Tian et al. (2016). The literature review was conducted on four aspects (who, why, what and how) for knowing which most scholars are concerned and for informing educational institutions with insights on distributed leadership for future development

Análisis de los factores de riesgo en el seguro de automóvil mediante la regresión cuantílica y expected shortfall

Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2022-2023, Tutor: Miguel SantolinoEste trabajo se enfoca en el estudio de las técnicas de regresión cuantílica y regresión conjunta de regresión cuantílica con expected shortfall. El objetivo principal es superar las limitaciones de la regresión lineal estándar en un contexto de datos con colas pesadas. Con este fin, se aplicarán ambas regresiones en una base de datos de seguros de automóviles, con el propósito de mejorar la comprensión de las relaciones entre variables en diferentes puntos de la distribución de la variable dependiente, que en este caso es el coste total de siniestros, y realizar predicciones más precisas

Three-way Imbalanced Learning based on Fuzzy Twin SVM

Three-way decision (3WD) is a powerful tool for granular computing to deal with uncertain data, commonly used in information systems, decision-making, and medical care. Three-way decision gets much research in traditional rough set models. However, three-way decision is rarely combined with the currently popular field of machine learning to expand its research. In this paper, three-way decision is connected with SVM, a standard binary classification model in machine learning, for solving imbalanced classification problems that SVM needs to improve. A new three-way fuzzy membership function and a new fuzzy twin support vector machine with three-way membership (TWFTSVM) are proposed. The new three-way fuzzy membership function is defined to increase the certainty of uncertain data in both input space and feature space, which assigns higher fuzzy membership to minority samples compared with majority samples. To evaluate the effectiveness of the proposed model, comparative experiments are designed for forty-seven different datasets with varying imbalance ratios. In addition, datasets with different imbalance ratios are derived from the same dataset to further assess the proposed model's performance. The results show that the proposed model significantly outperforms other traditional SVM-based methods

Polysaccharides isolated from Morinda officinalis How roots inhibits cyclophosphamide-induced leukopenia in mice

Purpose: To investigate the optimum parameters for extracting polysaccharides from Morinda officinalis How (MOP), and explore their inhibitory effects on leukopenia in mice.Methods: Orthogonal design was performed to investigate the optimum parameters for extracting MOP. A leukopenia mouse model was established by injection of cyclophosphamide (CTX) for three days. Thereafter, MOP (100, 200 and 400 mg/kg) was administered orally for 10 days. Furthermore, blood cells (leukocytes, neutrophil, lymphocyte and mononuclear cell) were analyzed, while serum IL-3 and IL- 6 were determined by ELISA. The thymus and spleen of the mice were separated and weighed to determine viscera indices.Results: Orthogonal design showed that the influence order of the four factors was extraction times (C) > ratio of water to raw material (RWM, D) > extraction time (B) > extraction temperature (A). The optimum extraction parameters for MOP were: extraction temperature (80 °C), extraction duration (2 h), no. of extractions (3), and ratio of water to raw material (30 mL/g). Furthermore, the results indicate that MOP (100, 200 and 400 mg/kg) elevated the levels of leukocyte (p < 0.01), neutrophil (p < 0.01), lymphocyte (p < 0.01) and mononuclear cell (p < 0.01) in leukopenia mice. Besides, MOP (100, 200 and 400 mg/kg) also increased thymus (p < 0.01) and spleen (p < 0.05) indices and serum levels of IL-3 (p < 0.05) and IL-6 (p < 0.01).Conclusion: Orthogonal design is a good strategy for optimizing extraction parameters of MOP. Furthermore, MOP stimulated synthesis of leukocytes in CTX-induced leukopenia in mice. Thus, MOP is a potential adjunct for the treatment of tumors/cancers.Keywords: Morinda officinalis, Polyscacharide, Orthogonal design, Leukopenia, Thymus index, Spleen inde

Event-Based Visual Odometry on Non-Holonomic Ground Vehicles

Despite the promise of superior performance under challenging conditions, event-based motion estimation remains a hard problem owing to the difficulty of extracting and tracking stable features from event streams. In order to robustify the estimation, it is generally believed that fusion with other sensors is a requirement. In this work, we demonstrate reliable, purely event-based visual odometry on planar ground vehicles by employing the constrained non-holonomic motion model of Ackermann steering platforms. We extend single feature n-linearities for regular frame-based cameras to the case of quasi time-continuous event-tracks, and achieve a polynomial form via variable degree Taylor expansions. Robust averaging over multiple event tracks is simply achieved via histogram voting. As demonstrated on both simulated and real data, our algorithm achieves accurate and robust estimates of the vehicle's instantaneous rotational velocity, and thus results that are comparable to the delta rotations obtained by frame-based sensors under normal conditions. We furthermore significantly outperform the more traditional alternatives in challenging illumination scenarios. The code is available at \url{https://github.com/gowanting/NHEVO}.Comment: Accepted by 3DV 202

Genetic Evolution and Molecular Selection of the HE Gene of Influenza C Virus

Influenza C virus (ICV) was first identified in humans and swine, but recently also in cattle, indicating a wider host range and potential threat to both the livestock industry and public health than was originally anticipated. The ICV hemagglutinin-esterase (HE) glycoprotein has multiple functions in the viral replication cycle and is the major determinant of antigenicity. Here, we developed a comparative approach integrating genetics, molecular selection analysis, and structural biology to identify the codon usage and adaptive evolution of ICV. We show that ICV can be classified into six lineages, consistent with previous studies. The HE gene has a low codon usage bias, which may facilitate ICV replication by reducing competition during evolution. Natural selection, dinucleotide composition, and mutation pressure shape the codon usage patterns of the ICV HE gene, with natural selection being the most important factor. Codon adaptation index (CAI) and relative codon deoptimization index (RCDI) analysis revealed that the greatest adaption of ICV was to humans, followed by cattle and swine. Additionally, similarity index (SiD) analysis revealed that swine exerted a stronger evolutionary pressure on ICV than humans, which is considered the primary reservoir. Furthermore, a similar tendency was also observed in the M gene. Of note, we found HE residues 176, 194, and 198 to be under positive selection, which may be the result of escape from antibody responses. Our study provides useful information on the genetic evolution of ICV from a new perspective that can help devise prevention and control strategies

Conditional random pattern model for copy number aberration detection

<p>Abstract</p> <p>Background</p> <p>DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.</p> <p>Results</p> <p>This paper presents a conditional random pattern (CRP) model for CNA detection where much contextual cues are explored to suppress the noise and improve CNA detection accuracy. Both simulated and the real data are used to evaluate the proposed model, and the validation results show that the CRP model is more robust and reliable in the presence of noise for CNA detection using high density SNP array data, compared to a number of widely used software packages.</p> <p>Conclusions</p> <p>The proposed conditional random pattern (CRP) model could effectively detect the CNA regions in the presence of noise.</p

Host-range shift of H3N8 canine influenza virus: a phylodynamic analysis of its origin and adaptation from equine to canine host

International audiencePrior to the emergence of H3N8 canine influenza virus (CIV) and the latest avian-origin H3N2 CIV, there was no evidence of a circulating canine-specific influenza virus. Molecular and epidemiological evidence suggest that H3N8 CIV emerged from H3N8 equine influenza virus (EIV). This host-range shift of EIV from equine to canine hosts and its subsequent establishment as an enzootic CIV is unique because this host-range shift was from one mammalian host to another. To further understand this host-range shift, we conducted a comprehensive phylodynamic analysis using all the available whole-genome sequences of H3N8 CIV. We found that (1) the emergence of H3N8 CIV from H3N8 EIV occurred in approximately 2002; (2) this interspecies transmission was by a reassortant virus of the circulating Florida-1 clade H3N8 EIV; (3) once in the canine species, H3N8 CIV spread efficiently and remained an enzootic virus; (4) H3N8 CIV evolved and diverged into multiple clades or sublineages, with intra and inter-lineage reassortment. Our results provide a framework to understand the molecular basis of host-range shifts of influenza viruses and that dogs are potential “mixing vessels” for the establishment of novel influenza viruses