bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Educational Guidance of College Students’ Career Planning Awareness in the Context of Informatization
Authors: Xiong Binru
Published: August 2024

The rapid development of science and technology has brought society into the era of digital intelligence, which not only changes people’s way of production and life but also brings unprecedented changes to practical courses such as career planning for college students. The study constructs a model of factors influencing college students’ career planning based on relevant theories of college students’ career planning education. After the correlation analysis and regression analysis of the career planning ability and the factors, as well as the difference analysis of the career planning ability of college students, the model of career planning education for college students based on SWOT analysis is proposed. There are significant correlations between family care support, career lectures, mentoring behavior, career information acquisition, and career planning ability (p-value is less than 0.005). The four independent variables have an impact coefficient of 0.186, 0.010, 0.092, and 0.291 on the career planning abilities of college students. P-value of significance of gender, major, age, and career counseling experience on each dimension of college students’ career planning is less than 0.05, and there is a significant difference between college students’ career planning ability in gender, major, age, and career counseling experience.
Informatization Development Strategy for Rural Financial Services
Authors: Liu Xiaowan
Published: August 2024

Promoting the development of rural financial informatization is an important magic weapon to help rural revitalization, and it is also a necessary way to comply with the trends of the times. This paper constructs a quantitative model of farmers’ investment behavior based on the VaR method and the Morning Star performance evaluation method to provide financial service institutions with ideas for financial product innovation in order to solve the current problems of the increasing level of rural financial service informatization but the uneven degree of informatization and the weak sense of innovation in the construction of rural financial service informatization. In order to make full use of rural financial service informatization resources and reduce the investment cost and time of farmers, this paper designs and implements the financial product recommendation algorithm based on the investment behavior of farmers using the AE_xDeepFFM recommendation algorithm. The analysis finds that farmers’ investment behavior is more significantly affected by economic and social value perception and social influence, and the path coefficients of the two on behavioral intention in the resultant model are 0.411 and 0.407 at the significant level, respectively. Effort expectation, on the other hand, indirectly affects the investment intention and behavior of farmers through performance expectation.
Deep Learning-Driven Real-Time Facial Expression Tracking and Analysis in Virtual Reality
Authors: Liu Yinuo
Published: August 2024

In this paper, we use VR equipment to collect relevant facial expression images and normalize the angle, scale, and gray scale of the collected images. The direction quantization of image features is realized by 3D gradient computation, and then the histogram of the direction gradient of each video sub-block is cascaded into the final HOG3D descriptor so as to complete the extraction of dynamic expression features. In view of the multi-dimensional problem of the features, it is proposed to use a principal component analysis algorithm to reduce their dimensionality and use a multi-layer perceptron and deep confidence network to jointly construct the facial expression tracking recognition model. The datasets are used to analyze real-time facial expression tracking in virtual reality. The results present that the verification correctness of both datasets A and B reaches the maximum at the 120th iteration. In contrast, the loss value reaches the equilibrium state quickly at the 40th iteration. The dynamic occlusion expression recognition rate of the deep confidence network on dataset A (66.52%) is higher than that of the CNN (62.74%), which fully demonstrates that the method of this paper is able to effectively improve the performance of real-time facial expression tracking performance in virtual reality. This study can help computers further understand human emotions through facial expressions, which is of great significance to the development of the human-computer interaction field.
Application and Path Exploration of PDCA Management Model in Higher Vocational Education Management
Authors: He Wenwen
Published: August 2024

With the rapid development of society, the total education demand for higher vocational colleges and universities is growing at an extremely fast rate, and the original education management mode can no longer meet the needs of higher vocational education in the new era. The PDCA management model is a continuous improvement model that can achieve the objective of continuous improvement processes and perfectly fits the needs of higher vocational education management. This paper introduces the support vector machine, an algorithm suitable for high-dimensional classification problems, into the PDCA management model to carry out a multidimensional analysis of vocational high school students’ behavioral data, optimizing the checking part of the PDCA management model so that the cycle can continue to play an ideal role. The results of the application of the prediction of academically abnormal students show that the total number of academically normal students is 12,823, the total number of academically abnormal students is 2,981, and the proportion of abnormal students in different schools can be as high as 34.82%, and as low as 12%. The SVM algorithm, in the case of the imbalance between the proportion of academically abnormal and academically normal students, the model is still able to find out the majority of the students with abnormal studies, and it plays a central role in the PDCA management model to make the management of higher vocational education more perfect. By playing a central role, it enhances the management of higher education and creates a unique management path.
Construction and Application of Deep Learning Models for Evaluating the Effectiveness of International Communication of Chinese Music
Authors: Wang Mingjie , Qi Xuejing
Published: August 2024

In recent years, research on deep learning has become an important topic in artificial intelligence, has achieved excellent results in several evaluation fields, and has become a cutting-edge method for solving various evaluation problems. For this reason, this paper explores the effects of China’s international music communication from three dimensions: cognition, attitude, and behavior, and establishes an evaluation system containing 11 secondary indicators. Then, an assessment model of the music communication effect is constructed using the deep learning network method. The constructed assessment model was used to evaluate the impact of international communication on Chinese music. According to the output of the model, it was determined that the communication power of the selected 1,120 Chinese music songs belonged to the solid and average levels, accounting for 71.34% of the total, and the comprehensive evaluation score was between 2.5 and 4.3. This indicates that Chinese music has achieved better dissemination effectiveness and influence with the help of various music platforms.
A Practical Approach of Integrating Traditional Cultural Elements into Art and Design Talent Cultivation in Colleges and Universities under the Background of Deep Learning
Authors: Jiang Meng
Published: August 2024

Chinese traditional culture has rich cultural connotations, which has an important role in promoting the development of modern art and design education. The study examines the application of deep learning technology in art and design education through the analysis of several target design colleges and universities based on the background of deep learning. Then, it starts from the creation of art images based on traditional cultural style migration, constructs a style migration model based on a convolutional neural network, and evaluates the effect of style migration images of traditional cultural elements. Create teaching experiments to investigate the utilization of deep learning technology in art and design education. At present, teachers and students still need to improve their cognition of the use of deep learning technology in art design, and the use of deep learning technology in art design has been popularized to a certain extent, with computer vision technology (90.7%) and natural language understanding technology (71.2%) being the most used. The images generated by the style migration model integrating traditional cultural elements have high PSNR values (12~20) and SSIM values (0.375~0.633), and the performance of the students using the model is 6.98% higher than that of the control students, which reflects the validity and feasibility of the application of the model in the creation of art design. It is necessary to optimize the curriculum system, enrich the teaching mode, cultivate the appreciation ability, carry out practical activities and create a good atmosphere and other dimensions to promote the talent cultivation of traditional culture in art design.
Dual-line Cultivation of Students’ Professional Skills and Creative Thinking in Vocational Education in the Context of Emerging Technologies
Authors: Li Ke , Zhang Li
Published: August 2024

In order to improve the teaching quality of vocational education, explore the vocational education model that meets the market demand, and build a distinctive vocational education system, it plays an important role in analyzing the research trend of vocational education. The process of text mining is first described in this paper, which primarily involves text data acquisition, text preprocessing, latent information extraction, and data statistical analysis. Then, in view of the shortcomings of the traditional K-means clustering algorithm, the algorithm is improved on this basis, and DT-Kmeans clustering is used to study and verify the effectiveness of the algorithm. The training tendency of each vocational education school was investigated. The keyword feature extraction was completed, and the integrated education model of each vocational education school was relatively unified. Among the top five keywords, each school had a high bias towards “natural science” and “ideological and political education”. Eighteen schools (90%) believe that “ideological and political education” occupies a “very important” position in student training. Two schools (10 percent) considered it “relatively important”.
Application of Artificial Intelligence Technology in Smart Building Integrated Management Platform under Big Data Environment
Authors: Wu Zheng
Published: August 2024

The rapid development of the construction industry has led to a wider application of artificial intelligence technology, and the application of this technology to the comprehensive management of intelligent buildings can promote the construction of intelligent construction sites and improve the level of quality management. In this paper, on the basis of elaborating on the intelligent building design, the framework of the intelligent building comprehensive management platform is built by combining 5D-BIM technology and artificial intelligence technology, and engineering cost modeling is carried out based on the whole process control of engineering cost. The engineering cost prediction model is established based on the BP neural network, and a genetic algorithm is introduced to optimize the initial threshold of the model so as to obtain more accurate prediction results. To verify the effectiveness of the intelligent building integrated management platform application, data analysis is carried out across three dimensions: engineering cost control, prediction, and application. The whole process of cost control makes the peak value of cost-effectiveness reach 4.25*108 yuan, the average value of project cost reduction reaches 78.68%, and the relative error of project cost prediction results minimizes to only 1.77%. The process of processing project information was shortened and improved by 9.15% and 8.06%, respectively, and the backlog reduction rate of project materials could be reached by 24.76%. The intelligent building integrated management platform that utilizes artificial intelligence technology promotes construction project intelligence and effectively reduces construction costs.
Research on Optimization Strategies of Student Financial Aid System in Colleges and Universities Based on Multi-Objective Decision-Making Model
Authors: Zhou Jing
Published: August 2024

The identification of economically disadvantaged students in colleges and universities is the primary link in the college and university financial aid system, and it is the prerequisite, foundation, and guarantee for the implementation of various national financial aid policies and measures. This paper takes the Q college student financial aid system as the research object and discusses the authenticity of the information, the standard qualitative and quantitative difficulty in the determination of the work of standardized operation, and other problems in the determination of the work in depth. By analyzing the operation level of the student financial aid system of the university and according to the existing problems of the current financial aid system, a multi-objective decision-making model is designed and optimized, and the qualitative evaluation in the fuzzy multi-objective decision-making method is used to consider multiple factors in the determination process, so as to ensure the accuracy and fairness of the financial aid. This paper proposes an optimization strategy for the student financial aid system in colleges and universities based on the model’s identification results. A questionnaire survey is re-conducted on Q colleges and universities that use the optimized student financial aid system. The results show that the optimized student financial aid system is more helpful for students’ academic lives.
A Study of Reinforcement Learning Algorithms for Artistic Creation Guidance in Advertising Design in Virtual Reality Environments
Authors: Zhu Leyi
Published: August 2024

The innovative application of virtual reality technology in advertising design greatly promotes the development of advertising design work in the media field and also provides a new guiding direction for art creation in advertising design. After analyzing the advantages and performance of VR technology applied in advertising design, the article elaborates on the use of art creation rules and related skills in advertising design. To facilitate the guidance of art creation in advertising design within a virtual reality environment, this paper employs chunked feature-matching technology to visually process print advertisement images, thereby providing an interactive design process for advertisements in virtual reality. Then, using a reinforcement learning algorithm as a framework, we combine the DDPG strategy with a neural renderer to construct a virtual reality advertisement design art creation style migration model and conduct design experiments to verify its effectiveness. Finally, we conduct an experience evaluation analysis for the design of virtual reality advertisements. The model in this paper converges after 225 epochs, at which time the loss value is 17.09% lower than that of the CycleGAN model; the mean value of the advertisement image style migration score is 4.08; and the mean value of the comprehensive score of the on-campus test for virtual reality advertisement design is 8.12. Reinforcement learning not only facilitates the art creation guidance of advertisement design in a virtual reality environment but also enhances the user’s understanding of the advertisement design content, thereby laying the foundation for improving the communication effect of virtual advertisements.
Optimizing Collaborative Filtering Recommendation Algorithms for Knowledge Sharing in Libraries
Authors: Ji Ying
Published: August 2024

With the rapid development of information technology, how to enable teachers and students to quickly find and filter information of interest in massive collections has become a hot issue for many scholars. This paper enhances the traditional collaborative filtering algorithm by utilizing the knowledge-sharing model. Specifically, we calculate similarity using keyword information from items and dynamic information from users based on similarity calculations related to item features and user attributes. The relevant information about users and items is fully utilized to successfully alleviate the problem of new items and new users, and the entire process of collaborative filtering recommendations for libraries is designed. The improved collaborative filtering-based algorithm can achieve a recommendation accuracy of more than 60% and recommend more accurate books to users. The average recommendation rate of the book recommendation algorithm is 0.056 higher than the average recommendation rate of other recommender systems, indicating a higher recommendation rate that can better match the needs of users and alleviate the cold-start problem to a certain extent.
Optimization and Upgrading of Big Data Processing Techniques in High Performance Computing Environments
Authors: Li Jianguang
Published: August 2024

Currently, high-performance computing environments are facing challenges such as limited resources and an increasing number of users. In order to improve the utilization of environmental resources, this paper proposes a high-performance hybrid computing architecture based on big data processing technology, which is constructed on the basis of an HDFS distributed system combined with MapReduce framework and GPU virtualization technology. The PageRank algorithm is utilized to evaluate the performance of rack nodes in the high-performance computing environment, and the evaluation results are applied to design an improvement strategy for task allocation and scheduling through the MapReduce framework. A division function is introduced to dynamically divide the Reduce data, and an approximate sampling method based on sampling information is proposed to guide the setting of the number of Reduce. The IB algorithm is used to cluster the labeled files, and a rack-aware strategy is designed based on HDFS to achieve resource load balancing. The MapReduce-based task allocation scheduling scheme has a reduction in job execution time of up to 39.83% compared to delayed scheduling. The dynamic partitioning design can achieve data load balancing by partitioning 5.382% of the groups and migrating 1.207% of the KVs if the data skew is 1.0. Dynamic balancing of environmental resources and resource scheduling optimization in high-performance computing environments can be achieved through the use of big data processing techniques.
Research on the Innovation Path of Teaching Methods of Civics Classes in Colleges and Universities Based on K-means Cluster Analysis
Authors: Huang Aiwa , Li Ni , Chen Jinyan
Published: August 2024

The innovative design of teaching methods of Civics classes in colleges and universities is an effective measure to help the teaching of Civics classes in colleges and universities. In this paper, the significance of innovative Civics teaching methods is addressed, and a novel path for teaching Civics courses in colleges and universities is proposed. Through feature selection, the K-Means clustering algorithm is optimized, and after optimal selection of the initial clustering center, balanced discriminant function, and combing of the optimization process, the model is applied to the actual innovation of Civics and Political Science teaching, quantitatively assessing the behavioral characteristics of the students and constructing the prediction model to achieve dynamic monitoring of students’ performance. The empirical teaching analysis method is aimed at quantitatively assessing the path proposed in this paper. The clustering results show that consistent with the preset, the model divides students’ learning behavioral characteristics into four categories with clear boundaries and good clustering effect, and most of the student’s grades are concentrated around 60-80 points, according to which the teachers can adjust their teaching strategies in time to improve the teaching effect. Through the control experiment, we know that for the students who have gone through the innovative Civics teaching mode, the mean value of Civics achievement is 71.594, which is 19.329 points higher than the students who have studied in traditional Civics teaching, which is confirmed by the P-value in the t-test of independence which is less than 0.05. It indicates that the innovative teaching method for civics has a significant effect on improving students’ civics achievement.
Research on Feature Extraction Strategies for Cybercrime Crimes Combined with Deep Learning and Their Probabilistic Models
Authors: Lei Yang , Liao Lingyu
Published: August 2024

In this paper, in order to improve the accuracy and precision of the detection and identification of cybercrime cases, eliminating the incomplete and ambiguous information obtained from a single source of evidence, combined with the procedural steps of the sampling and forensics for the detection of cybercrime cases, a cybercrime detection and control model based on the fuzzy reasoning and the improvement of the D-S algorithm is proposed. Combined with the application of the improved D-S evidence theory in the fusion of cyber evidence, the weighted Bayes is combined to achieve effective forensics of cybercrime evidence. The improved D-S evidence theory algorithm achieves a detection rate of 0.989 for network anomalous data, which has an obvious advantage in network data fusion over the no-preprocessing, original D-S evidence fusion algorithm. The intrusion path generation algorithm considers the intrusion risk of intrusion path IV5 to be the highest at 0.186 with the intrusion paths .
Research on Digital Transformation Mode Analysis and Brand Influence Enhancement Strategy of Shanxi Intangible Cultural Heritage Guangling Paper Cutting
Authors: Jia Qi
Published: August 2024

In this paper, through the collection and analysis of data, the art of Guangling paper-cutting is theoretically researched, and the general features and shapes of Guangling paper-cutting are summarized. In order to overcome the limitations of traditional algorithms in the extraction of features of Guangling paper-cutting, the combination of spatial pyramid matching and context-dependent histogram methods are used to extract the shape features of paper-cutting images with stronger differentiation. The support vector machine is used to solve the problem of recognizing and classifying the image patterns in the digitized display. The design of the digital promotion of the Shanxi Guangling paper-cutting brand is carried out. Research variables are designed to analyze the effect of digital transformation and promotion of paper-cutting brands. The results show that the discrepancy of Guangling paper-cutting features extracted by the algorithm in this paper is very low, the e1 difference is maintained within 0.1, and the total recognition rate of SVM on Guangling paper-cutting features can reach 88.06%, and the overall effect is more satisfactory, and the regression equation of the influence of paper-cutting = −0.807+0.111*history+0.122* style+0.234*paper-cutting+0.216*display+0.136 * linkage, and propose strategies to enhance the influence of paper-cutting brand. The technical methods used in this study guarantee the quality of the digital transformation of Guangdong paper-cutting from the source.
Temperature compensation study of infrared Sf6 gas sensor combining GA and wavelet neural network
Authors: Wang Qing , Johar Md Gapar Md , Tham Jacquline
Published: August 2024

Ambient temperature changes have a nonlinear effect on infrared SF6 gas sensors, which leads to SF6 gas leakage and affects the normal operation of equipment. In this paper, based on the infrared differential detection technology and Lambert-Beer law for quantitative detection, a dual-channel pyroelectric detector is constructed for detection and analysis by using 3.75μm the measurement filter and 10.85μm the reference filter. In order to eliminate the nonlinear effect of the temperature change of the detection environment on the infrared gas sensor, a temperature compensation model based on the GA-WNN fusion algorithm is proposed to compensate the measurement error due to the temperature change of the detection environment by using its good nonlinear mapping as well as generalization ability. The experimental results showed that the maximum measurement error decreased from 333.93 ppm without temperature compensation to 80 ppm after temperature compensation in the range of detecting ambient temperature of 15-4°C and SF6 gas concentration of 0-2000 ppm. This method eliminates the need for additional external equipment to maintain the gas chamber temperature in dynamic equilibrium, thus avoiding an increase in the size of the gas sensor itself and the cost of fabrication. Compared to the traditional compensation method, this method does not require solving the fitting parameters sequentially and determining the temperature compensation coefficients segmentally. This reduces the amount of calculation and simplifies the process of temperature compensation, resulting in an excellent compensation effect.
Research on Library Bibliographic Information Integration Technology Combined with Group Intelligence
Authors: Xin Lichun
Published: August 2024

There are abundant bibliographic resources in libraries, but the resource search platforms and search methods are different, which brings difficulties to readers in using and causes problems such as low resource utilization. In this paper, the search performance of the QPSO algorithm is improved by using reverse learning and dynamic group search method to get the QPSO-DGS algorithm, and then the MSP strategy is introduced to synthesize the MSP-QPSO-DGS algorithm, which realizes the parallelization of group intelligence algorithm in the integration of bibliographic information. Subsequently, a system for integrating bibliographic information in a library is constructed using the MSP-QPSO-DGS algorithm. According to the performance test, the MSP-QPSO-DGS algorithm suggested in this paper has a superior convergence accuracy than the optimization results of other population intelligence algorithms. Meanwhile, it is found that the system proposed in this paper has an average checking completeness rate and checking accuracy rate of 93.01% and 90.85% in bibliographic information integration, respectively, and has achieved good results in practical applications. This paper has made meaningful attempts and explored to provide efficient and accurate library bibliographic information integration techniques, and the proposed system provides a reference for research in this field.
Quantum Information Technology Facilitates Innovative Research on Traditional Painting Art Styles
Authors: Xu Jing
Published: August 2024

The continuous progress of the network and big data has brought far-reaching influence and potential opportunities to traditional painting design, and at the same time, it continues to shape the content and form of its artistic style. This paper employs the quantum image enhancement algorithm to transform the traditional painting image into a quantum pure state. Subsequently, it segments each pixel to extract edge information, thereby constructing the traditional painting image state. Next, we employ the quantum image color enhancement algorithm to amplify the color aesthetics of the extracted image state, thereby fostering innovation. Finally, this paper proposes an innovative approach to traditional painting styles using quantum information technology. This paper proposes a quantum image enhancement algorithm that outperforms the classical program in all quality indicators after processing traditional painting images, thereby establishing a theoretical foundation for future research. The study found that traditional paintings made with the help of a quantum image enhancement algorithm have a higher quality of art style innovation and artistic value. The study also found that both types of works, plants (4.37 points) and myths (4.50 points), got higher scores on the tests. This paper brings a fresh perspective to the creation of traditional painting art, paving the way for a more intelligent and diverse future for this genre.
Markov Decision Process Modeling in Pharmacoeconomics with Application Perspectives
Authors: Xu Yan , Wu Qide
Published: August 2024

Aiming at the complexity of the problems of risk prediction and drug cost and utility in pharmacoeconomics, this paper proposes the application of the Markov decision model to pharmacoeconomics, and based on this, the solution method of pharmacoeconomic optimization is proposed. After summarizing the advantages and purposes of Markov’s application in pharmacoeconomics, the Markov decision process is established from four aspects: state of the world, action, transfer, and benefit function. The Lagrangian function is constructed with the expectation of the maximum long-term drug benefit. The solution problem is converted into an unconstrained problem, and the objective solution is carried out using reinforcement learning methods. The improved algorithm’s convergence is examined. It is found that the optimized Markov decision-making algorithm obtains a cumulative payoff value of 85, which is 25 higher than that obtained by the Markov decision-making algorithm, and the Markov decision-making model is more effective in evaluating the economics of drugs or treatment measures. Evaluating the long-term benefits of therapeutic measures on cost, survival, and quality of life in sick populations has promising applications as well.
Understanding motivational determinants of gastronomic tourism during peak seasons. Empirical evidence from Latacunga City in Central Ecuador
Authors: Rodas Alejandra , Benavides Lucia , Armijos Sara , Andrade Andrea , Guamán Guevara Adolfo Ricardo , Guamán-Guevara Fabricio
Published: August 2024

This empirical study examines the motivational determinants driving the consumption of traditional local food and beverages in Latacunga in Central Ecuador (South America). This geographical area embraces a rich cultural and historical heritage, making it a year-round destination for tourists looking to experience its unique local cuisine and festivals. An online survey was conducted between September 2021 and February 2022, during which 445 valid questionnaires were collected; these were quantitatively analysed using binary logistic regression analysis. Model-based findings revealed that age, taste, health and safety concerns, cultural experience, and expenditure were the most significant factors influencing the consumption of traditional local food and beverages. This information will help understand tourists’ behaviour concerning gastronomic tourism, and help develop optimal positioning, branding, and marketing strategies for sustainable development at top-ranking destinations, particularly cities in Central Ecuador and other international cities featuring similar tourism characteristics.
Using Blockchain Technology at Supply Chain: The Sample of Migros
Authors: Cömert Menekşe , Kanoğlu Esra , Güleç Hakan , Kaya Münevver
Published: August 2024

This study aims to determine the functionality and benefits of blockchain technology in food procurement. Within the scope of the study, Migros Trade Inc., a retail food supply company implementing blockchain technology in Türkiye, was examined as a case study. The study employed a qualitative research case study design, asking expert participants from Istanbul and Izmir to give their opinions on pre-designed themes, and conducting descriptive analyses of the data collected. The themes of the research are food supply chain, good agricultural practices, sustainability in food, blockchain applications in food supply and food safety. At the end of the study, it was found that the transparency and traceability principles of blockchain have a positive impact on consumers and supply chain stakeholders. However, challenges such as technical infrastructure and performance, as well as the reasons for not starting the process directly from the field, were the problems experienced. The data shows that blockchain technology is an efficient system that should be expanded in the food supply chain.
Improving Bitter Gourd Growth and Yield in Different Soil Environments by Combining Biochar and Inorganic Fertilizer
Authors: Islam Md. Nazrul , Rabbani Mahbub , Malek Muhammad  Abdul , Khalifa Md. Sohag , Rahman Zillur , Orpa Nusrat Nawreen , Mannan Md. Abdul
Published: August 2024

A study using the assigned Complete Block Design with three replications was carried out at Hobigong, Bangladesh from January to August 2021 to investigate the impact of different combinations of organic and inorganic fertilizers on the growth and production of bitter gourd. The experiment employed five different combinations of organic and inorganic fertilizers, which are listed below: T1: 4 kg of organic fertilizer per plant, T2: 4 kg of organic fertilizer + 2 liters of cow urine + 2 liters of bc (biochar), T3: 2 liters of liquid bc (biochar)) + NPK (44 g urea + 43 g TSP (Triple Super Phosphate) + 77 g MoP (Muriate of Potash), T4: NPK (44 g urea + 43 g TSP + 77 g MoP), and T5: 4 kg of organic fertilizer + 2 liters of bc+ NPK (44 g urea + 43 g TSP + 77 g MoP) on three distinct soils in the villages of Kalonjhora, Madhabpur, and Jointure. The growth and yield of bitter gourd at different study locations were significantly affected by the application of both organic and inorganic fertilizers, according to the results. The results showed that the use of both organic and inorganic fertilizers had a significant effect on the development and yield of bitter gourd at the different study sites. Maximum germination rate (90%), at 45 DAS (days after sowing), longest plant (173.28 cm) at 100 DAS, maximum number, longest and heaviest fruit (6.30 number of fruits per plant, 15.51 cm and 82.50 g, respectively) were obtained from crops grown in Jointer village that were applied with 4 kg organic fertilizer + 2 liters bc + NPK (44 g urea + 43 g TSP + 77 g MOP). According to the previously described research, most development and yield characteristics of bitter gourd are improved when grown in a mixture treated with 4 kg organic fertilizer + 2 liters bc + NPK (44 g urea) + 43 g of TSP + 77 g of MoP.
Contribution of Some Agro-Food Processing By-products to Chicken Sausages
Authors: Akşit Zeynep , Gençcelep Hüseyin
Published: August 2024

In this study, some agro-food processing by-products were evaluated as novel food ingredients, that meet the consumer's demand for natural ingredients, and their contributions to chicken-type sausage production were examined. Sausages were formulated with 3% quince waste (QS3), 3% grapefruit waste (GS3), 2% tomato waste (TS2), and 3% tomato waste (TS3). Other ingredients were fresh breast chicken meat, beef tallow, spice mix, ice, NaCl, and NaNO2. Proximate composition and sensory analyses were conducted before the storage. Water activity, pH, TBARS, purge accumulation, and microbiological analyses were performed during the storage. QS3, TS2, and TS3 treatments got appreciated (7.0-7.4 out of 10) sensory scores, while GS3 scored low acceptability (4.0 out of 10) points. Adding food waste significantly reduced purge accumulation; the average purge accumulation of the control sample was 3.70% which is approximately two times higher than food waste added samples. The average TBARS value of the control sample was determined as 0.31 mg MA/kg, and the food waste-added samples were found between 0.57-0.65 mg MA/kg during storage. Total mesophilic aerobic bacteria and yeast-mold load were higher in TS2 and TS3 products; microbial load and TBARS values of food waste affected the product quality. Also, water activity, microbial growth, and purge accumulation amount affected each other during storage.
Evaluation of Enzymatic and Non-enzymatic Antioxidant Defense Responses of Durum Wheat (Triticum durum Desf.) in Coping with Boron Stress
Authors: Temizgül Rıdvan
Published: August 2024

Wheat, one of the world's most important agricultural products, plays a vital role in meeting the nutritional needs of our growing global population. However, arid and semi-arid regions face a potential threat from boron (B) toxicity. While boron is an essential nutrient for plant growth and development, its excessive presence can be toxic. It disrupts physiological processes, causing chlorosis and necrosis, ultimately leading to yield loss or plant death. Although B deficiency is a problem in the soils of many countries, Türkiye is one of the few experiencing B toxicity problems in its agricultural areas. This study investigated the physiological and biochemical responses of durum wheat to various B concentrations (0-20 mg L-1) under controlled air-conditioned cabin conditions. Durum wheat exhibited a decrease in chlorophyll content, phenolic content, and antiradical capacity at B doses exceeding 10 mg L-1. However, carotene content increased steadily with increasing B concentrations. The activities of antioxidant enzymes, including superoxide dismutase (SOD), ascorbate peroxidase (APX), and glutathione S-transferase (GST), increased up to a B dose of 15 mg L-1. Catalase (CAT) and glutathione reductase (GR) activities increased up to 10 mg L-1 B dose but decreased at higher B levels. Proline content increased tenfold up to a B dose of 10 mg L-1, indicating an attempt to mitigate stress. Conversely, malondialdehyde (MDA) accumulation increased continuously (approximately 150%) with increasing B doses, suggesting membrane damage. Despite being considered B-sensitive, this study demonstrated that durum wheat can effectively cope with B stress up to a B dose of 10 mg L-1 under controlled conditions. Beyond this threshold, physiological and biochemical changes indicate a decline in stress tolerance. Many osmoregulators, carotenes, alkaloids, flavonoids, tocopherols, phenolic compounds, non-protein amino acids, and several unidentified metabolites are activated to support antioxidant defense. The SOS pathway and the released ROS force gene regulatory systems come into play. Following these, the ROS released in the organism are neutralized, and ionic homeostasis and cellular stress resistance are achieved.
Determination of the Effect of Thymoquinone on DNA Damage in Kidney Cells Treated to High Glucose Depending on Time and Dosage by Comet Assay
Authors: Usta Ayşe , Dede Semiha , Yüksek Veysel , Öner Ahmet Cihat
Published: August 2024

The purpose of this study was to assess the anti-genotoxic potential of thymoquinone (TQ) against DNA damage in NRK-52E cells treated with high glucose using the comet assay technique single cell gel electrophoresis method. Cells were propagated by regular passages in in vitro conditions. TQ proliferative concentration (10μM) and IC25 (3rd-hour: 550 mM, 12th-hour: 240 mM, 24th-hour: 200 mM) and IC50 (3rd-hour: 760 mM, 12th-hour: 400 mM, 24th-hour: 280 mM) values for each hour of high glucose and were determined separately with MTT method. At these concentrations, the cells were divided into control(C), Thymoquinone (TQ), high glucose(G) and high glucose plus thymoquinone (GT) groups; It was incubated with the indicated substances for 3, 12, 24 hours. DNA damage was evaluated by applying the comet assay protocol and the results were calculated as DNA damage index (DDI). While DDI levels were observed to be significantly higher (p<0.05) in all groups administered high glucose compared to the control, a significant decrease was determined in all groups in which TQ was added along with high glucose. It was determined that high concentrations of glucose had genotoxic effects on kidney cells, and TQ administration together with high glucose, depending on concentration and time, had a significant effect on reducing DNA damage. However, it was concluded that the application of only thymoquinone significantly increased the DDI value compared to the control, and this was a data worth investigating in future studies. Additionally, TQ inhibited DNA damage. These results demonstrated the importance of TQ against nephrotic syndrome with its high antioxidant properties.
The Separation of Free Bran by Using Electricity-Assisted Electrostatic Field System
Authors: Kayıran Sema Nur , Koç Ramazan , Bayram Mustafa
Published: August 2024

In this study, it was to identify a method for separating the free bulgur bran from the fine bulgur during the production of bulgur. This was attempted by creating an electrostatic field using a PVC surface. It was observed that the issue of free bran, which adversely affects the packaged products visually, was effectively solved by this method. In contrast to conventional techniques, an alternative methodology was employed which utilizing a device comprising a folded PVC surface (folded curved channel). The configuration of the experimental apparatus was developed with dimensions of 4, 5 and 6 cm in width, 20, 40 and 60 cm in length, and angles of 30, 35 and 40 degrees, respectively. At the end of the PVC surface, plates were placed to create an electric field. In order to create the electric field, one of the plates was charged with a positive and the other with a negative charge. The distance between the plates was varied according to the width of the tunnel. The expected results were obtained in the layered PVC system. Consequently, a fine bulgur mixture consisting of 5 g of bran per 1000 g of bulgur was introduced into the experimental system at a flow rate of 0.89 g/s. This resulted in a notable reduction in the free bran content, which decreased from 5 g to approximately 2 g.
Antifungal and Antioxidant Properties of Some Artificial Antioxidants, Generally Recognized as Safe Compounds and Nano-Oxides
Authors: Gürgen Ayşenur , Yıldız Sibel
Published: August 2024

In this study, the usage potential of some artificial antioxidants, generally recognized as safe (GRAS) compounds and nano-oxides solutions in wood preservation industry, was investigated. For this purpose, antifungal and antioxidant properties of solutions were determined. Erythorbic acid, ethoxyquin, potassium disulfide, sodium ascorbate, sodium erythorbate and Enginerring and Nature Sciences Faculty (TBHQ) were selected as artificial antioxidants; dehydroacetic acid, sorbic acid and sodium benzoate were used as GRAS compounds and nano MgO, nano CeO, nano ZnO, nano SiO2 and TiO2 were investigated as nano-oxides in this study. Three different concentrations (0.5%, 1.0% and 1.5% ) were prepared, and anti-fungal test were carried out. The brown rot fungus Coniophora puteana (Schumach.) P. Karst. (BAM Ebw. 15) was used for the anti-fungal test. Then antioxidant activity of the solutions were determined. Iron (III) ion reducing antioxidant power method (FRAP) was used to determine the antioxidant activity of solutions. All solutions at 1.5% concentration completely inhibited the growth of C. puteana fungus. The antioxidant activity of solutions was sorted as artificial antioxidants>GRAS compounds>nano-oxides, respectively. It was concluded that the tested substances can be used as impregnating agents in wood preservation.
Design, Fabrication and Preliminary Testing of a Small-Scale Cassava Starch Extraction Machine
Authors: Etim Promise
Published: August 2024

A cassava starch extraction machine was designed and fabricated to perform a quadruplet action of grating, washing, sieving and separation. The study was necessitated based on concerns that most locally manufactured cassava processing machines are without provision for the extraction of starch. Food processors mainly depend on the manual pressing of cassava to obtain starch and this has significantly increased the cost of the product in the local market. Materials for construction were locally sourced and the machine was powered by a 2 hp electric motor through a v-belt-pulley transmission system and operating at a speed of 547 rpm. Fresh cassava tubers were harvested from Ikot Akpaden, a rural community in Mkpat Enin, Akwa Ibom, South-South of Nigeria, and used for the experiment. Results from the experiment showed that the quantity of wet starch extracted increased from 0.64 to 1.48 kg as the volume of water mixed with 2 kg of the product increased from 1 to 5 Liters. The rate of water usage and throughput capacity increased from 0.0005 to 0.0025 m3/kg and 35.29 to 46.75 kg/h respectively as volume of water increased. The optimum machine efficiency was 74%. The machine was fabricated at a cost of N 150,200 (equivalent of $100). Minimal time consumption, ease of operation and low production cost were some of the features that made the machine economically viable when compared to other conventional methods of extracting starch from cassava.
Pollutant Effects and Management of Animal Manure
Authors: Kılıç Fatma Nur , Sönmez Osman
Published: August 2024

Animal manure pollution constitutes a significant environmental issue, particularly in areas with intensive livestock activities. Manure, due to its various pollution loads such as nitrogen, phosphorus, heavy metals, and pathogens, can have adverse effects on soil, water resources, and air quality. Among manure management practices, sustainable methods such as composting, biogas production, and advanced treatment techniques stand out. These methods offer effective solutions for reducing the environmental impact of manure, while also holding the potential to be valued as valuable resources for agriculture and energy production. The growth in the global population along with urbanization has intensified the demand in commerce, industry, and agriculture sectors. This need to satisfy the supply-demand dynamics has led to increased production activities, subsequently giving rise to significant waste management challenges. This review examines the environmental impacts of pollution originating from animal manure, current management strategies, and research developments (R&D) in this field.
Educação em saúde bucal para profissionais de saúde de uma Unidade de Terapia Intensiva Pediátrica
Authors: Miranda André Lucas Valois , Rocha Lúcia Alves da
Published: August 2024

Objetivo: Descrever a prática vivenciada por cirurgião-dentista na implantação do protocolo de higiene bucal para pacientes internados em Unidade de Terapia Intensiva (UTI) de um hospital pediátrico do Estado do Amazonas. Relato de experiência: Trata-se de um relato de experiência desenvolvido por discente do Programa de Pós-Graduação em Ciências da Saúde da Universidade Federal do Amazonas. Através da oferta de um curso teórico-prático direcionado aos profissionais de saúde que atuam nas duas UTIs do hospital, foi apresentado e implantado o protocolo de medidas preventivas bucais, a fim de promover o controle efetivo do biofilme bucal nos pacientes infantis e diminuir o risco do desenvolvimento de pneumonias nosocomiais, que são um grave problema de saúde pública. Considerações finais: O planejamento prévio do curso e o conhecimento do ambiente e das rotinas de trabalho seriam essenciais para a adesão dos profissionais ao protocolo de higiene bucal proposto, assim como a oferta de momentos de discussão em grupo.