bluuebunny/crossref_metadata_2025_split huggingface dataset:
regulations for street music in Spain lead urban musicians to break the law?
Authors: Ospina Gallego Crismary , Lloret Romero Maria Nuria , Betancur Santa Héctor Yovanny 
Published: January 2025

Do the regulations for street music in Spain lead urban musicians to break the law?

This study focuses on street musicians who sing or play musical instruments in a public space for donations/tips. Currently most of their needs are not covered in the laws relating to of street musicians in Spain, several cities do not have this profession regulated and in the localities that do, they prohibit amplification, the sale of their own music (CDs etc.), limit free movement and the instruments that they can use. These are rules that musicians must break in order to work, leaving the buskers who perform in a legal gap or limbo, without defense against the authorities.
This study addresses 3 parts: the first is an observational exercise from the perspective of the street musician which seeks to find out the basic needs of workers in their busking experience; the second area analyzes how the Spanish regulations behave based on the needs that these performers have; and the third element contrasts the personal view of the researcher with the opinions of other street musicians and groups found in the media.
Machine Learning Models in Predicting Failure Times Data Using a Novel Version of the Maxwell Model
Authors: Panitanarak Uthumporn , Ishaq Aliyu Ismail , Singh Narinderjit Singh Sawaran , Usman Abubakar , Usman Abdullahi Ubale , Daud Hanita , Adepoju Akeem Ajibola , Sadiq Ibrahim Abubakar , Suleiman Ahmad Abubakar 
Published: January 2025

This work aims to introduce a novel statistical distribution based on Maxwell distribution that can handle both positive and negative data sets with varying failure rates, including decreasing and bathtub-shaped distributions. The novel statistical distribution can be derived via the log transformation approach with an additional exponent parameter, defining the Transformed Log Maxwell (TLMax) distribution. The numerical investigation reveals that the developed TLMax distribution can effectively fit negative and positive data sets. A data set containing failure times for Kevlar 49/epoxy at a pressure of approximately 90% was employed to compare the proposed model against the traditional Maxwell model, and the results obtained indicated that the novel distribution outperformed the comparator. Finally, for the prediction of failure times in the dataset, we employed a machine learning model, including support vector regression (SVR), K-nearest neighbors’ regression (KNN), linear regression (LR), and gradient boosting regression (XGBoost). The findings indicate that the KNN model demonstrates greater prediction robustness than the other models. Beyond practitioners and researchers, this research holds relevance for professionals in physics and chemistry, where the Maxwell distribution is commonly employed.
La traducción y la interpretación. Un binomio crucial para luchar por la justicia lingüística de los pueblos indígenas
Authors: Libreros Cortez Héctor 
Published: January 2025

Reseña del libro:

Kleinert, C., Monzó-Nebot, E. y Tasa, V. (Eds.). (2023). La traducción y la interpretación como claves en la protección de los derechos lingüísticos de las comunidades indígenas. España: Comares.
Utilization of Sonic Bloom Technology as An Effort to Improve The Productivity of Pakcoy (Brassica rapa L.) Cultivation in The Vila Pasir Mas Taruna Tani Group
Authors: Putri Dea Helmalia , Harahap Fitra Syawal , Walida Hilwa , Adam Dini Hariyati 
Published: January 2025

The pak choy plant is a plant that has a very easy method of cultivation. The pak choy plant is also one of the vegetables that is often developed by hydroponic farmers because many people like to eat pak choy so this plant is one of the people's favorites. The aim of community service (PKM) is that the community is expected. Efforts to increase the productivity of pak choy continue to be made because this plant has quite high economic value and market interest. This service uses the lecture method, namely by conveying information and knowledge orally using power points. By using Sonic Bloom technology on Pakcoy plants, you can stimulate the opening of the stomata, thereby influencing the movement of carbon dioxide around the plant, thereby influencing the absorption of carbon dioxide around the leaves and more importantly using high frequency and organic sound waves. nutrients, which are proven to grow plants better to increase their productivity. By implementing this community service program, the Karang Taruna Tani Pasir Mas Group Partners will be able to provide knowledge in cultivating vegetables using Sonic Bloom technology. And based on this report, it can be concluded that Sonic Bloom treatment using the sound of the Al Quran can produce plant height, number of leaves, production weight and weight of basal roots and dry roots in bok choy plants because the sound is given using a high frequency. can stimulate the leaf mouth (somata) to remain open.
Effect of Ketip Banana (Musa paradisiaca Forma typiaca) Peel Ethanol Extract on Sperm Viability of Mice (Mus musculus) Following Cigarette Smoke Exposure
Authors: Bahri Syamsul 
Published: January 2025

Tobacco smoke contains more than 4000 kinds of constituents, including nicotine, tar, carbonic monoxide, polycyclic aromatic hydrocarbons, and heavy metals. Because of the complexity of tobacco smoke components, the toxicological mechanism is notably complicated. Most studies have reported reduced semen quality, reproductive hormone system dysfunction and impaired spermatogenesis, sperm maturation, and spermatozoa function in smokers compared with nonsmokers. Many studies have reported plant tissue contain secondary metabolites such as saponin, terpenoid, alkaloid, and flavonoid with antioxidant properties. Tropical fruit species that is known rich antioxidants content is banana, and one cultivar banana is Ketip. The aim of this research is to study the effect of Ketip banana peel ethanol extract on sperm viability of mice following cigarettes exposure. Data analysis showed that tobacco smoke exposure tend to dccrease sperm viability but insignificantly. Treatment with ethanol extract of ketip banana tend to reduce sperm viability. It is concluded that ethanol extract of ketip banana insignificantly increase sperm viability.
Pharella Acutidens Clams Population Dynamic in Mangrove Ekosistem, Cempi Bay,Woja District, Dompu Regency, West Nusa Tenggara
Authors: Dermawan Awan , Abidin Zaenal 
Published: January 2025

This study examines the growth of the Pharella acutidens clam in mangrove ecosystem of Cempi Bay, which has a habit of living in the substrate with a vertical shell position. These clams emit siphons when the hole they live is waterlogged to obtain food. Field observations showed that the depth of the Pharella acutidens hole was strongly influenced by the tide. During high tide, the clam moves close to the surface up to 10 cm from the substrate, while during low tide, the clam can bury itself to a maximum depth of 70 cm and a minimum of 25 cm. The minimum shell length recorded was 4.90 cm, while the maximum length of Pharella acutidens clams was 9.30 cm. the highest L∞ (9,71) and K (0.45) is found in locations that are densely vegetated, the lowest L∞ (7,88) and K (0.38) is found in low vegetated locations. There is something interesting because the low-vegetated location and higher disturbance has a relatively high recruitment value.
CLUSTER ANALYSIS OF K-MEANS AND WARD METHOD IN FORMING A ROBUST PORTFOLIO: AN EMPIRICAL STUDY OF JAKARTA ISLAMIC INDEX
Authors: Zain Zuva Amalina , Mussafi Noor Saif Muhammad , Supandi Epha Diana 
Published: January 2025

Building a portfolio is one method of reducing investment risk. Cluster analysis can shorten the time required to choose companies for a portfolio because it makes it easy to put firms in the same category together. To maintain the best state of the portfolio cluster analysis in the case of data containing outliers, K-means, and ward cluster analysis are employed in conjunction with a robust portfolio strategy. K-means clustering is a popular method for grouping data by assigning observations to clusters based on proximity to the cluster’s center meanwhile the Ward method is based on the size of the distance between clusters by minimizing the number of squares. This study seeks to determine the robust portfolio performance comparison outcomes produced by K-Means and Ward clustering utilizing the Sharpe ratio criterion. The Sharpe ratio is one of the most widely used methods to evaluate a portfolio’s risk-adjusted performance. The greater a portfolio's Sharpe ratio, the better its risk-adjusted performance. Stocks included in the Jakarta Islamic Index 70 (JII70) are used in this research. The results of the formation of a robust portfolio on K-Means clustering produce a return rate of 0.01038627 and risk of 0.1066364, while in the Ward cluster, the portfolio profit rate is obtained at 0.01632749 and the risk is 0.1340073. Based on the Sharpe ratio criteria, in this case, the robust portfolio with the Ward cluster is superior to the K-Means cluster because it produces a higher Sharpe value.
Lyme disease as an interdisciplinary problem
Authors: Turyanitsa S.R. , Turyanitsa S.M. , Korchynska O.O. , Loya N.О. , Shumilina T.R. 
Published: January 2025

Lyme disease (LD) is one of the most common transmissible diseases, but its course and outcomes for the health are poorly understood. Our knowledge of clinical symptoms, diagnosis and treatment is limited due to the lack of reliable epidemiological studies and long-term follow-up.Patients with suspected LD have a wide variety of symptoms, including fever, rash, fatigue, muscle and joint pain, facial paralysis and arthritis. Therefore, the clinical picture of LD sometimes resembles other pathologies (rheumatological, autoimmune diseases, neurological disorders, etc.).Rare coinfections with this disease transmitted through a tick bite have been described also. Therefore, doctors need to diagnose this disease in time and refer the patient to an infectious disease specialist, because an incorrectly established diagnosis complicates the choice of a treatment method in the future and further worsens the course of the disease.The objective: to determine the relevance of LD as an interdisciplinary problem.Materials and methods: The methods of bibliographic and content analysis of the literature, comparative approach and synthesis, statistical data processing, as well as semantic grouping regarding various aspects of symptoms, diagnosis and treatment of LD were used. 125 patient histories were also analyzed.Results. It was found that among 125 patients LD is most often manifested by symptoms characteristic of arthritis of various localizations, Sjogren’s syndrome, Raynaud’s syndrome, gout, spondylitis. Among the patients the age group 51-60 years (34,4 % - 43 patients) prevailed, followed by 31-40 years (18,4 % – 23 people), 41-50 years (17.6 % – 22 people), 61-70 (12 % – 15 persons) and.Women are more affected by LD – 60 % (75) than men – 40% (50). The largest number of symptoms is observed in the age group of 51-60 years – 34.4 % (43), and the least complaints are expressed by patients aged 10-20 years – 2.4 % (3).Conclusions. Modern diagnostic methods are effective if their indication and interpretation are well followed, otherwise they can lead to incorrect diagnosis.Treatment of Lyme disease is based on antibiotic therapy according to its stage and clinical manifestations. However, there are no clear guidelines for the treatment of functional, persistent symptoms that patients experience over a long period of time.
Spontaneous pneumothorax in women. Team approach of thoracic surgeons and gynecologists
Authors: Tkalich V.V. , Nedilia Yu.V. , Borysova V.I. , Galiiev O.V. , Savoliuk S.I. 
Published: January 2025

The objective: to implement the non-intubated treatment of pneumothorax in women and its inclusion in the protocol of Enhanced Recovery After Surgery (ERAS).Materials and methods. Surgical treatment using non-intubated video-assisted thoracic surgery (NIVATS) in 30 women with an average age of 38.56 ± 11.32 years (18–69 years) with spontaneous pneumothorax was analyzed. Most of the patients had a first episode of pneumothorax (90%), 3 people had a recurrent episode.All patients were operated by the method of non-intubated uniportal video-assisted thoracic surgery (NI-UVATS) with thoracic epidural anesthesia (TEA) as the main method of analgesia in the postoperative period. The average time to surgery was 1.5 days (0–5 days).Pathohistological studies confirmed the etiology of pneumothorax: bullous disease, thoracic endometriosis. Patients with confirmed thoracic endometriosis were referred to a gynecologist for consultation. The observation period was 48 months.Results. All patients underwent operative treatment and were satisfied with the NIVATS operation. The level of pain intensity according to the visual analogue scale was 1–2 points. The recurrence rate after NI-VATS surgery was 6.7% (2 patients) with confirmed thoracic endometriosis during the use of combined estrogen and progesterone hormone pills, the recurrences occurred after stop of hormonal treatment.Conclusions. Non-intubated video-assisted thoracic surgery for spontaneous pneumothorax in women can be considered a safe and effective treatment and as part of enhanced recovery after surgery (ERAS). Long-term follow-up and further clinical studies are needed to confirm the benefits of the proposed approach.
Peningkatan Perkembangan Kognitif Anak Usia Dini (AUD) Melalui Alat Permainan Edukatif (APE) Papan Berhitung
Authors: Arumsari Andini Dwi , Setyawan Dedi , Dzulkifli Dzulkifli , Marini Marini 
Published: January 2025

Abstrak: Alat permainan edukatif (APE) diberikan kepada anak usia dini (AUD) untuk membantu anak-anak belajar, salah satunya adalah mengoptimalkan perkembangan kognitifnya melalui pembelajaran berhitung. Alat permainan edukatif (APE) Papan berhitung dirancang secara khusus untuk menarik minat anak dan membantu mereka belajar berhitung dengan cara yang menyenangkan dan mudah dimengerti. Tujuan dalam penelitian ini adalah untuk mengetahui peningkatan perkembangan kognitif anak usia dini (AUD) melalui alat permainan edukatif (APE) Papan berhitung. Subyek dalam penelitian ini adalah siswa TK A di TK Aisyiyah Surabaya. Penelitian ini menggunakan metode penelitian pre eksperimen dengan model one group pretest post-test design. Pre dan post tes dilakukan menggunakan 10 indikator dalam Standar Tingkat Pencapaian Perkembangan Anak usia dini (STPPA) usia 5-6 tahun. Hasil dari penelitian ini adalah ada peningkatan perkembangan kognitif anak usia dini (AUD) melalui alat permainan edukatif (APE) Papan Berhitung dengan skor sig Uji beda dilakukan dengan menggunakan SPSS versi 29, dan mendapatkan hasil nilai signifikansi (Sig) sebesar 0.03.Kata Kunci: Alat Permainan Edukatif, Anak Usia Dini, Perkembangan Kognitif, siswa TK A Abstract : Educational game tools (APE) are given to early childhood (AUD) to help children learn, one of which is optimizing their cognitive development through learning to count. Educational game tools (APE) Counting boards are specifically designed to attract children's interest and help them learn to count in a fun and easy-to-understand way. The purpose of this study was to determine the increase in cognitive development of early childhood (AUD) through educational game tools (APE) Counting boards. The subjects in this study were students of Kindergarten A at Aisyiyah Kindergarten Surabaya. This research used pre experiment method with one group pre-test post-test design model. Pre and post tests were conducted using 10 indicators in the Early Childhood Development Achievement Level Standards (STPPA) aged 5-6 years. The results of this study are that there is an increase in cognitive development of early childhood (AUD) through educational game tools (APE) Counting boards with a sig score. The difference test was conducted using SPSS 29th version, and obtained a significance value (Sig) of 0.03. Keywords: Educational Game Tools, Early Childhood, Cognitive Development, Kindergarten students
Dinâmica das assimetrias na distribuição de renda segundo os arranjos familiares no Brasil
Authors: Silva Terra Taís Maria , Hermeto Ana Maria 
Published: January 2025

O trabalho explora o papel das mudanças dos arranjos familiares na distribuição de renda brasileira, utilizando microdados da Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC) no período de 2012 a 2023. Os arranjos familiares serão distribuídos em 5 grupos: casal com filhos, casal sem filhos, monoparentais femininos, unipessoais e outros arranjos. Observa-se tendências modestas, mas relevantes, como diminuição de casais com filhos e aumento de famílias unipessoais e casais sem filhos. Nota-se quedas recentes na desigualdade de renda, acentuadas em 2020, devido ao empobrecimento geral, intensificado com a pandemia. Por fim, resultados da regressão quantílica sugerem que há assimetrias estatisticamente significativas entre os percentis ao longo da distribuição de renda em todos os arranjos familiares e resultados da decomposição do índice de Theil indicam que a distância “dentro dos grupos” é mais relevante na distribuição da renda familiar, embora o peso da desigualdade “entre grupos” esteja aumentando desde 2019.
Autoencoder Artificial Neural Network Model for Air Pollution Index Prediction
Authors: Basir Nor Irwin , Tan Kathlyn Kaiyun , Djarum Danny Hartanto , Ahmad Zainal , Vo Dai-Viet N. , Jie Zhang 
Published: January 2025

Air pollution, a significant global challenge driven by industrialization, urbanization, and population growth, is caused by the emission of harmful gases, particulates, and biological molecules into the atmosphere, posing serious risks to health and the environment. Key sources include power plants, industrial activities, vehicles, and residential heating. Thus, effective air quality monitoring and forecasting are crucial to mitigating the adverse impacts of pollution. This paper presents shallow and deep sparse autoencoder artificial neural network models to improve the prediction of the Air Pollution Index (API) in Perak Darul Ridzuan, Malaysia, as a case study. The results show that the deep sparse autoencoder achieves better prediction accuracy with and values of 0.1474 and 0.8331, respectively, compared to 0.1515 and 0.8300 for the shallow sparse autoencoder. The performance of these autoencoder models is also compared with other models, such as feedforward artificial neural networks (FANN) and principal component analysis (PCA). The findings confirm that both autoencoder models enhance API prediction accuracy, with the deep sparse autoencoder emerging as the optimal model, highlighting the potential of deep learning in improving air quality prediction.
ABSTRAK: Pencemaran udara, merupakan satu cabaran global yang didorong oleh perindustrian, urbanisasi pesat, dan pertumbuhan populasi, adalah disebabkan oleh pelepasan gas, partikel, dan molekul biologi merbahaya ke atmosfera, menimbulkan risiko serius kepada kesihatan dan alam sekitar. Sumber utama termasuk loji janakuasa, aktiviti industri, kenderaan, dan pemanasan kediaman. Oleh itu pemantauan dan ramalan kualiti udara penting bagi mengurangkan kesan buruk pencemaran. Kajian ini membentangkan model rangkaian neural tiruan pengauto kod jarang ‘cetek’ dan pengauto kod jarang ‘dalam’ memperbaiki ramalan Indeks Pencemaran Udara (API) di negeri Perak Darul Ridzuan, Malaysia sebagai kes kajian. Dapatan kajian menunjukkan bahawa pengautokod jarang ‘dalam’ mencapai ketepatan ramalan lebih baik, dengan nilai MSE dan R2 masing-masing sebanyak 0.1474 dan 0.8331, berbanding 0.1515 dan 0.8300 bagi pengautokod jarang ‘cetek’. Prestasi model pengautokod ini juga dibandingkan dengan model lain, seperti rangkaian neural tiruan suapan hadapan (FANN) dan analisis komponen utama (PCA). Hasil kajian mengesahkan bahawa kedua-dua model pengautokod meningkatkan ketepatan ramalan API, dengan pengautokod jarang ‘dalam’ muncul sebagai model paling optimum, menonjolkan potensi pembelajaran mendalam ‘dalam’ meningkatkan ramalan kualiti udara.
Utilizing MFCCs and TEO-MFCCs to Classify Stress in Females Using SSNNA
Authors: Zainal Nur Aishah , Asnawi Ani Liza , Ibrahim Siti Noorjannah , Mohamed Azmin Nor Fadhillah , Harum Norharyati , Mat Zin Nora 
Published: January 2025

All individuals are susceptible to experiencing stress in their everyday lives. Nevertheless, stress has a greater influence on females due to both biological and environmental factors. This study utilized female speeches to detect and classify stress and no stress in women. Using speech, composed of non-invasive and non-intrusive approaches, helps to identify stress better in females. A comparative analysis was conducted between Mel-frequency Cepstral Coefficients (MFCCs) and Teager Energy Operator- MFCCs (TEO-MFCCs) to determine the best speech feature for classifying emotions associated with stress and no-stress conditions for female voices. With the assistance of the Stress Speech Neural Network Architecture (SSNNA), an improved accuracy of 93.9% was achieved. This research showed that MFCCs enhanced higher-frequency components in stressed speech, distinguishing between stress and no-stress classes. This study shows that SSNNA achieved high accuracy with 14 female voices, confirming its ability to function independently of speaker identity.
ABSTRAK: Semua individu terdedah kepada stres dalam kehidupan seharian mereka. Walau bagaimanapun, stres memberi pengaruh yang lebih besar terhadap wanita akibat faktor biologi dan persekitaran. Kajian ini menggunakan ucapan untuk mengesan dan mengklasifikasikan stres dan tiada stres dalam kalangan wanita. Penggunaan ucapan, yang merupakan pendekatan tidak invasif dan tidak mengganggu, membantu mengenal pasti tekanan dengan lebih baik dalam kalangan wanita. Analisis perbandingan telah dijalankan antara Mel-frequency Cepstral Coefficients (MFCCs) dan Teager Energy Operator-MFCCs (TEO-MFCCs). Tujuannya adalah untuk menentukan ciri ucapan terbaik bagi mengklasifikasikan emosi yang berkaitan dengan keadaan stres dan tiada stres bagi suara wanita. Dengan bantuan Stress Speech Neural Network Architecture (SSNNA), metrik prestasi yang lebih tinggi dengan ketepatan 93.9% telah dicapai. Penyelidikan ini menunjukkan bahawa MFCCs meningkatkan komponen frekuensi tinggi dalam ucapan yang stres, secara efektif membezakan antara kelas stres dan tiada stres. Kajian ini menunjukkan bahawa SSNNA mencapai ketepatan tinggi dengan 14 suara wanita, mengesahkan ia berfungsi secara bebas daripada identiti penutur.