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ObjectiveThe aim of this study was to establish a scientific and reasonable estimation and allocation model for food safety evaluation.MethodsA statistical method was used to estimate the total number of samples for evaluative sampling， a sample size allocation index system was established based on an analysis of the literature， the Delphi method was used to screen multiple factors， and a combination weight was assigned to each index based on the analytic hierarchy process and CRITIC method.ResultsBased on the estimated failure rate of food safety evaluation sampling in Province X， the total number of food safety evaluation samples in Province X was determined to be 7 800. The evaluation sampling size allocation index system covered two aspects of food varieties and testing areas and included the following eight indicators： sampling failure rate， dietary structure， the number of food safety incidents， attention， food consumption， consumption expenditure， and resident population. The allocation of samples for each food category in each prefecture-level city in the evaluative sampling test in Province X was obtained based on the weights of the calculated indicator combinations.ConclusionThe sample size allocation model can be used to allocate the sample size in a more objective and reasonable manner according to the food safety situation in each region and can be used as a reference for food safety evaluation sampling.

The hole edge crack monitoring of metal structures with holes is of great significance for ensuring flight safety and enhancing the reliability of aircraft structures. In order to monitor the crack growth at the hole edge, the fatigue loading test of porous aluminum alloy plate containing the corner crack at the hole edge is carried out, and the a-N curve of the test piece of porous aluminum alloy plate and the center wavelength offset of the optical fiber grating strain sensor during the crack growth at the hole edge are obtained. The damage identification algorithms such as envelope analysis method and BP neural network are used to process and analyze the test data. The monitoring model that can identify the crack growth at the hole edge with the center wavelength offset of the optical fiber grating strain sensor is established, and verified with test parts. The results show that the established monitoring model can effectively identify the propagation and penetration of the corner crack at the hole edge, and the accuracy of monitoring the propagation length of the corner crack at the hole edge has reached 97.2%, which can be applied to the ground fatigue test of the whole aircraft, aircraft structure health monitoring and other scenarios in the future.

Accurate workload prediction is the key to realize elastic resource management of cloud platform. Aiming at the problem that a large number of tasks with short running time achieve prediction in the cloud platform, which leads to the lack of training data of the forecasting model, a structured prediction of multivariable workload sequences (SP-MWS) method is proposed. It is based on the characteristics of intrinsic correlation among multiple resources consumed in the running of a single task, and the relationship of multi-dimensional workload sequences is explored to supplement the prediction information of small-scale sequence. Firstly, in order to obtain the related workload types, the maximum information coefficient (MIC) and information entropy are adopted to measure the correlation, and related workload types are selected. Secondly, for the selected multiple related workloads, trace-norm regularization multi-task learning (TNR-MTL) is introduced to construct prediction model to realize structural information mining of related workload sequences and complete prediction of multiple workloads simultaneously. Validated on Google cloud platform’s operational monitoring log dataset, the experimental results show that the proposed method can significantly increase model information; the decision-making basis of the prediction model is interpreted and the contribution of each variable to the prediction model is visualized. Comparative experiments show that, the proposed prediction method is better than the commonly used workload prediction methods in time performance and prediction accuracy.

Hyperglycemia-induced toxicity of neurons contributes to the pathogenesis and progression of diabetic neuropathy (DNP). High concentration glucose triggered reactive oxygen species (ROS) overproduction and induced cell apoptosis of neurons from dorsal root ganglion (DRG) in vitro. Currently, there is no effective therapeutic method to retard this devastating complication or neurotoxicity induced by high glucose. Insulin-like growth factor-1 (IGF-1) has multi-neurotrophic actions which need to be explored regarding its actions and mechanisms on relieving high glucose induced neurotoxicity. Herein, high concentration glucose was exposed to the DRG neurons in vitro. The effects of IGF-1 on relieving high glucose-induced neurotoxicity were evaluated. We illustrated that IGF-1 enhanced regeneration of neurites sent from DRG neuronal cell bodies and increased neuronal viability which inhibited by high glucose challenge. IGF-1 alleviated neuronal apoptosis caused by high glucose exposure. IGF-1 also suppressed the intracellular ROS overproduction and ATF3 expression upregulation which was induced by high glucose insult. The anti-neurotoxic effects of IGF-1 might be through restoration of prosurvival PI3K/Akt/S6K signaling. These data shed some light on the treatment of intractable DNP and suggested that IGF-1 might be a potential effective agent on relieving high glucose induced neurotoxicity.

Objective: To investigate the correlation between serum neopterin, homocysteine (Hcy) and the risk of developing ischemic stroke (IS) in patients with transient ischemic attack (TIA).

The construction of China’s management and prevention and control system regarding air pollutants in airport area is of great significance to improve the regional ambient air quality in Chinese cities. By analyzing the deficiencies of air pollution control in airport areas in China and sorting out the international experience in pollution control, this paper proposes to improve the standard system of aircraft engine emission, establish a database of aircraft engine emission coefficients, carry out technical research on assessment of atmospheric impact caused by aviation emission, and explore the multiple prevention and control paths of aircraft pollution.

Current learning platforms generally have problems such as fragmented knowledge, redundant information, and chaotic learning routes, which cannot meet learners' autonomous learning requirements. This paper designs a learning path recommendation system based on knowledge graphs by using the characteristics of knowledge graphs to structurally represent subject knowledge. The system uses the node centrality and node weight to expand the knowledge graph system, which can better express the structural relationship among knowledge. It applies the particle swarm fusion algorithm of multiple rounds of iterative simulated annealing to achieve the recommendation of learning paths. Furthermore, the system feeds back the students' learning situation to the teachers. Teachers check and fill in the gaps according to the performance of the learners in the teaching activities. Aiming at the weak links of students' knowledge points, the particle swarm intelligence algorithm is used to recommend learning paths and learning resources to fill in the gaps in a targeted manner.

Using the educational knowledge graph to express the logical characteristics of knowledge, this paper takes project-driven learning in the teaching of "Information Technology in Secondary Schools" as an example and studies the group cooperative teaching mode based on the educational knowledge graph. The relationship between knowledge points in subject courses is described in the form of a knowledge graph, and the learning activities of coordinating the cooperation of each group are completed through the integration process of the knowledge graph. The use of a group cooperation teaching mode in the classroom can not only build a collaborative knowledge system between teachers and students but also help to carry out project-driven learning. The application of the knowledge graph of "Information Technology in Middle School" in the classroom can better show the logic between knowledge, and its graphical structure can help students to structure the knowledge they have learned.

Shrimp tends to deteriorate during the refrigeration process. To monitor the freshness of shrimp during refrigeration, near-infrared (NIR) hyperspectral imaging was utilized to non-destructively identify the freshness of shrimp. In [...]

While the importance of motivation and engagement in L2 writing in higher education is well documented, research on L2 secondary students' English writing motivation and engagement remains scanty. This study used the adapted English Writing Motivation and Engagement Scale for High School (EW-MES-HS) and explored Chinese secondary students' motivation and engagement in English writing. A total of 2,205 students from 55 secondary schools across China participated in the study. The results revealed a multi-dimensional perspective of students' L2 writing motivation and engagement. Four distinct profiles of secondary L2 students' motivation and engagement were specified: the 'Unmotivated and disengaged', the 'Motivated and engaged', the 'Ambiguously motivated and engaged', and the "Ambivalently motivated and engaged." These findings argue against a dichotomous portrait of Chinese secondary EFL students as being either demotivated/disengaged or motivated/engaged in writing and shed new light on the nature of writing motivation and engagement in L2 writing contexts.

Following a sociocultural perspective, this vignette-based study explored Chinese master's students' emotions and emotion-regulation strategies in supervisor writing feedback situations. An instrument contained 17 vignettes was developed, validated and administered among 189 participants. Individual interviews with five participants were also conducted, and written materials were collected. The findings revealed that across the 17 hypothetical scenarios, positive emotion was the most reported emotional status, and Chinese master's students would be more likely to feel grateful, hopeful and excited, while contemptuous, bored and angry were the least reported. This study also identified a set of emotion-regulation strategies (i.e. task-related regulation, response regulation, cognitive regulation, attention deployment, co-regulation, and general response) used by students in handling their emotions in supervisory feedback situations. This study provides insights into the emotional dimension of supervisory feedback practices and concludes with pedagogical implications to enhance the wellbeing of postgraduate students in learning academic writing.

While abundant research has investigated the teaching and learning of English as a foreign language (EFL) writing in college contexts, there has been little examination of writing in primary and secondary school settings. It is important to understand the writing literacy development of young EFL learners and to explore instruction that supports their growth as writers. For research and pedagogical purposes, we conducted a review of 136 studies of EFL writing in primary and secondary school contexts from 2012 to 2019 concerning three themes: (1) contexts and participants, (2) research foci and theoretical orientations, and (3) research methodology and data sources. The findings offer a broad picture of the scholarship on EFL writing in school contexts over the last eight years and suggest future directions for researching and teaching EFL writing in primary and secondary school contexts.