Abstract As a natural agricultural product, honey is favored by consumers, and its variety and adulteration have a huge impact on the quality. Acacia honey, red jujube honey and rape honey were used as experimental objects, and their spectral reflectance curves were obtained through a near-infrared spectral image acquisition system. Spectral features were extracted from the preprocessed spectral reflectance curves, and a honey variety classification model based on near-infrared spectral features was established by machine learning. After statistical analysis, Principal Component Analysis Support Vector Machine after processing data through Successive Projections Algorithm (SPA-SVM) is the optimal classification model for three varieties of acacia honey, red jujube honey and rape honey, and the correct rate of honey variety classification reaches 95.83%. The spectral reflectance curve was used to establish a honey adulteration identification model based on the partial least squares-discriiminate analysis (PLS-DA), and the classification accuracy was 97.92% in the test set.

This study analyses the influence and infection of traditional Chinese culture, starting from the cultural influence of ancient Chinese poetry and literature, and explores the impact and healing effect of traditional Chinese poetry and literature on college students' psychological anxiety. Combining with traditional Chinese culture, it proposes intervention and treatment strategies for college students' psychological anxiety. Through volunteer recruitment, 100 college students were recruited for comparative experiments, and the subjects were divided into an experimental group and a control group. The experimental group participants regularly participate in Chinese ancient poetry and literature appreciation courses during the experimental period, and form an ancient poetry and literature learning group for discussion and learning. Research has found that psychological anxiety is a common psychological problem among contemporary college students, with most of them experiencing varying degrees of psychological anxiety. After the experiment, the number of patients with severe anxiety disorder decreased by 64.21%, while the number of patients with moderate anxiety disorder decreased by 57.36%. Under the artistic influence of traditional Chinese culture, the anxiety state of students with mental anxiety has been significantly improved, and the overall satisfaction score of students with treatment intervention plans is relatively high. CONTRIBUTION: This study uses the profound historical heritage of Chinese ancient poetry and literature to help contemporary college students adjust their psychological state and reach the psychological adjustment under the infection of Chinese tradition culture. During the learning and appreciation of Chinese ancient poetry, literature and culture, students can comprehend the literature advancement in Chinese society, also influenced by the excellent traditional Chinese culture, for enhancing the humanistic quality and mental health level. The results of this study can be utilised by scholars in the field of the psychology of religion and public theology

ABSTRACT Introduction: Basketball players depend on excellent explosive power in the lower limbs for training and competition activities such as starting, braking, accelerating, decelerating, running, and jumping instantly and quickly. The level of Chinese athletes in this aspect is lower than world powers, and formulating training focused on explosive strength can enhance the training of these athletes. Objective: Study the effects of stretching on lower limb strength in basketball athletes. Methods: 20 young male basketball players selected as volunteers for the research were randomly divided into an experimental and control group, with 10 people in each group for retrospective analysis. The effect of rapid stretching compound training on the explosive power of lower limbs in basketball players was evaluated using the comparative method of literature data, expert interviews, experimental methods, and mathematical statistics. Results: After 8 weeks of training, the scores of each test index in the control group were significantly improved, including the standing jump and long-distance scores (P < 0.01). Unipodal takeoff and post-run long-range scores were significantly improved (P < 0.05). Conclusion: Both traditional resistance and compound lower limb stretching training can improve explosive power in young basketball players, but compound training showed more prominent results. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

RESUMEN Introducción: Los jugadores de baloncesto dependen de una excelente potencia explosiva en los miembros inferiores para las actividades de entrenamiento y competición, como arrancar, frenar, acelerar, desacelerar, correr y saltar de forma instantánea y rápida. El nivel de los atletas chinos en este aspecto es inferior al de las potencias mundiales y la formulación de un entrenamiento centrado en la fuerza explosiva puede mejorar la formación de estos atletas. Objetivo: Estudiar los efectos de los estiramientos en la fuerza de las extremidades inferiores en atletas de baloncesto. Métodos: 20 jóvenes jugadores de baloncesto seleccionados como voluntarios para la investigación fueron divididos aleatoriamente en grupo experimental y grupo de control, con 10 personas en cada grupo para el análisis retrospectivo. Se evaluó el efecto del entrenamiento compuesto de estiramiento rápido sobre la potencia explosiva de las extremidades inferiores de los jugadores de baloncesto mediante el método comparativo de datos bibliográficos, entrevistas a expertos, métodos experimentales y estadística matemática. Resultados: Después de 8 semanas de entrenamiento, las puntuaciones de cada índice de prueba en el grupo de control mejoraron significativamente, incluyendo las puntuaciones de salto de pie y de larga distancia (P < 0,01). Las puntuaciones de despegue unipodal y de largo alcance tras la carrera mejoraron significativamente (P < 0,05). Conclusión: Tanto el entrenamiento de resistencia tradicional como el entrenamiento compuesto de estiramiento de las extremidades inferiores pueden mejorar la potencia explosiva en jóvenes jugadores de baloncesto, pero el entrenamiento compuesto mostró mayor protagonismo en sus resultados. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

RESUMO Introdução: Os jogadores de basquetebol dependem de um excelente poder explosivo nos membros inferiores para as atividades de treinamento e competição como iniciar, frear, acelerar, desacelerar, correr e pular instantânea e rapidamente. O nível dos atletas chineses neste aspecto é inferior ao de potências mundiais e a formulação de um treinamento focado em força explosiva pode aprimorar o treinamento desses atletas. Objetivo: Estudar os efeitos do alongamento sobre a força dos membros inferiores nos atletas de basquetebol. Métodos: 20 jovens jogadores de basquete masculino selecionados como voluntários para a pesquisa foram divididos aleatoriamente em grupo experimental e grupo de controle, com 10 pessoas em cada grupo para análise retrospectiva. O efeito do treinamento composto de alongamento rápido sobre o poder explosivo dos membros inferiores dos jogadores de basquetebol foi avaliado usando o método comparativo de dados da literatura, entrevistas com especialistas, métodos experimentais e estatísticas matemáticas. Resultados: Após 8 semanas de treinamento, as pontuações de cada índice de teste no grupo de controle foram significantemente aprimoradas, incluindo o salto em pé e as pontuações de longa distância (P < 0,01). A decolagem unipodal e as pontuações de longo alcance pós corrida foram significativamente melhoradas (P<0.05). Conclusão: Tanto o treinamento tradicional de resistência quanto o treinamento composto de alongamento dos membros inferiores podem melhorar o poder explosivo nos jovens jogadores de basquete, porém o treinamento composto apresentou maior destaque em seus resultados. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

Abstract In order to reduce post-harvest losses, the classification of fresh apples is crucial. Taking the hierarchical transmission control system as the object, the research was carried out on the verification of the bus network can flexibly expand the motor equipment, the stable and reliable operation of the motor, and the accuracy of Apple's classification. Combine Labview virtual instrument technology to realize the design of Apple's hierarchical transmission control system based on Controller Area Network technology. Fuzzy PID and traditional PID algorithms are used to simulate and realize the operation of brushless DC motor, and compare the advantages of brushless DC motor control based on fuzzy PID to ensure the safe and stable operation of the system. Using the machine learning algorithms model for color detection, the Support Vector Machine algorithm model finally achieved the classification of the three types of apple samples with a recognition rate of 96.7%.

Abstract Prediction of seed vigor based on hyperspectral peant. The traditional method is time-consuming and laborious to detect seed vigor. At the same time, the accuracy of the detection result is not high, and it will cause damage to the seed itself. Therefore, in order to achieve rapid and non-destructive detection of peanut seed vigor, the test was performed with original health, artificial aging for 24h and Peanut seeds with different vigor gradients at 72 hours were used as the research samples. Hyperspectral images with a wavelength range of 387~1035 nm were collected, and the image of the central part of the peanut seeds with a pixel size of 60 × 60 after correction was intercepted and the average reflectance value was calculated. After a combination of processing analysis, characteristic band processing, and model selection, a hyperspectral prediction system with the highest correlation to the viability of extracted peanut seeds was finally established. Experiments shown that the combination of hyperspectral imaging technology and the MF-LightGBM-RF model had the best performance, with a prediction accuracy of 92.59% and a fitting time of 1.77s, which simplifies the model and improves efficiency.

Abstract The classification algorithms of different peanut varieties were studied based on hyperspectral imaging technology. Firstly, the spectral images of five peanut species were collected by hyperspectral instrument produced by Zhuolihanguang Co., LTD. Then SpacVIEW was used to correct the spectral images in black and white, and ENVI5.1 was used to extract the interest in the spectral image of each peanut and calculate the mean spectral reflection value of the region. The spectral characteristic curves of the five peanut samples all showed certain differences, which lays a foundation for the feasibility of modeling in the next step. In order to eliminate the influence of non-quality factor information in hyperspectral spectral data, a variety of data preprocessing methods were used to eliminate noise in the original spectral data, and XGBoost, LightGBM, CatBoost and GBDT algorithms were used to extract feature bands. XGBoost and LightGBM were then used for classification modeling of extracted feature bands. In the classification model, both XGBoost and LightGBM can reach 99.33%, while other performance evaluation indexes cannot distinguish these two models well. Therefore, Optuna algorithm was selected to optimize the two algorithms respectively. After optimization, both LightGBM and XGBoost have improved to varying degrees, but LightGBM is relatively obvious, especially in fit_time, which is 11 times faster than XGBoost and 16 times faster than before optimization. Therefore, the best classification algorithm selected in this study is MF-LightGBM-LightGBM-Optuna-LightGBM. The research of peanut classification method provides a strong theoretical basis and technical support for the revitalization of rural industry, the integration of peanut agriculture and industry and the acceleration of the modernization of agricultural industry system, production system and management system.

Abstract This study investigated the hyperspectral reflectance response of time series generated during oven drying to changes in the moisture content of potato tubers. Seventeen preprocessing methods were used to eliminate the influence of spectral noise on the spectral characteristic curve. Algorithms such as CatBoost, LightGBM, and XGBoost are used to obtain the first 40 effective characteristic spectra of hyperspectral images, which reduces the redundancy of data and improves the prediction accuracy. The water content prediction model of potato tubers was established by using the selected characteristic bands. The results showed that the combined model based on Lasso and XGBoost algorithm had the strongest prediction ability. The best model is MF-Lasso-XGBoost, which has R2 value of 0.8908, Rmse of 0.0610, Mdae of 0.0389, and R2cv of 0.8448. This research can provide reference for the detection of potato moisture content and theoretical basis for the development of crop moisture detector.

Abstract Peanut storage time affected the quality of peanut seed sowing and germination and also affected the taste of edible peanuts. With the increase of peanut storage time, the total amount of water and amino acids decreased, and peanuts appeared moldy. The artificial judgment of peanut storage time mostly relied on visual classification to evaluate the color, which leads to large differences in color classifications between observers. This research was conducted to determine the fresh state of peanuts during storage based on the hyperspectral imaging (HSI) technology, and to identify the storage time of peanuts through hyperspectral images (387~1035 nm). Three models, two preprocessing methods, and two feature band extraction methods were combined. The experimental results shows that the DT-MF-Catboost model was the best method to detect the storage time of peanuts, and its accuracy of identifying the storage time of peanuts was 97.53%. Studies have shown that HSI has great potential in classifying the freshness and identification of peanuts, and provides a basis for non-destructive testing classification as well as grading of peanuts during storage.

Abstract In order to realize the rapid nondestructive detection of mildew peanut in the process of peanuts storage, hyperspectral imaging technology was proposed to detect mildew peanut. A total of 200 peanuts were selected from 5 kinds of peanuts purchased in the market for moldy treatment, and the remaining 400 peanuts were kept sterile. After completion, samples were collected with a hyperspectral instrument to obtain spectral data of the samples. According to the characteristics of the data, 10 pre-processing algorithms were used to de-noise the data, and Median Filtering (MF) had the best effect, with the recognition accuracy reaching 97.7%. GBDT, LightGBM, CatBoost and XGBoost algorithms were used to extract important feature bands in the spectral data pre-processed by MF. GBDT, LightGBM, CatBoost and XGBoost algorithms were used to model the extracted feature bands. The results showed that LightGBM is the best algorithm with a detection rate of 99.10%. Optuna algorithm was used to tune its parameters. Compared with the previous model, the running time of the optimized model was improved by about 0.25 s. The results showed that hyperspectral imaging provides an efficient and nondestructive method for detecting mildew in peanut storage.

RESUMO Objetivo: Nosso objetivo foi avaliar a associação entre alfabetização em saúde e comportamentos de estilo de vida para intervir entre estudantes universitários chineses. Método: O questionário Chinese eHealth Literacy Scale (C-eHEALS) foi usado para investigar o nível de alfabetização em saúde e a associação com comportamentos de estilo de vida entre estudantes universitários chineses. O teste t de amostra independente e o coeficiente de correlação de Pearson foram usados pelo software estatístico SPSS v20. Resultados: Na primeira etapa, participaram 5.151 estudantes universitários, sendo 71,46% do sexo feminino e 28,54% do sexo masculino, com idades entre 18 e 22 anos (93,13%). Quatro comportamentos de estilo de vida (exercícios, fumar, beber e dormir) foram todos significativamente correlacionados com os escores de alfabetização em saúde e demonstraram diferenças significativas. Na segunda investigação (N = 2.939), a pontuação média de alfabetização em saúde foi de 31,64 ± 6,44, uma melhoria notável em comparação com a primeira investigação. Conclusão Aqueles do grupo com pontuações altas de alfabetização em saúde têm um estilo de vida mais saudável que aqueles do grupo com pontuação baixa. A formação em recursos relacionados com a saúde é uma medida positiva para melhorar a alfabetização em saúde dos estudantes universitários.

ABSTRACT Objective: Our aim was to evaluate the association between eHealth literacy and lifestyle behaviors to intervene among Chinese university students. Method: The Chinese eHealth Literacy Scale (C-eHEALS) questionnaire was used to investigate the eHealth literacy level and association with lifestyle behaviors among Chinese university students. Independent sample t-test and Pearson’s correlation coefficient were used by statistical software SPSS v20. Results: In the first round, 5,151 university students participated in the study, including 71.46% female and 28.54% male, aged 18–22 (93.13%).The average eHealth literacy score was 26.81 ± 5.83. Four lifestyle behaviors (e.g., exercise, smoking, drinking and sleeping) were all significantly correlated with eHealth literacy scores and demonstrated significant differences. In the second investigation (N = 2,939), the average eHealth literacy score was 31.64 ± 6.44, a notable improvement compared with the first investigation. Conclusion: Those in the group with high eHealth literacy scores have a healthier lifestyle than those in the low-score group. Training in eHealth-related resources is a positive measure to improve university students’ eHealth literacy.

RESUMEN Objetivo: Evaluar la asociación entre la alfabetización en salud y los comportamientos de estilo de vida para las intervenciones de estudiantes universitarios chinos. Método: Para investigar el nivel de alfabetización en salud y su asociación con los comportamientos de estilo de vida se utilizó el cuestionario Escala de Alfabetización China en Cibermedicina (C-eHEALS). La prueba t de la muestra independiente y el coeficiente de correlación de Pearson se llevaron a cabo con el software estadístico SPSS v20. Resultados: En la primera etapa participaron 5.151 estudiantes universitarios, 71,46% mujeres y 28,54% hombres, con edades comprendidas entre los 18 y los 22 años (93,13%). Cuatro conductas de estilo de vida (ejercicio, fumar, beber y dormir) se correlacionaron significativamente con las puntuaciones de Alfabetización en Salud y mostraron diferencias significativas. En la segunda investigación (N = 2.939), la puntuación media de la alfabetización sanitaria fue de 31,64 ± 6,44, lo que supone una notable mejora en comparación con la primera investigación. Conclusión: Los estudiantes del grupo con puntuación alta de alfabetización en salud tienen un estilo de vida más saludable que las del grupo con puntuación baja. La instrucción sobre recursos relacionados con la salud es una medida positiva para mejorar la alfabetización sanitaria de los estudiantes universitarios.

Abstract In this study, tensile strength, slicing, and infrared characteristics were evaluated to determine the changes in ramen dough and constituent proteins during production by hand. The results showed that two variables played important roles during the ramen-making process: the frequency of ramen agent additions and the method of ramen making. After two additions of the ramen agent to the dough, the tensile strength increased to the maximum value. Moreover, the ordered secondary structure of the protein improved, and the starch granules and protein molecules were arranged in an orderly fashion.

Abstract Turmeric is a natural active substance extracted from the Zingiberaceae plant, containing a variety of derivatives, the main component being curcumin. Curcumin has a wide range of sources, low cost, and has strong antioxidant, anti-inflammatory, anti-cancer, antibacterial and other physiological functions, but it has problems such as poor water solubility, poor stability, and low bioavailability. There are certain interactions (hydrophobic interactions, electrostatic interactions, hydrogen bonds, etc.) between curcumin and bio-based proteins or polysaccharides, which can be combined to form different encapsulation systems, which can effectively improve the poor water solubility, poor stability and intestinal problems such as low bioavailability. This article focuses on the types of natural bio-based encapsulation systems (emulsion, liposome, micelle, nanoparticles, gels, and microcapsules), mechanisms and their applications in the food field of curcumin.

Abstract In order to study the mechanism of arabinoxylan (AX) delaying the aging of steamed bread, the effects of AX on gelatinization, texture and starch crystallinity of steamed bread were analyzed. The results were as follows: as the storage time of steamed bread extended, the hardness and chewiness of steamed bread decreased successively in the control group, water extract AX group and enzyme extract AX group. The gelatinization of flour was decreased by both water and WEAX and EEAX, and a significant effect were observed in EEAX group. In the storage process of steamed bread, AX could inhibit the crystallinity rate of amylopectin in the freeze-dried powder of steamed bread, and the overall change range of ΔH was lower than that of control. The x-diffraction results showed that adding AX could reduce the crystallinity of steamed bread. Hence, it delays the retrogradation process and thus delay the aging of steamed bread. These results suggest that Arabinoxylan can be used as a novel additive in CSB industry, not only for the nutritional value, but also the anti-staling effect.

ABSTRACT Objective To evaluate usage of renal artery embolization (RAE) for renal injuries and discuss the indications for this treatment. Materials and Methods A retrospective study was performed evaluating the electronic medical records of all patients with renal trauma admitted to two major comprehensive hospitals in Shantou city from January 2006 to December 2015. Results There were 264 and 304 renal traumatic patients admitted to hospital A and B, respectively. LGRT was the reason for presentation in the majority of patients (522, 91.9%). A total of 534 (94.0%) patients were treated conservatively. RAE was performed in 9 patients from 2012 to 2015 at hospital A, including in 6 patients (6/9, 66.7%) with LGRT, and 3 patients (3/9, 33.3%) with HGRT. No patient underwent interventional therapy (RAE) at hospital B during the same period. No significant differences in the operative rate of hospital A were observed between the two time periods (2006-2011 and 2012-2015). The operative rate for LGRT between the two hospitals from 2006 to 2011 and 2012 to 2015 was not significantly different. Hospital A showed a significant decrease in the rate of conservative treatment for patients with LGRT. In the univariate and multivariate analyses, the AAST renal grade both were significantly associated with undergoing RAE. Conclusions LGRT was present in the majority of patients, and most cases of renal trauma could be treated with conservative treatment. RAE was well utilized for the treatment of renal trauma. However, some patients with LGRT were treated with unnecessary interventional therapy.

This study aimed to investigate whether the routine administration of escitalopram for three months would improve the prognosis of patients with ischemic stroke and decrease the plasma copeptin level. A total of 97 patients with acute cerebral infarction were randomly allocated to receive escitalopram (5-10 mg once per day, orally; n=49) or not to receive escitalopram (control group; n=48) for 12 weeks starting at 2-7 days after the onset of stroke. Both groups received conventional treatments, including physiotherapy and secondary prevention of stroke. The National Institutes of Health Stroke Scale (NIHSS) score was used to evaluate the disability of patients at the initial evaluation and at the monthly follow-up visits for three months. Impairment in the daily activities was assessed using the Barthel Index (BI), while cognitive impairment was assessed using Mini-Mental State Examination (MMSE) score. The psychiatric assessment included the administration of the Present State Examination modified to identify Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) symptoms of depression. The severity of depression was measured using the 17-item Hamilton Rating Scale for Depression (HAMD). During the 3-month follow-up period, 95 patients were included in the analysis (two patients withdrew from the escitalopram group). NIHSS and BI improvement at the 90th day were significantly greater in the escitalopram group (P<0.05), while HAMD and plasma copeptin levels significantly decreased, compared to the control group (P<0.01). In patients with acute ischemic stroke, the earlier administration of escitalopram for three months may improve neurological functional prognosis and decrease copeptin level.