宁波城市职业技术学院于2003年3月经浙江省人民政府批准设置而成。学校的前身——宁波大学职业技术教育学院，创建于1992年，是浙江省最早开展全日制高等职业技术教育的机构，曾被原浙江省教委确定为省职业技术教育师资培训基地。2001年，“旅游管理与服务”专业被教育部确定为高职高专教育教学改革试点专业。学校本部校区地处宁波鄞州高教园区；溪口校区迁至萧王庙街道奉化城西文化教育园区，新建奉化校区。学校下设商学院、信息与智能工程学院、旅游学院、艺术学院、景观生态学院、财会金融学院、国际学院、成人教育学院/继续教育学院等8个二级学院及思想政治理论课教学部/基础课教学部，聘请国内外知名教授担任部分二级学院院长。学校现有教职工556人，全日制高职专科学生8330人，本科生362人。校设有30个高职专科专业、5个职教师资类本科专业（以宁波大学名义招生，颁发宁波大学毕业文凭和学位证书）。会计专业、物流管理专业被列为中央财政支持提升专业服务产业发展能力项目，共有省优势专业5个，省市特色、重点、品牌建设专业13个，校级重点专业18个，1门课程被认定为全国首批精品在线课程。学校重点打造基于现代服务业的“6+1”特色专业群，基本形成了以现代服务业为特色的专业结构体系。教育部《高等职业院校人才培养工作评估方案》颁布后，2009年12月，学校首批通过浙江省高职院校人才培养工作评估。学校力争打造成为宁波、浙江乃至长三角地区培养现代服务业人才的重要基地。
We investigate the impact of geopolitical risk (GPR) on global Travel & Leisure (T&L) stock returns using a Multivariate Quantile-on-Quantile Regression (MQQR) approach. Analyzing global, American, European, and Asian markets, we examine how GPR influences cross-market connectedness under different market conditions. Results reveal that the T&L sector exhibits a “fear-aspiration” dynamic, characterized by heightened vulnerability during market downturns and notable resilience during bullish conditions. American and European markets amplify global risk spillovers, whereas Asian markets act as relative buffers. Combining quantile-based vector autoregressions (QVAR) with OLS estimates, we demonstrate that GPR significantly dampens systematic return spillovers, particularly under extreme market conditions; instead, the underlying effects remain limited in normal states. These findings highlight the importance of integrating GPR measures into sector-specific stress-testing and early warning frameworks.
Acer rubrum is a widespread Acer species valued for its vibrant autumn foliage. The UGT (UDP-glycosyltransferase) gene family is integral to the biosynthesis of anthocyanins, the pigments responsible for leaf coloration. This study aimed to comprehensively identify and characterize the UGT gene family in the A. rubrum genome. The results of the phylogenetic analysis of 249 ArUGTs revealed 18 distinct subgroups. Conserved motif analysis demonstrated structural similarities within subgroups. Gene duplication analysis identified 21 tandem and 66 segmental duplication events across chromosomes. Transcriptomic data from autumn leaves of different colours and under low-temperature stress were analyzed for ArUGT expression patterns. Compared to controls, 44 UGTs were upregulated and 99 downregulated in yellow leaves, while 59 were upregulated and 84 downregulated in red leaves. Low-temperature treatments showed upregulation of 18 UGTs at 10 °C and 40 UGTs at 4 °C. Downregulation was observed in 7 UGTs at 10 °C and 33 UGTs at 4 °C. Among all UGT genes, ArUGT52 was common in highly expressed genes in both red leaf and low-temperature stress. Furthermore, the transient overexpression of ArUGT52 in tobacco plants demonstrated cytoplasmic localization and a marked increase in anthocyanin levels under cold stress. In vitro, biochemical assay results indicated that the ArUGT52 was involved in anthocyanin biosynthesis via the glucosylation of anthocyanidins. This study provides insights into the genetic mechanisms of leaf coloration and the potential of UGT manipulation for enhancing plant responses to low-temperature stress. These findings have applications in ornamental horticulture and agriculture.
The preservation of cultural heritage (CH) through sustainable tourism (ST) practices is vital for maintaining the authenticity and value of cultural sites worldwide. This research investigates the impact of ST on CH conservation in China, focusing on iconic heritage sites such as the Great Wall and the Forbidden City. The study aims to understand how ST contributes to safeguarding cultural assets by assessing the perceptions and behaviors of tourists who visited these sites within the past five years. A quantitative approach was adopted, utilizing a structured questionnaire to collect data from 500 tourists, with 420 complete responses analyzed using SPSS software. The analysis involved descriptive statistics, correlation, and regression techniques to explore the relationship between ST practices and CH preservation. Findings reveal strong positive perceptions of ST practices, particularly in areas of preservation, understanding, and sustainability. The study highlights the significant role of ST in fostering CH conservation and provides empirical insights into its impact. Its novelty lies in its focus on diverse communities and its in-depth analysis of the complex interplay between ST and CH preservation within the Chinese context. This research offers valuable contributions to the field by emphasizing the role of ST in preserving cultural assets for future generations.
The development of generative design driven by artificial intelligence algorithms is speedy. There are two research gaps in the current research: 1) Most studies only focus on the relationship between design elements and pay little attention to the external information of the site; 2) GAN and other traditional generative algorithms generate results with low resolution and insufficient details. To address these two problems, we integrate GAN, Stable diffusion multimodal large-scale image pre-training model to construct a full-process park generative design method: 1) First, construct a high-precision remote sensing object extraction system for automated extraction of urban environmental information; 2) Secondly, use GAN to construct a park design generation system based on the external environment, which can quickly infer and generate design schemes from urban environmental information; 3) Finally, introduce Stable Diffusion to optimize the design plan, fill in details, and expand the resolution of the plan by 64 times. This method can achieve a fully unmanned design automation workflow. The research results show that: 1) The relationship between the inside and outside of the site will affect the algorithm generation results. 2) Compared with traditional GAN algorithms, Stable diffusion significantly improve the information richness of the generated results.
Based on hot compression experiments and grain growth experiments of 6063 aluminum alloy, this study established a microstructure model for 6063 aluminum alloy. The accuracy of the developed model was verified by embedding it into hot compression numerical simulations through subroutine secondary development. Subsequently, the microstructure model was applied to the porthole die extrusion of complex cross-sectional profiles to investigate microstructure evolution during profile formation and analyze the influence of process parameters on microstructure. The results demonstrate that the established microstructure model can accurately predict the microstructural evolution of 6063 aluminum alloy during hot deformation. The results indicate that the established microstructure model can accurately predict the microstructure of the 6063 aluminum alloy. During the porthole die extrusion of complex cross-sections, the dynamic recrystallization (DRX) volume fractions from the surface to the interior of the profile are 92.44
