菟丝子醇提液对小鼠脑缺血再灌注损伤的保护作用

目的探讨菟丝子醇提液（AECS）对脑缺血再灌注（I/R）小鼠学习记忆障碍的改善作用,对肝脑组织中相关酶的作用及其作用机制。方法利用超声提取法制备AECS;采用暂时性阻断两侧颈总动脉的方法制备小鼠脑I/R损伤的模型,进行避暗实验,观察AECS对小鼠学习记忆功能的保护作用;生化方法测定肝脑组织中谷胱甘肽过氧化物酶（GSH-Px）活性。结果AECS中、高剂量可明显减少脑I/R小鼠避暗实验中错误次数,延长潜伏期;AECS中、高剂量能不同程度地提高肝、脑组织中GSH-Px活性。结论AECS对脑I/R所致小鼠记忆功能障碍具有保护作用,其作用机制可能为增强肝、脑组织中GSH-Px活性。     

云南野生香薷油对子代小鼠学习记忆功能的影响

本研究旨在探讨云南野生香薷油对子代小鼠学习记忆功能的影响。将昆明种小鼠从受孕第1d开始分为空白对照、阳性对照、低、中、高剂量5个组,用云南野生香薷油灌胃至断乳,断乳d小鼠按孕鼠剂量灌胃至出生49d后做Morris水迷宫实验,之后测定小鼠脑组织神经递质和肝、脑组织的脂肪酸。结果表明,与空白对照组比较,定位航行实验的第5d各组均有统计学意义（P〈0．01）。空间探索实验的阳性对照组有统计学意义（P〈0．05）。脑神经递质TPro、NO、AchE：阳性、中、高剂量组均有统计学意义（P〈0．05）。肝脂肪酸结果中阳性和高剂量组的ALA有统计学意义（P〈0．05）;脑组织脂肪酸结果：高剂量组的油酸和ALA有统计学意义（P〈0．05）。可见,富含α-亚麻酸的香薷油具有部分改善子代小鼠学习记忆的功能,其作用可能与喂养此香薷油使脑组织的TPro升高,NO、AchE降低;肝和脑组织的α-亚麻酸升高有关。     

Research on image segmentation of Miao costume patterns based on the RSKP-UNet model北大核心CSCD

The Miao nationality is the sixth largest ethnic group in China which has a history of thousands of years. It has created a unique material culture and spiritual culture in its development process and the Miao costume is a highly condensed collection of the material and spiritual culture of the Miao nationality. As one of the unique symbols of Miao culture the Miao costume has profound cultural heritage and cultural connotations. The patterns of the Miao costume are particularly eye-catching as they not only symbolize the wisdom of the Miao people in thousands of years of production and life but also symbolize the pursuit of the good spirit of the Miao people. However under the impact of modern pop culture and foreign culture these cultural symbols are gradually disappearing. In order to protect and inherit them the Miao costume pattern segmentation has become the most important work. However the Miao costume pattern segmentation is quite difficult. At present there are few studies on the extraction classification identification and preservation of the features of Miao costume pattern segmentation. With the excellent segmentation performance of the U-Net model and the advantages of easy deployment the paper improves the basic structure of the U-Net model and proposes a Miao costume pattern segmentation algorithm based on the RSKP-UNet Residual Selective-Kernel Parallel U-Net model. The algorithm adds Residual modules in the encoder part of the U-Net model to improve the feature extraction capability of the model and embeds the SKNet modules and ParNet modules in the decoder part to enhance the feature expression capability of the model. The paper uses evaluation metrics to measure the segmentation performance of the model and compares it with four segmentation models based on deep learning. The paper not only combines the current research focus-deep learning and attention mechanism but also introduces the Lovász-hinge loss function to effectively solve the problem of class imbalance in the Miao costume patterns. The RSKP-UNet model is better than other models in various segmentation indicators. Compared with the benchmark model U-Net the Dice coefficient IoU precision recall and accuracy are improved by 6. 98% 11. 07% 2. 89% 6. 75% and 3. 92% . The segmentation algorithm proposed in this paper realizes the extraction of the element content of the Miao costume patterns through image segmentation of Miao costume patterns which can be used to build the Miao costume pattern database in this way thus helping designers relevant researchers and organizations to provide research foundation and completing the protection and inheritance of the Miao costume culture. The paper also provides some reference for the segmentation research of other minority costume patterns. © 2022 Authors. All rights reserved.     

Virtual fencing technology to intensively graze lactating dairy cattle. II: Effects on cow welfare and behavior

Virtual fencing technology uses a neckband-mounted device to deliver an audio cue when an animal nears a virtual boundary that is set via a global positioning system, followed by an electrical stimulus if it crosses the boundary. The flexibility offered by this technology could revolutionize grazing management on dairy farms, but its application and effects on lactating dairy cattle have not been assessed. This experiment reports on the effects of an electric or a virtual front-fence on dairy cow behavior and welfare. Two temporally separated treatments were applied to a herd of 30 multiparous cows. Cows were provided an estimated 14 to 15 kg of dry matter/cow of fresh pasture in a new paddock every 24 h. From d 1 to 10 cows were grazed using a conventional electric front-fence (control treatment) and from d 14 to 23 they were grazed using a virtual front-fence (eShepherd, Agersens Pty Ltd.). Cows were trained to the technology from d 11 to 13. The milk production and live weight of individual cows were recorded daily. Cortisol concentrations were obtained from milk samples collected from individual cows on 3 d during each of the control and the virtual fence grazing periods, plus the first day of training. From d 6 of the experiment, 6 focal cows were fitted with a RumiWatch (Itin + Hoch GmbH) noseband sensor to monitor grazing and ruminating time, and 8 focal cows were fitted with an IceTag (IceRobotics Ltd.) sensors to monitor activity. Milk production, live weight, and the time cows spent standing and lying did not differ between the electric and virtual fence periods. Milk cortisol concentrations, activity, and the times spent ruminating and grazing were comparable between the electric and early virtual fence periods (i.e., d 1–3 with a virtual fence). However, at d 4 to 6 with a virtual fence, activity (steps taken and motion index) and time spent grazing were lower, and time spent ruminating was greater, compared with an electric fence. Further, least significant difference tests suggest milk cortisol concentrations were higher at d 5 with a virtual fence than at d 8 with an electric fence and d 1 with a virtual fence. We conclude there is no evidence of behavioral and welfare effects of virtual fencing on dairy cows in the days immediately following implementation of the technology in a simple intensive grazing regimen, but a longer study is required to fully elucidate effects beyond this period.     

Management practices associated with conception rate and service rate of lactating Holstein cows in large, commercial dairy herds

Data from lactating Holstein cows in herds that participate in a commercial progeny testing program were analyzed to explain management factors associated with herd-average conception and service rates on large commercial dairies. On-farm herd management software was used as the source of data related to production, reproduction, culling, and milk quality for 108 herds. Also, a survey regarding management, facilities, nutrition, and labor was completed on 86 farms. A total of 41 explanatory variables related to management factors and conditions that could affect conception and service rate were considered in this study. Models explaining conception and service rates were developed using a machine learning algorithm for constructing model trees. The most important explanatory variables associated with conception rate were the percentage of repeated inseminations between 4 and 17 d post-artificial insemination, stocking density in the breeding pen, length of the voluntary waiting period, days at pregnancy examination, and somatic cell score. The most important explanatory variables associated with service rate were the number of lactating cows per breeding technician, use of a resynchronization program, utilization of soakers in the holding area during the summer, and bunk space per cow in the breeding pen. The aforementioned models explained 35% and 40% of the observed variation in conception rate and service rate, respectively, and underline the association of herd-level management factors not strictly related to reproduction with herd reproductive performance.     

Excellence in teaching for promotion and tenure in animal and dairy sciences at doctoral/research universities: A faculty perspective

In this study, animal or dairy sciences faculty from doctoral/research universities were surveyed to clarify teaching performance expectations for the purpose of promotion and tenure of assistant professors. A survey tool including 15 evaluation criteria was available online and at the registration desk of the 2005 Joint Annual Meeting of the American Dairy Science Association and the American Society of Animal Science. The analyzed data set included 47 faculty (41 tenured and 6 tenure-track) with a substantial teaching responsibility from 27 different departments in 25 states. Four criteria were perceived as currently overemphasized: student evaluation of the instructor, student evaluation of the course, authoring peer-reviewed publications, and authoring an undergraduate textbook or book chapter. Nevertheless, more than 50% of respondents reported that these criteria should be used. One criterion emerged as being currently underemphasized: documentation of personal assessment of one's own teaching by preparing a portfolio. The lack of consensus for the remaining 10 items may have reflected substantial differences in institutional practices. The significance of overemphasis or underemphasis of certain criteria varied substantially depending on the respondent's perceived institutional mission. When asked about recognition within their department, 68% of respondents indicated that efforts in teaching improvement were properly rewarded. Respondents doubted the meaningfulness and appropriateness of student ratings tools as currently used. Results also suggested that animal and dairy science faculty placed a higher value on criteria recognizing excellence in teaching based on intradepartmental recognition (e.g., interactions with close-up peers and students) rather than recognition within a broader community of scholars as evidenced by authorship or success in generating funding for teaching. Proposed improvements in the evaluation of teaching for promotion and tenure include 1) providing tenure-track faculty with written guidelines at the time of hiring; 2) ensuring that student ratings tools are reliable and valid; 3) carefully mentoring new faculty within the departmental and institutional culture; and 4) encouraging self-reflection and documentation of attempts to address pedagogical issues in one's own teaching. Educational leaders in doctoral/research universities should promote changes to enhance teaching performance of future faculty graduating from their institutions.     

少样本学习下的服装风格分析与评价

为提高服装风格评价的客观性,提出了利用卷积神经网络对不同品牌服装风格特征进行自动提取、识别和分类的方法,以不同品牌的服装为对象,探究其视觉风格合理表征的方法,并实现品牌服装的分类任务。建立了品牌服装数据集,该数据集包含50个品牌的服装图像,每个服装品牌30张,随机抽取36个用作训练集,剩余14个用作支持集和查询集。采用少样本学习的网络模型,Siamese网络模型、Protype网络模型、Meta baseline网络模型对品牌服装数据集进行测试,对比分析3种网络模型的实验结果。结果表明:在品牌服装图像数据较少的情况下,可以通过少样本学习方法对其进行分类,使用meta baseline网络在5-way,1-shot任务中的分类准确率高达0.9475。     

基于深度学习的布匹疵点检测方法

为快速、准确检测布匹疵点,提出以深度学习目标检测框架YOLOv4为基础的布匹疵点检测方式,首先将5种常见疵点图像(吊经、百脚、结点、破洞、污渍)进行预处理,然后将图像输入到YOLOv4算法中进行分类。YOLOv4采用CSPDarknet53作为主干网络提取疵点特征,SPP模块、FPN+PAN的方式作为Neck层进行深层疵点特征提取,预测层采用3种尺度预测方式,对不同大小的疵点进行检测。研究结果表明:经600个测试集样本的验证,该方法对疵点图像的检测准确率达95%,检测单张疵点图像的速率为33 ms。与SSD、Faster R-CNN、YOLOv3方法进行比较,采用YOLOv4方法准确率更高,速度更快。     

“场域——惯习”视角下提升大学生自主学习能力策略研究——以《食品发酵与酿造工艺学》实践教学为例

《食品发酵与酿造工艺学》课程是烟台南山学院食品生物技术专业的方向模块课程,实践性和应用性非常强。以改进O2O平台、教学模式、师资与评价的场域因素和以个人主观意愿为主的惯习因素为基础,以“具有自主学习意向—引导自主学习动力—转化自主学习实践”和“无自主学习意向—激发自主学习动力—转化自主学习实践”为主线,从“场域—惯习”视角下分析提升大学生自主学习能力的策略。研究结果为培养大学生综合素质提供理论依据和决策参考。     

灵活运用“电大在线”,优化网络学习资源发布方式

通过实例,给出了“电大在线”下的优化网络学习资源发布方式.实践证明,该方法对激发学生的学习积极性起到了促进作用.