bluuebunny/crossref_metadata_2025_split huggingface dataset:
A chance constrained dynamic network reconfiguration based on Minty algorithm in distribution networks
Authors: Song Xinfu , Li Changling , Yi Geng , Zhong Rui , Wang Wei 
Published: October 2023

Abstract
With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in the dynamic network reconfiguration (DNR) is a big challenge. Besides, the existing mathematical and artificial intelligence algorithms for network reconfiguration face the problem of falling into local optima and poor convergence. To address the above challenge and problem, this paper first establishes a chance-constrained programming model to handle the uncertainties. Then the Minty algorithm is applied for efficiency and accurate static network reconfiguration (SNR) in each time interval. Finally, a branch exchange-based method is proposed to eliminate violations for the operation times of switches. Numerical simulations on the IEEE 33 system and an actual 151-bus distribution network show the superiority of the proposed algorithm over existing methods.
Research on IoT data aggregation by fusing fast matching algorithms
Authors: Jiang Congshi , Chen Quan 
Published: October 2023

Abstract
The characteristics of data aggregation with different network environments and dynamic changes in channel availability make some problems in IoT data aggregation. Therefore, this paper proposes an FMA-coverage model for algorithm design based on edge information. The FMA-coverage model includes the method of edge frequency, the method of primitive length (stroke), the texture energy metric of Laws and the method of fractal texture description. The FMA-coverage model can improve the network performance of IoT data aggregation. From the computational analysis, it can be seen that the security of data storage is only 17%. After the improvement of the fast matching algorithm, the security is up to 87%. After the network coding scheme, the IoT performance of data aggregation is up to 95%. It is important to note that, in this case, the required transmission volume in the network can be greatly reduced when the links are long. The IoT performance is up to 97% with the compression-aware scheme. By cross-sectional comparison, the IoT-based mobile model has the highest accuracy, with 98% accuracy of data aggregation. This paper extends the data aggregation mechanism by introducing fast-matching algorithms for device authentication and secure storage.
Innovative Reform Strategies of Artistic Practice of College Ethnic Music Education Based on Information Fusion Technology
Authors: Zhang Shiwen 
Published: October 2023

Abstract
To seek the path and method of innovation and reform of art practice of ethnic music education in colleges and universities. Based on information fusion technology, this paper introduces the Kalman filter algorithm for analysis and recognition of ethnic music education in colleges and universities and understands the application of information fusion technology in ethnic music education in colleges and universities through the correct recognition rate and recognition time of music signals. We also apply independent experiential and problem-based experiments to verify the feasibility of information fusion technology in innovative reform. The experimental results show that the Kalman filter algorithm based on information fusion technology has a 96.57% correct recognition rate for ethnic music signals, and the recognition time is faster than the support vector machine and BP neural network by 3.587s and 1.291s on average. 73.47% of the students, on average, think that the innovative reform of art practice based on information fusion technology in college ethnic music education is very effective, which is higher than the original The average percentage of students who thought the effect of the innovation reform of folk music education based on information integration technology was very good was 73.47%, which was 60.37 percentage points higher than the original research results. The average percentage of students who thought it was ineffective was only 9.19%, 52.31 percentage points lower than the original research results. The above results prove the feasibility of information fusion technology in reforming art practice innovation in university ethnomusicology education and provide a new direction for reforming art practice innovation in university ethnomusicology education.
Evaluation of corrosion resistance of marine engineering materials under function integral algorithm
Authors: Zhang Luyang , Liu Dashun 
Published: October 2023

Abstract
Significant corrosion problems in materials related to marine engineering projects are bound to be a threat to overall operational safety and reliability. This paper investigates the influence of corrosion time on the material product film performance and its corrosion resistance, combined with the function integral algorithm. The gray matrix transform, image binarization, and wavelet transform of the function integral algorithm are used to establish the corrosion damage image recognition model and quantify the microscopic characteristics of corrosion damage based on the corrosion morphological features. Through the corrosion damage image recognition model, evaluation and analysis of common marine engineering materials 2205 duplex stainless steel and Q420 steel in chloride ion (Cl−). Test results show that: chloride ion on 2205 duplex stainless steel corrosion resistance 17.89μA cm−2 was the critical point, the higher the concentration played a suppressive effect. Chloride ions on Q420 steel corrosion resistance in lower solutions below 2.23μA cm−2 concentration, Q420 surface product film has a certain protective effect on the substrate. The corrosion characteristic value evaluation results based on the function integration algorithm are consistent with the electrochemical test results, so the evaluation model established in this paper can effectively evaluate the corrosion resistance of the material.
Research on the reform of English teaching based on big data technology
Authors: Zheng Jingjing 
Published: October 2023

Abstract
The rapidly developing big data technology not only directly affects people’s work and life but also plays a greater role in promoting the direction of education. This paper introduces online teaching methods to traditional teaching methods, constituting a hybrid online and offline teaching method, and optimizes the reform of business English teaching objectives, contents and processes. After pre-processing the teaching evaluation indexes, the rough set method based on big data technology is used to mine the association rules of teaching data. The principal component analysis evaluation method was used to evaluate the structure of the mined teaching data set. And the changes in teaching evaluation index values obtained by the principal component analysis method were used as the basis for determining the effectiveness of the business English teaching reform. The experiment proved that: aS10 students in group A with the worst business English level increased their teaching level value from 1.004 to 1.224 after the general reform, an increase of 20.77%. After the online and offline hybrid reform, the teaching level value increased from 1.004 to 1.306, an increase of 22.72%. This shows that the reformed business English teaching mode has deepened the reform and innovation of business English teaching through the full use of big data technology, improved the comprehensive English ability and literacy of the majority of students, and laid a solid foundation for the future development of students’ working career.
Combining big data with innovative education on online ideology and politics for college students
Authors: Fan Qi 
Published: October 2023

Abstract
This paper proposes new methods and approaches to online ideological and political education for college students. Firstly, a network ideological and political intelligence platform is constructed based on the functional stratification characteristics of big data. Then, the ideological and political contents are clustered and filtered, and the contents are divided into several teaching fields according to the nature of various events. Based on this, the “incentive compatibility” mechanism based on “interest cluster” analysis is used to cluster and model users interested in the topic, to recommend relevant online content to similar groups. Finally, we analyzed the problems of online ideological and political education in colleges and universities in China and proposed countermeasures. Only 52.3% of colleges and universities have substantial recognition of the construction work results. 75% of the first batch of pilot colleges and universities have funding sources with the Ministry of Education and the schools themselves, 45% of colleges and universities have special funds of over 1 million, and the remaining 55% have special funds below 200,000. For further improvement, college students’ online ideological and political construction needs to be paid attention to and carried out.
The construction of visual aesthetic element system in graphic design based on big data
Authors: Shen Jing , Ling Sheng 
Published: October 2023

Abstract
Various exquisite graphic designs that can be seen everywhere beautify people’s vision and influence people’s visual aesthetics subtly. This paper starts with the visual aesthetic elements of graphic design and discusses the construction of visual aesthetic element systems in graphic design by analyzing the composition elements and aesthetic characteristics. Secondly, it proposes to use the biological visual perceptual machine model to process information through two visual pathways in a hierarchical manner. The features of graphic design images are expressed, stored, and extracted using the visual information model. Finally, the effectiveness of the bio-visual perceptual model applied to the construction of visual aesthetic elements of graphic design is verified by the Caltech5 database, Caltech256 database, and Scene15 database. The results show that the classification accuracy of the bio-visual perceptron model is 94.28%, 91.36%, and 99.75% in Caltech5, Caltech256, and Scene15 databases, respectively, which is 23.12% higher than the accuracy of other neural network models on average. The bio-visual perceptron model proposed in this paper can accurately detect the elemental features in complex graphic design, which provides a new idea and method for rapid detection and recognition for graphic design workers.
Blossoming Beauty: Enhancing Natural Fibres with Calendula Officinalis L. Flower Dye and Assessing Color Fastness with Microbial Properties
Authors: Mariselvam R. , Ranjitsingh A.J.A. , Mideen Ponani Kaja , Manoharadas Salim , Krishnamoorthy Rajapandiyan , Alshuniaber Mohammad A 
Published: October 2023

Abstract
Mordants are materials used to fix long periods of colour on selected fabrics or fibres. The current research aimed to dye natural fibres like palm leaf (Borassus flabellifer L.), korai grass (Cyperus pangorei L.), banana fibre (Musa accuminata L.), screw fine fibre (Pandanus), sisal fibre (Agave sisalana Perrine), and pineapple fibres (Ananas comosus L.) with Calendula officinalis plant flower dye. The dye was fixed to the selected fibre material with the help of different mordants. The Calendula officinalis flower dye produced different colours, like black, brown, orange, sandal, yellow, etc., on the dyed materials. The different colour formations on the dyed materials are based on the mordents used to fix the dye. The mordants tonify the different colours in the same dyestuff of Calendula officinalis flower dye. Mordant-based dyed natural fibres have good fastness properties against light and water. Calendula officinalis dyes have potential activity against the skin infection-causing organism Pseudomonas aeruginosa.
Occurrence of Tet Gene-Bearing Antimicrobial-Resistant Escherichia coli From Dairy Farms in Nigeria
Authors: Yusuf Muhammad S. , Kabir Junaidu , Bello Mohammed , Aliyu Mohammed B. , Esonu Daniel O. , Yusuf Fatima L. , Babashani Mohammed 
Published: October 2023

Abstract
This study focused on antibiotic resistance genes as emerging contaminants with potential global human health implications. Intensive livestock farming has been identified as a major contributor to the spread of resistant bacteria and genes. The study examined antimicrobial-resistant Escherichia coli and tetracycline-resistant genes in raw milk from commercial dairy farms in Kano State. Out of 300 registered farms, 54 (18 %) were purposively sampled for the study. A total of 313 milk samples were collected and processed through enrichment and inoculation on selective media for Escherichia coli isolation. The antibiogram pattern of the isolated Escherichia coli strains was assessed using the disk diffusion method. The results revealed resistance to various antimicrobial agents, with no resistance to quinolones but high resistance to ampicillin (100 %), erythromycin (73.3 %), and tetracycline (46.7 %), among others. The multiplex polymer-ase chain reaction was conducted on all Escherichia coli isolates to detect tet genes (tet A, B, C, D, and M), and one isolate carried the tet M resistance gene, while six (40 %) others carried the tet A resistance gene. The study concludes that a significant proportion of the cultured Escherichia coli strains were resistant to one or more tested antibiotics, indicating a potential public health threat associated with Escherichia coli contamination in raw milk. We recommend implementing robust regulatory policies governing the use and sales of antimicrobials in animal production. Furthermore, we suggest further investigation into other resistant genes that these isolates might carry to better understand the extent of antibiotic resistance in the region.
Pinealocytes and Glia Cells in the Pineal Gland of the African Straw-Coloured Fruit Bat (Eidolon helvum)
Authors: Olopade James O. , Igado Olumayowa O. , Adesina Marvellous A. , Folarin Rachael O. , Obasa Adedunsola A. 
Published: October 2023

Abstract
The mammalian pineal gland is a structure that in recent years has been extensively studied, due to its functions and the hormones it produces. Bats are the only known flying mammals, with the order having a large number of species. This study was carried out to investigate the gross and histological features of the pineal gland of the Eidolon helvum, the African fruit bat, using male and female subjects. Eight free flying E. helvum (4 males, 4 females) were captured using mist nets. The pineal gland was grossly observed to be very small in size, oval in shape, and covered by the pia mater. Histological examination revealed two populations of pinealocytes – Types I and II – oval structures possessing acidophilic cytoplasm and large, round nuclei. Pinealocytes were seen to appear singly or in clusters, having no particular arrangement. Sexual dimorphism was observed, with the females having less density in population of pinealocytes at the peripheral region of the gland. This was consistent in all subjects examined. Astrocytic appearance was typical with long and slender processes, and perivascular and capsular microglia were observed. The glia cells were observed to be abundant in the parenchyma and around the capsule. There was no sensitivity to NeuN antibody. Results obtained may find application in behavioural and comparative neuroscience.
Rotor Speed and Load Torque Estimations of Induction Motors via LSTM Network
Authors: Kosten Mehmet Muzaffer , Emlek Alper , Yildiz Recep , Barut Murat 
Published: October 2023

Abstract
In this study, a long short-term memory (LSTM) based estimator using rotating axis components of the stator voltages and currents as inputs is designed to perform estimations of rotor mechanical speed and load torque values of the induction motor (IM) for electrical vehicle (EV) applications. For this aim, first of all, an indirect vector controlled IM drive is implemented in simulation to collect both training and test datasets. After the initial training, a fine-tuning process is applied to increase the robustness of the proposed LSTM network. Furthermore, the LSTM parameters, layer size, and hidden size are also optimised to increase the estimation performance. The proposed LSTM network is tested under two different challenging scenarios including the operation of the IM with linear and step-like load torque changes in a single direction and in both directions. To force the proposed LSTM network, it is also tested under the variation of stator and rotor resistances for the both-direction scenario. The obtained results confirm the highly satisfactory estimation performance of the proposed LSTM network and its applicability for the EV applications of the IMs.
Editorial Gatekeeping in Sports News During Prime Time Television in a Public Broadcaster
Authors: Cruz Carla , Araújo Duarte 
Published: October 2023

AbstractIntroduction.Based on Shoemaker's model of gatekeeping, this study addresses two questions: What social representations of sports are promoted by the prime time news program of the public television broadcaster Radio Televisão Portuguesa (RTP)? How do editors assess sports news stories during the editorial decision-making process?Material and Methods.For this, we quantitatively examined all the sports content in the prime time ‘Telejornal’ daily news program of RTP during a trimester. Moreover, we studied the factors that influenced editorial decisions, by conducting naturalistic participant observation and semi-structured interviews.Results.Results indicate that facts of greater public protagonism, which cause a significant emotional reaction and are relatable to the public, are more newsworthy. The main constraints influencing the editorial decisions were organized in three co-dependent areas: Social System (macro level), RTP Organization (meso level) and Telejornal Newsroom (micro level).Conclusions.Findings contribute to a reduction in social stereotypes created by television broadcasters, and to sports actors optimizing their communication strategy.
Exploring Cross-Cultural Differences in Fundamental Motor Skills Proficiency Between Polish and Latvian Children
Authors: Makaruk Hubert , Grants Juris , Bodasińska Anna , Bula-Biteniece Inta , Zieliński Janusz , Dravniece Irēna , Starzak Marcin , Ciekurs Kalvis , Piech Krzysztof , Makaruk Beata , Žīdens Janis , Kalniņš Kārlis , Sadowski Jerzy 
Published: October 2023

AbstractIntroduction.Fundamental motor skills (FMS) are a critical component of success in various sports and lifelong physical activity (PA). This study aimed to evaluate and compare the FMS proficiency levels of 7-9-year-old children from Poland and Latvia, providing insights into the current state of motor competence in these populations.Material and Methods.A cross-sectional study design was utilized, incorporating a sample of 163 boys and girls. The FUS test (Fundamental Motor Skills in Sport), a comprehensive, qualitative, and process-oriented assessment tool was used to assess FMS. The FUS test encompassed a range of movement tasks, including hurdles, jumping rope, forward roll, ball bouncing, ball throwing and catching, and kicking and stopping a ball that allows for a thorough evaluation of FMS proficiency.Results.The study revealed alarmingly low FMS proficiency levels in both countries, with 93.3% of students displaying ‘insufficient FMS proficiency’. The Mann-Whitney U test showed that Latvian boys outperformed their Polish peers in jumping rope and forward roll (p < 0.05), while Polish boys exhibited superior results in kicking and stopping a ball (p < 0.05). In contrast, Polish girls achieved significantly higher scores in hurdles and kicking and stopping a ball (p < 0.05) compared to Latvian girls, who scored higher in jumping rope (p < 0.05).Conclusions.These findings highlight the urgent need for effective, evidence-based interventions to improve motor competence in both countries, emphasizing the importance of incorporating FMS development into physical education curricula and promoting regular PA for children.
A rare cause of mixed hypertrophic and dilated phenotype cardiomyopathy – the MELAS syndrome
Authors: Casian Mihnea , Dragotoiu Nic , Onciul Sebastian , Popescu Bogdan A. , Jurcuţ Ruxandra 
Published: October 2023

Abstract

Introduction
MELAS is a systemic hereditary condition that can present as hypertrophic or mixed hypertrophic and dilated phenotype cardiomyopathy in young individuals, although a late-onset form is also described in the literature. Genetic testing is essential for correct diagnosis and appropriate management.

Case presentation
We present the case of a 22-year-old male who was referred to our center after being diagnosed with NYHA class III heart failure with a mixed hypertrophic and dilated cardiomyopathy. His medical history included stroke episodes, seizures, progressive hypoacusis, neurocognitive impairment, and muscle atrophy. Lactic acidosis and elevated CK levels were also noted. The ECG revealed short PR interval and delta wave in lateral leads. TTE showed mildly dilated and hypertrophied LV and RV with severe biventricular systolic impairment. The CMR study was relevant for ring-like subepicardial fibrosis, predominantly in the medium and apical segments. Brain MRI showed multifocal supratentorial subcortical stroke-like lesions in both cerebral hemispheres, involving multiple vascular territories and following a migratory pattern. Genetic testing confirmed a pathogenic MT-TL1 mutation (m.324A>G) and the patient was diagnosed with MELAS. Further management included specific lifestyle recommendations and cascade genetic screening, as well as starting GDMT for HFrEF. Three months after discharge, his clinical status improved. However, the LVEF remained reduced. After careful consideration, an ICD was implanted for primary prevention.

Conclusion
A red-flag approach in this young patient, which took into consideration the stroke-like episodes, lactic acidosis, seizures, hypoacusis, myopathy, as well as the short PR interval, led to the correct diagnosis, further confirmed by using the appropriate genetic test. Failure to diagnose affects the patient’s prognosis, as their prognosis and clinical status are influenced by enforcing specific recommendations.
Characterization and Removal of Dissolved Organic Matter in River Water Through Preoxidation-Coagulation Process
Authors: Hidayah Euis Nurul , Anastasia Grace Claudia , Cahyonugroho Okik Hendriyanto 
Published: October 2023

Dissolved organic matter (DOM), which is part of of natural organic matter or NOM, contained of carbon compound and can cause problems related to taste, odor, and disinfection by-products (DBPs) in water and treated water. Permanganate is strong oxidant and have been know its efficiency in oxidazing organic compound. Coagulation is most widely used in all water treatment plant due to its efficiency in removing suspended solid. The objectives of this study is to characterize and to remove natural organic matter in term of Â DOMÂ in water through KMnO4 preoxidation, Al2(SO4)3 or FeCl3 coagulation, KMnO4 preoxidation followed by Al2(SO4)3 or FeCl3 coagulation. Raw water, which was taken from Jagir River in Surabaya, and treated water were measured quantitatively by using total organic carbon (TOC), ultraviolet at wavelength 254 nm (UV254) in order to know its aromatic properties. In addition, fourier transfor m infrared spectroscopy (FTIR) was used to identify the functional group of DOM in water and treated water. The results showed that raw water has high TOC concentration (6,9 mg/L) and mainly composed of aromatic (UV254 0.075 cm-1). The optimum result showed that TOC concentration and UV254 removed significantly into 4,2 mg/L and 0,0020 cm-1, respectively after preoxidation followed by FeCl3 coagulation. According to FTIR analysis, mostly single bond carbon such as C-O and C-H still exist in treated water. This results indicated that preoxidation-coagulation has a better performance than preoxidation only and coagulation only.