bluuebunny/crossref_metadata_2025_split huggingface dataset:
An innovative study of art teaching strategies for preschool children based on big data analysis
Authors: Zhao Junchao , Tao Zhengwei 
Published: September 2023

Abstract
To understand the relationship between art teaching strategies and innovative development in preschool children. In this paper, using a sample-control research design, 2 middle classes of a kindergarten were selected as experimental and control classes to test the changes of children on these 5 dimensions after the art teaching was carried out, based on no significant differences in the 5 dimensions of the pre-test of innovative thinking test (drawing), namely originality, fluency, delicacy, title, and contemplation. The k-means algorithm in big data was also used to help analyze the effect of art instruction on innovativeness in preschool children. The k-means algorithm analysis revealed that in comparing between-group and within-group differences, there was a significant difference between the control and experimental classes in originality F of 6.65 and a borderline significant F of 3.94 in the dimension of title abstraction. The F values of fluency, originality, titleless, delicacy, and resistance to premature closure (contemplation) in the time dimension were 13.40, 17.84, 3.57, 21.04, and 14.60, respectively. The results found that the dimensions of fluency, originality, captioned abstraction, delicacy, and resistance to premature closure (contemplation) were significantly higher for the posttest children than for the pretest, and the dimensions of innovativeness were significant for both time and class interactions. Thus, there is a correlation between art instruction and innovative thinking development in preschool children.
A study on the effect of music on college students’ depression and anxiety based on big data analysis
Authors: Qin Puhong 
Published: September 2023

Abstract
The purpose of this paper is to investigate music’s effect on anxiety regulation among college students, to help them find new ways to improve their negative emotions and enhance their emotion regulation ability. This paper first describes the association rule mining algorithm, then optimizes and improves the association rule mining algorithm by using the particle swarm algorithm to encode and calculate the fitness value to generate the population optimization of the particle swarm. The optimization algorithm iteratively searches for the optimal solution, and the particles achieve the search process by following their own and the population’s optimal particles and using the particle swarm optimization association rule algorithm to mine data on the effect of music intervention on anxiety and depression. When the different interventions were applied, the post-test depressive mood level of the music group was significantly lower than that of the motor training group p=0.008 and significantly lower than that of the blank group p=0.006. And the difference between the pre-test and mid-test results of SAS in the music group was significant p=0.014, and the difference between the pre-test and post-test results of the music group was borderline significant p=0.069. When the intervention was applied with music, the intervention group SDS All four dimensions scores decreased when comparing themselves before and after the intervention, depressive psychological disorder 18.83±3.20 decreased to 14.41±3.39 and psycho-affective disorder decreased from 4.87±0.13 to 2.83±0.84. Thus, it can be seen that music significantly affects the intervention of anxiety and depressive mood.
Construction of sustainable development professional cluster in private universities based on data mining model
Authors: Liu Xueyi 
Published: September 2023

Abstract
Professional cluster construction is the change of professional development mode in the context of current social development, and it is the innovation of internal construction and intensive management of private colleges and universities. This paper analyzes the advantages and disadvantages of the maximum expectation algorithm in big data mining, proposes to optimize the parameter estimation iteration by using the Monte Carlo method for the problem that the stable point of the EM algorithm does not necessarily reach the global optimum, uses the sample mean instead of the overall mean, and further proposes MCEM acceleration algorithm to improve the convergence speed of the parameter estimation iteration. The evaluation score of the audit professional group construction in internal business process management of school A is 3.21, that of the software technology professional group construction in the learning and growth dimension of school B is 3.45, that of the Chinese medicine professional group construction in developing core competitiveness dimension of school C is 2.87. The comprehensive evaluation score of the construction of the industrial robotics professional group in school D is 3.33. The mining evaluation of professional cluster construction based on big data can precisely locate the key factors of professional cluster construction in private colleges and universities, which is of reference significance for the sustainable development of professional cluster construction in colleges and universities.
A Regionalization Study of Market-Based Allocation of Data Factors in China
Authors: Dai Dongyang , Jin Lin 
Published: September 2023

Abstract
Studying regional differences in the market-based allocation of data factors can help promote the development of data factor markets in China. This paper establishes a market-based allocation framework for data factors and analyzes the economic characteristics and market-based classification of data factors to explain the market-based framework. On this basis, a data factor market-based allocation efficiency measurement model is established based on network DEA with additional intermediate inputs to calculate the stage and overall market-based allocation efficiency of 30 Chinese provinces and cities with available data from 2019 to 2020, while the Malmquist index reflecting the inter-period dynamic changes is analyzed. The measured average values of market-based allocation efficiency of data factors in 2020 in the eastern, central, and western regions of China are 0.714, 0.515, and 0.362, all exceeding the average value in 2019, and improving by 12.43%, 15.67%, and 17.38% year-on-year, respectively. The average value of market-based allocation efficiency of data factors in 2019~2020 is 0.80, and above in six provincial. There are 6 administrative districts. 19 provinces have a Malmquist index of market-based allocation of data elements greater than 1 in 2020, accounting for 63.37%. In the era of the digital economy, provinces should actively formulate high-standard data factor market cultivation and development plans to ensure that data factors become basic and strategic resources for each province, empowering high-quality economic development.
Coupled coordination analysis of green finance on economic growth based on big data
Authors: Guo Su , Zhang Taile , Cui Junfu 
Published: September 2023

Abstract
Exploring the coupled and coordinated relationship between green finance and economic growth is to achieve the high-quality dual development of green and economy. This paper studies the rough set and information entropy attribute approximate calculation based on MapReduce parallel computing framework under big data technology. The basic principles of rough set and information entropy are described, and the MapReduce algorithm is used to calculate information entropy, mutual information, and attribute kernel, which shows that MapReduce calculation is always on the key-value pairs. For the correlation analysis of green finance and economic growth, the coupled coordination model of green finance and economic growth is constructed using the MapReduce algorithm, and the coupled coordination analysis of green finance and economic growth is carried out for this model. From the comprehensive evaluation index, the comprehensive evaluation index of green finance and economic growth increased by 6308.44% and 2242.21%, respectively. The coupling degree of green finance and economic growth increased by 164.66% and 835.84% from the coupling degree and coordination degree, respectively. Thus, the coupling relationship between green finance and economic growth based on big data is relatively low, but the coordination degree is high, indicating that the two influence each other and interact.
Decentralized Internet-based calligraphy education leads the internal development of aesthetic education in schools
Authors: Li Chengzong 
Published: September 2023

Abstract
Traditional physical calligraphy education faces huge challenges and opportunities in the context of the rapid development of big data technology and the Internet. This paper first combines big data technology and the educational objectives of calligraphy and proposes the use of machine learning to solve traditional calligraphy education challenges and lead the internal development of aesthetic education in schools. Then it elaborates the research idea and structural framework of machine learning, which mainly consists of two parts: global features of the GIST algorithm and local features of SIFT algorithm, and optimizes machine learning by weighted self-learning hash high-dimensional data indexing algorithm. Finally, the study was conducted to determine the target and content of the study based on the selection of evaluation features and to use machine learning to analyze the satisfaction of calligraphy education on the decentralized Internet. A satisfaction analysis was conducted. The results showed that for students: the satisfaction value of decentralized Internet-based calligraphy education fell within the range of 35.01% to 42.98%, and its average satisfaction was 38.99%, with students outperforming parents and teachers with 38.99% average satisfaction. This study will help students to learn calligraphy systematically with half the effort so that the calligraphy culture can take root in their minds and blossom again, which is the true meaning of “learning for the past”.
Microbiological and Sensory Properties of Tempeh as Influenced by Type of Legumes and Storage Temperature
Authors: Adanlawo Oladipo Olawale , Malomo Adekunbi Adetola , Adeniran Hezekiah Adekanmi 
Published: September 2023

Abstract
Bambara groundnut and lima bean are lesser-known legumes with high protein content. These legumes were incorporated into tempeh; a soybean-based snack to advance their uses as food. This research studied effects of the legumes on microbiological, physicochemical and sensory properties of tempeh during storage at ambient and refrigeration temperatures. The results showed that the total viable count of bacteria and fungi count of tempeh mash ranged between 6.173 - 7.903 logcfu/g and 6.602-6.799 log cfu/g respectively. The microbial load of the refrigerated fried tempeh snacks was lower than samples at room temperature. Blends of the three legumes (4.079 – 7.297 logcfu/g) had the highest total viable count while lima bean tempeh (3.903-5.602 logcfu/g) had the lowest. Bacillus cereus, Staphylococcus epidermidis, Bacillus coagulan, Bacillus subtilis, Bacillus alvei, Bacillus Licheniformis, Micrococcus cryophilus, Propionibacterium species, Rhizopus oryzae, Rhizopus stolonifer and Geotricum sp were isolated from tempeh snacks during storage. The results of the sensory assessment showed that lima bean tempeh snack was the most preferred. This research therefore suggests the use of lima bean and blends of lima bean, Bambara groundnut and soybean in production of tempeh to advance the use of these underutilized legumes and increase food security.
Screening and Identification of an Antibacterial Agent-Producing Lactobacillus Strain and its Application in Bananas Preservation
Authors: Guo Meng , Shu Guowei , Wang Zhanmin , Kang Jie , Chen Li , Qi Kangru , Liu Yu 
Published: September 2023

Abstract
With the development and progress of human society and the continuous enhancement of people's health awareness, lactic acid bacteria inhibitors as a natural biopreservative have an irreplaceable position, with the advantages of high efficiency, broad spectrum, stability, safety and other characteristics. This paper studied the antibacterial effect of 23 lactic acid bacteria; the strains with the best antibacterial effect was identified by 16S rDNA method as being Lactobacillus rhamnosus L57 and was applied to banana storage. Our study showed that Lactobacillus rhamnosus L57 has a broad spectrum, inhibiting Escherichia coli, Staphylococcus aureus, Vibrio alginolyticus and Bacillus nato. Excluding the interference of organic acids, hydrogen peroxide and extracellular polysaccharide, the salting out of ammonium sulfate preliminarily determined that the proteins or peptides are the antibacterial substances in the antibacterial agent. Physicochemical properties showed that the microorganism had good antibacterial activity after trypsin, pepsin and papain, with good tolerance to pH, temperature and UV light, and the pH optimal range of 2.0-4.0. The mixture of freeze-dried powder of L. rhamnosus L57, chitosan and natamycin was used for banana preservation, with the proportion of freeze-dried powder of 1.25%, chitosan 1.5% and natamycin 0.03%. The preservation period was extended by 4 days compared with the absence of either bacteriostatic agent.
Milk Yield and Composition, Technological Properties and Homeostasis Indices at Different Lactation Stages and Parities of Two Polish Dairy Goat Breeds
Authors: Urbańska Daria Maria , Puchała Ryszard , Jarczak Justyna , Barłowska Katarzyna , Czopowicz Michał , Mickiewicz Marcin , Kaba Jarosław , Bagnicka Emilia 
Published: September 2023

AbstractThe purpose of the research was to determine the effect of breed, lactation number, and lactation stage on milk efficiency and goat milk ingredients, these being indicators of milk technological parameters and homeostasis disturbances. Goat breed and number of lactation affected energy-corrected milk, value-corrected milk yield, fat corrected milk, protein, casein, lactose contents and free fatty acids. Additionally, differences in non-fat solids and urea contents were found between two Polish common dairy breeds White Improved (PWI) and Fawn Improved (PFI) goats. Moreover, parity affected milk yield, its acidity and somatic cell count (SCC). Milk yield and milk components were found to vary according to lactation stage. At the beginning of lactation, milk is richer in ingredients which have effect on cheese and yoghurt production. All the goats undergo similar changes related to the lactation stage that is at the same time and this can affect the yield and quality of the curd. In production focused on liquid milk, the age structure of the herd should be properly managed, as the goats in their third lactation or above have higher milk yields, regardless of breed. For cheese production, the PWI breed would be more suitable than PFI as the PWI goat milk contains less SCC and more components essential for milk processing, including caseins.
Effect of Ozon Treatment on Shelf-Life of Poultry Meat in the Logistic Chain
Authors: Matłok Natalia , Zapałowska Anita , Durał Beata , Balawejder Maciej 
Published: September 2023

Abstract
A study was carried out to determine the influence of ozon treatment on the shelf-life of poultry meat. The following doses of gaseous ozone were used: 0 ppm for 0 min, 10 ppm for 1 min, 10 ppm for 5 min, 10 ppm for 15 min, 100 ppm for 1 min, 100 ppm for 5 min, and 100 ppm for15 min. Treated and untreated samples were stored at 4°C for a maximum of 3 days and microbiologically examined on the 1st, 2nd and 3rd day of cold storage. The textural properties and water content were also analyzed. The present study showed that the most desirable color change was recorded after the 3rd day of storage, on the samples treated with gaseous ozone of 10 ppm for 15 min. Regardless of exposure time and the gas dose used, ozone has been shown to effectively reduce meat hardness. Although the analyzes performed had non-significant effects on water content and microbiological load during post-treatment storage at 4 °C, our findings confirmed the effectiveness of the ozone gas used on extending shelf life of the examined poultry meat by influencing their texture profile and color parameters.
Mr. Marvin Goes to Key West
Authors: Denham James M. 
Published: September 2023

Abstract
This essay provides a sketch of William Marvin's first decade in Key West (1835–45). In this period, Marvin, originally from New York, served as the territory's U.S. district attorney (1835–39) and its second territorial judge (1839–45). It was during this time that Marvin became acquainted with the city's wrecking industry and began to develop his interest in salvage law.
Judge William Marvin and the Law of Salvage
Authors: Friedell Steven F. 
Published: September 2023

Abstract
This essay explores the salvage decisions rendered by William Marvin during his time as a judge in Key West (1839–45; 1847–63). It also discusses his celebrated treatise on salvage law (1858), which cemented his reputation as one of America's leading authorities on maritime law. Lastly, it recounts how Marvin superintended the city's notorious wrecking industry.
Growth-climate responses of Picea sitchensis [Bong.] Carr. versus Picea abies [L.] Karst. in the British Isles and Central europe
Authors: Brabec Pavel , Vacek Zdeněk , Vacek Stanislav , Štefančík Igor , Cukor Jan , Weatherall Andrew , Gallo Josef , Slávik Martin , Sitková Zuzana , Putalová Tereza 
Published: September 2023

Abstract
Introduced tree species have become increasingly important in the context of the ongoing climate change. This paper focuses on the dendrochronology of the most widespread introduced tree species in the British Isles – Sitka spruce (Picea sitchensis [Bong.] Carr.) – in comparable soil conditions in England, Czechia, and Slovakia. The research aims to evaluate the growth dynamics and the influence of climatic factors on this tree species while comparing it with economically main tree species in Europe – Norway spruce (Picea abies [L.] Karst.). Based on the analysis of 150 increment cores, the radial growth of Sitka spruce was on average 24.2% higher than that of Norway spruce. The highest increments in 52 to 62-year-old stands were achieved in England by both Sitka spruce (8.7 mm) and Norway spruce (7.0 mm). In terms of negative pointer years (NPYs), there was no difference in the number of years with a significantly low increment between the two species at any site. The lowest effect of climatic factors on growth was found in Czechia, while the highest was in England. Higher resistance to climate was found for Sitka compared to Norway spruce. In general, the main limiting factor for the growth was the lack of precipitation in the previous year’s vegetation season, or heavy frost in England. In Central Europe, due to low precipitation, Sitka spruce will not be a substantial introduced tree species in the future, but on suitable sites, it can achieve high production potential and play a significant role for increasing stand diversity in the face of climate change.
Comparison of growth of northern red oak (Quercus rubra L.) and durmast oak (Quercus petraea [Mattusch.] Liebl.) under similar growth conditions
Authors: Štefančík Igor , Pástor Michal 
Published: September 2023

Abstract
The impacts of climate change on forest stands are manifested in different ways and intensity. Changes in the species composition of forest stands due to the different tolerance of forest species to the effects of climate change are one of the consequences too. In this context, introduced tree species are often mentioned as a possible replacement for dying autochthonous species. Of the deciduous species, it is mainly northern red oak. The aim of this paper is to compare selected quantitative (number of trees, basal area, merchantable volume, basal area increment and volume increment) and qualitative (crop trees) characteristics in one stand of the northern red oak at the age of 54 years and in two stands of durmast oak (age 57 and 58 years) in comparable site conditions. Achieved results showed higher values in all investigated quantitative parameters in the northern red oak stand compared to durmast oak stands. The merchantable volume in the northern red oak stand was 473 m3 per hectare in the tended subplots and 742 m3 ha–1 in the control ones. On the subplots with durmast oak, it was only from 228 to 289 m3 ha–1 in the subplots with thinning and 226 to 357 m3 ha–1 in the control areas. The same results were obtained for the category of crop trees. It means 230 m3 ha–1 for the northern red oak and 28 to 121 m3 ha–1 for durmast oak. The well-known fact about the higher quantitative production of the northern red oak compared to durmast oak was confirmed.
Silvicultural potential of the main introduced tree species in the Czech Republic – review
Authors: Novotný Stanislav , Gallo Josef , Baláš Martin , Kuneš Ivan , Fuchs Zdeněk , Brabec Pavel 
Published: September 2023

Abstract
Only 1.82% of the Czech forests are covered by the introduced (exotic, non-native) tree species, they represent only a very minor part of the forest area in the Czech Republic. Despite this fact under certain circumstances and locally, they can play an important role in the forest restoration of declined forests. The main non-native tree species used in the Czech Republic are: black locust (Robinia pseudoacacia L.), Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco), grand fir (Abies grandis [Douglas ex D. Don] Lindl.), black walnut (Juglans nigra L.), northern red oak (Quercus rubra L.), and blue spruce (Picea pungens Engelm.). Other tree species are cultivated on very small areas, despite their much larger potential. The aim of the presented review paper is to summarize information on the introduced tree species, available especially from national sources, and give comprehensive information concerning the potential and risk of their use in the conditions of the Czech Republic. The authors mention also other tree species eligible for silviculture under current as well as future climatic circumstances. The current area and silvicultural potential in the climate changing conditions are analysed and summarized.
Detecting Abandoned Houses in Rural Areas using Multi-Source Data
Authors: Lee Changro 
Published: September 2023

Abstract
Abandoned houses have become a common feature of the local landscapes: the rising number of abandoned houses is a major challenge facing many counties in South Korea. Their presence negatively influences the neighborhood by undermining its aesthetic quality, depreciating the perception of safety in the neighborhood properties, and deepening the fiscal deficit of local financing. The detection of abandoned houses is the first step toward adequate housing management by local governments. This study aims to provide a cost-effective and prompt approach to identifying abandoned houses in rural areas. Multi-source data, that is, images and building registry data are utilized and a multi-input neural network is designed to adopt these heterogeneous datasets. Trained by the two source datasets, the proposed network achieves 86.2% accuracy in classifying abandoned houses, which is an acceptable performance level in administrative practice. The database of abandoned houses identified in this manner is expected to promote effective housing management by governments and ultimately contribute to mitigating vacancies in rural areas.