bluuebunny/crossref_metadata_2025_split huggingface dataset:
Veterinary medicine under COVID-19: a mixed-methods analysis of student and practitioner experiences in Austria
Authors: Humer Elke , Winter Stefanie , Probst Thomas , Pieh Christoph , Dale Rachel , Brühl Deianira , Neubauer Viktoria 
Published: November 2024

BackgroundThis study aimed to provide a detailed analysis of the pandemic’s impact on the veterinary profession and education in Austria.MethodsTwo online surveys were conducted from November 2022 to January 2023, inviting all veterinarians and veterinary students in Austria to share their experiences on the impact of the pandemic on their veterinarian work and education in a free text question.ResultsA total of n = 289 veterinarians and n = 272 veterinary students provided an answer. In summary, 39.8% of veterinarians reported no impact by the pandemic, while others experienced changes in workload (19.7%), changes in client behavior (14.9%), implementation of safety measures (13.1%), and organizational changes (13.1%). Additional impacts included effects on mental health, private life, finances, as well as physical health. Changes were more frequently mentioned in veterinarians working with pets compared to those working with livestock. In the student panel, only a minority reported no significant impact (8.1%) but 44.9% reporting changes due to online and hybrid learning. Key issues included impaired learning conditions (34.9%), and social distancing (34.6%) leading to social isolation. Some students appreciated increased flexibility and reduced commuting (10.7%), while others experienced mental health challenges (10.7%). Further impacts were related to the implementation of safety measures (5.5%), organizational changes (4.8%) and impaired physical health due to infection (1.1%). Negative changes related to distance learning were mainly reported by students in the final study phase, whereas those in the first study phase reported more positive aspects related to online/hybrid learning.ConclusionOverall, this study highlights the significant impact of the COVID-19 pandemic on veterinary education and professional practice in Austria, revealing diverse challenges for students and relatively lower but still notable effects on practicing veterinarians. Future research should monitor these impacts longitudinally and explore the integration of beneficial practices into standard veterinary education and care, such as effective digital learning platforms and appointment-based systems.
Establishment of a mouse model of ovarian oxidative stress induced by hydrogen peroxide
Authors: Liang Huili , Wu Shuaishuai , Zhang Zhenwei , Khan Muhammad Zahoor , Zhan Yandong , Zhu Mingxia , Wang Shoushan , Liu Wenqiang , Wang Changfa , Cao Guiling , Han Ying 
Published: November 2024

IntroductionOxidative stress, resulting from environmental changes, significantly affects female fertility. Developing a mouse model to study oxidative stress lays the groundwork for research into human reproductive health and livestock fertility.Materials and methodsIn this study, we established and evaluated an oxidative stress model by administering hydrogen peroxide (H2O2) to mice. ICR mice of similar age (7–8 weeks old) and average body weight (31.58 ± 1.12 g) were randomly assigned to four groups (A, B, C, and D). Group A served as the control and was injected with a saline solution, while groups B, C, and D received saline solutions containing 0.75%, 1.50%, and 3.0% H2O2, respectively, over one week. We measured the body weights of all mice before and after the experimental period.Results and discussionOur findings showed that the average body weight of mice in groups A and B increased, while groups C and D experienced weight loss. Group C showed a significantly lower average weight gain compared to groups A and B, and group D exhibited an even more pronounced reduction in weight gain. Although group D had a high mortality rate, there was no significant difference in mortality rates among groups B, C, and D. Serum malondialdehyde (MDA) content increased with higher concentrations of H2O2, with a significant difference noted between groups C and A. Catalase (CAT) activity in group B was significantly higher than in group A, while superoxide dismutase (SOD) activity in group C was notably elevated compared to groups A and B. Conversely, glutathione peroxidase (GSH-Px) activity in group C was significantly lower than in both group A and group B. Hematoxylin and eosin (HE) staining revealed changes in ovarian morphology and follicle dynamics. The percentage of atretic follicles in group C was significantly higher than in the control group, and group D had a significantly lower total number of healthy follicles compared to the untreated group. Increased H2O2 content resulted in a reduction of ovary size and an irregular appearance in group D.ConclusionBased on our findings, treatment with 1.50% H2O2 effectively established an oxidative stress model in mice within 1 week. This model serves as a valuable reference for future clinical studies on oxidative stress and reproductive disorders in female animals and humans.
Improved Bacterial Foraging Optimization Algorithm with Machine Learning-Driven Short-Term Electricity Load Forecasting: A Case Study in Peninsular Malaysia
Authors: Zaini Farah Anishah , Sulaima Mohamad Fani , Razak Intan Azmira Wan Abdul , Othman Mohammad Lutfi , Mokhlis Hazlie 
Published: November 2024

Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. The IBFOA based on the sine cosine equation addresses the limitations of fixed chemotaxis constants in the original bacterial foraging optimization algorithm (BFOA), enhancing its exploration and exploitation capabilities. Finally, the load forecasting model based on LSSVM-IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. The comparative analysis demonstrates the model, achieving the highest determination coefficient (R2) of 0.9880 and significantly reducing the average MAPE value by 28.36%, 27.72%, and 5.47% compared to the deep neural network (DNN), LSSVM, and LSSVM-BFOA, respectively. Additionally, IBFOA exhibits faster convergence times compared to BFOA, highlighting the practicality of LSSVM-IBFOA for short-term load forecasting.
Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network
Authors: Lu Yujie , Du Qingbin , Zhang Ruijia , Wang Bo , Liu Zigeng , Tang Qizhe , Dai Pan , Fan Xiangxiang , Huang Chun 
Published: November 2024

In the field of fiber-optic sensing, effectively reducing the noise of sensing spectra and achieving a high signal-to-noise ratio (SNR) has consistently been a focal point of research. This study proposes a deep-learning-based denoising method for fiber-optic sensors, which involves pre-processing the sensor spectrum into a 2D image and training with a cycle-consistent generative adversarial network (Cycle-GAN) model. The pre-trained algorithm demonstrates the ability to effectively denoise various spectrum types and noise profiles. This study evaluates the denoising performance of simulated spectra obtained from four different types of fiber-optic sensors: fiber Fabry–Perot interferometer (FPI), regular fiber Bragg grating (FBG), chirped FBG, and FBG pair. Compared to traditional denoising algorithms such as wavelet transform (WT) and empirical mode decomposition (EMD), the proposed method achieves an SNR improvement of up to 13.71 dB, an RMSE that is up to three times smaller, and a minimum correlation coefficient (R2) of no less than 99.70% with the original high-SNR signals. Additionally, the proposed algorithm was tested for multimode noise reduction, demonstrating an excellent linearity in temperature response with a R2 of 99.95% for its linear fitting and 99.74% for the temperature response obtained from single-mode fiber sensors. The proposed denoising approach effectively reduces the impact of various noises from the sensing system, enhancing the practicality of fiber-optic sensing, especially for specialized fiber applications in research and industrial domains.
Pengaruh Pengetahuan Pajak, Tarif Pajak, Sanksi Pajak, Tax Amnesty dan Program Pengungkapan Sukarela terhadap Kepatuhan Pajak Karyawan AHASS di Kabupaten Semarang
Authors: Aini Nurul , Bambang Ahmad Indarto  , Fitri Dwi Jayanti  
Published: November 2024

This study aims to determine the effect of tax knowledge, tax rates, tax sanctions,Tax Amnesty And the Voluntary Disclosure Program for Tax Compliance in Ahass, Semarang Regency. This study used a quantitative method by processing primary data through questionnaires given to 100 ahass employees. The sampling technique ispurposive sampling, because the researcher took a random sample where the sample group was targeted to have certain attributes. The data obtained were processed with SPSS Version 20. The analysis used included validity and reliability tests, descriptive statistical tests, classical assumption tests, and hypothesis testing. The results of the research tests showed that simultaneously Tax Knowledge, Tax Rates, Tax Sanctions, Tax Amnesty and Knowledge Programs Taxes significantly influence Tax Compliance. Partially (1) Tax Knowledge has no significant effect on Tax Compliance. (2) Tax Rates have a significant effect on Tax Compliance. (3) Tax Sanctions have no significant effect on Tax Compliance. (4)Tax Amnesty no significant effect on tax compliance. (5) Voluntary Disclosure Program has a significant effect on Tax Compliance.
Abstrak

Penelitian ini bertujuan untuk mengetahui Pengaruh Pengaruh Pengetahuan Pajak, Tarif Pajak, Sanksi Pajak, Tax Amnesty Dan Program Pengungkapan Sukarela Terhadap Kepatuhan Pajak Di Ahass Kabupaten Semarang. Penelitian ini menggunakan metode kuantitatif dengan mengolah data primer melalui kuesioner yang diberikan kepada karyawan ahass sebanyak 100 responden. Teknik pengambilan sampel adalah purposive sampling, karena peneliti mengambil sampel secara acak dimana kelompok sampel ditargetkan memiliki atribut-atribut tertentu. Data yang diperoleh diolah dengan SPSS Versi 20. Analisis yang digunakan meliputi uji validitas dan reliabilitas, uji statistik deskriptif, uji asumsi klasik, dan uji hipotesis Hasil uji penelitian menunjukkan bahwa secara simultan Pengetahuan Pajak, Tarif Pajak, Sanksi Pajak, Tax Amnesty Dan Program Pengetahuan Pajak secara signifikan berpengaruh terhadap Kepatuhan Pajak. Secara parsial (1) Pengetahuan Pajak tidak berpengaruh signifikan terhadap Kepatuhan Pajak. (2) Tarif Pajak berpengaruh signifikan terhadap Kepatuhan Pajak. (3) Sanksi Pajak tidak berpengaruh signifikan terhadap Kepatuhan Pajak. (4) Tax Amnesty tidak berpengaruh signifikan terhadap kepatuhan pajak. (5) Program Pengungkapan Sukarela berpengaruh signifikan terhadap Kepatuhan Pajak.
Pengaruh Rasio Profitabilitas terhadap Earning Per Share pada BPR Konvensional Se Kabupaten Semarang (Studi Kasus Pada Tahun 2016-2021)
Authors: Isna Nur Amalia  , Bambang Ahmad Indarto  , Arda Raditya Tantra  
Published: November 2024

BPR is a microfinance institution that has a strategic function in providing financial services to small and medium-sized communities and SMES, whose existence is important in helping the development and economy of the community, especially rural areas. the purpose of this study was to determine the effect of profitability ratios on earning per share at conventional BPRs throughout Semarang Regency in 2016-2021. By using quantitative research methods to examine the effect of each of the variables NPL, LDR, CAR, BOPO, and Size on EPS using statistical methods and data processing with the SPSS application program. The type of data used is secondary data obtained from conventional BPR publication reports for the 2016-2021 period on the official OJK website. The population in this study were conventional BPRS throughout Semarang Regency and the sample was taken using a purposive sampling method, so that 71 observations were obtained. The results of the study show that NPL, LDR, CAR, BOPO and Size simultaneously have a significant effect on EPS. Partially, NPL has no effect on EPS while LDR, CAR, BOPO and Size have an effect on EPS.
Abstrak
BPR adalah lembaga keuangan mikro yang memiliki funsi strategis dalam memberikan layanan keuangan kepada masyarakat kecil dan menengah serta UMKM, yang keberadaannya penting dalam membantu perkembangan dan perekonomian masyarakat terutama wilayah pedesaan. tujuan dari penelitian ini adalah untuk mengetahui Pengaruh Rasio Profitabilitas Terhadap Earning Per Share Pada BPR Konvensional Se Kabupaten Semarang Pada Tahun 2016-2021. dengan mengunakan metode penelitian kuantitatif untuk menguji masing-masing pengaruh dari variabel NPL, LDR, CAR, BOPO, dan Size terhadap EPS dengan mengunakan metode statistik dan olah data dengan program aplikasi SPSS. Jenis data yang digunakan adalah data sekunder yang diperoleh dari laporan publikasi BPR Konvensional periode 2016-2021 pada situs resmi OJK. Populasi pada penelitian ini adalah BPR Konvensional se Kabupaten Semarang dan pengambilan sampel dengan purposive sampling method, sehingga diperoleh 71 pengamatan. dengan hasil penelitian menujukkan bahwa secara stimultan NPL, LDR, CAR, BOPO dan Size secara signifikan berpengaruh terhada EPS. Secara parsial NPL, tidak berpengaruh terhadap EPS sedangkap LDR, CAR, BOPO dan Size berpengaruh terhadap EPS.
Visualization of patterned alkanethiol monolayers on an antireflective substrate using a reflected-light microscope
Authors: Murata Daiki , Tanigaki Satoshi , Kitamura Masatoshi , Hattori Yoshiaki 
Published: November 2024

Abstract
Organic monolayers are extensively used in various applications to modify substrate surfaces. However, their characterization remains challenging owing to their small thickness. Optical visualization techniques using antireflective (AR) substrates are particularly effective for patterned monolayers. In this study, we demonstrate the visualization of patterned alkanethiol monolayers on an AR multilayer substrate produced through microcontact printing methods. The AR substrate was designed to achieve near-zero reflectance at ∼540 nm. The formation of the octadecanethiol monolayer caused a shift of approximately 2 nm toward longer wavelengths in the reflection spectrum. This shift was detected as a color difference by the digital camera attached to a reflected-light microscope. The contrast of the imaged pattern was enhanced by over 15% using a narrow band-pass filter at 530 or 550 nm. Consequently, line patterns with a width of approximately 6 μm were easily photographed using a commercially available color camera in a standard setup.
A Comprehensive Approach to Fault Classification of Helicopter Engines with Adaboost Ensemble Model
Authors: Pankaj Peeyush , Jain Sammit , Joshi Shyam 
Published: November 2024

This work is based on the PHM North America 2024 Conference Data Challenge’s datasets of Helicopter turbine engine performance measurements. These datasets were large and moderately imbalanced. For dealing with these challenges, we demonstrate significant tools covering feature engineering, augmentation and selection, model exploration, visualizations, model explainability and confidence margin estimation. This work was performed in its entirety using MATLAB. All these tools will be generally applicable to data-driven modeling and prediction of health to real life applications.
Initially, we explored the 742k observations in the training set, noting a 60-40 split between healthy and faulty labels, and identified two major operational clusters within the data. We enhanced the dataset by removing duplicates and engineered new features based on domain knowledge, expanding the feature set to 242 dimensions.
However for the torque margin estimation, we trained a regression model on a limited subset (18 features), which includes engineered features using domain knowledge, quadratic terms and linear interaction between all the terms. For the final submission, we utilized a stepwise linear regression model to optimize feature selection. This approach achieved a perfect regression score on test data, validated by a consistent torque margin residual range of +/- 0.5%. The model's RMSE and MAE metrics were optimal for employing a normal distribution probability density function.
For , we reduced the feature set to 58 using dimensionality reduction techniques and balanced the data with upsampling and down-weighing the minority class. We employed ASHA (Asynchronous Successive Halving Algorithm) in conjunction with AutoML to efficiently determine the most suitable model family, significantly saving compute time. Subsequently, we trained ensemble models, including bagged tree and AdaBoost (Adaptive Boosting), which minimized false negatives and positives, achieving robust classification performance. This was particularly critical given the high penalty for false negatives in the data challenge. The MathWorks team score on Testing Data was 0.9686 at the close of competition. This was further improved to 0.9867.
Our approach demonstrates the effectiveness of combining strategic data processing, feature engineering, and model selection to enhance predictive accuracy in complex operational datasets.
RESPON BEBERAPA VARIETAS BAWANG MERAH (Allium cepa L) AKIBAT APLIKASI PUPUK ORGANIK CAIR LIMBAH IKAN RUCAH
Authors: Kurnia Intan , Aryani Farida , Hasibuan Ikhsan 
Published: November 2024

Pada tahun 2019, Bengkulu menghasilkan sekitar 523,4 ton dari total produksi bawang merah nasional (0,033% dari total produksi nasional). Sebaliknya, penduduk Provinsi Bengkulu membutuhkan bawang merah sebanyak 5.182 ton setiap tahun. Perlu diupayakan peningkatan produksi bawang merah di Provinsi Bengkulu karena hal tersebut. Upaya peningkatan produksi bawang merah dengan pemanfaatan varietas unggul dan aplikasi POC pupuk organik cair ikan rucah (POC). Ikan rucah merupakan salah satu jenis ikan yang memiliki dagimg relatif sedikit dan banyak duri, sehingga jarang dimanfaatkan oleh masyarakat umum. Limbah ikan rucah berpotensi untuk dimanfaatkan sebagai bahan baku dalam pembuatan pupuk organik cair karena mengandung hara untuk tanaman. Penelitian ini bertujuan untuk mengetahui varietas mana yang cocok di budidayakan di bengkulu dan dosis terbaik POC ikan rucah pada pertumbuhan dan hasil tanaman bawang merah.. Petak utama adalah Varietas Bawang Merah (A); varietas Lokanata (A1), varietas Sanren F1 (A2), dan varietas Selupu merah (A3). Sedangkan Anak petak adalah Dosis POC ikan rucah (B) yang terdiri dari 4 taraf; 0 ml/l (B0), 100 ml/l (B1), 200 ml/l (B2), dan 300 ml/l (B3). Hasil penelitian menunjukkan Perlakuan varietas memberikan pengaruh sangat nyata terhadap peubah pertumbuhan bawang merah dan memberikan pengaruh nyata dan sangat nyata terhadap peubah hasil tanaman bawang merah.Perlakuan dosis POC memberikan pengaruh berbeda tidak nyata terhadap peubah pertumbuhan dan hasil tanaman bawang merah, kecuali pada peubah hasil ton/ha. Tidak terdapat interaksi antara kedua perlakuan yang diuji terhadap pertumbuhan dan hasil tanaman bawang merah.
Kata kunci: Bawang merah, Lokananta, Sanren F1, POC ikan rucah
PENGARUH MACAM NANGAN DAN PUPUK NITROGEN TERHADAP PERTUMBUHAN BIBIT KAKAO (Theoroma cacao L.)
Authors: Kesumawati Neti , Aryani Farida , Hayati Rita , Suryadi  , Armadi Yukiman 
Published: November 2024

Penelitian bertujuan mengetahui pengaruh macam naungan dan dosis pupuk nitrogen terhadap pertumbuhan bibit kakao (Theobroma cacao l.). Penelitian ini menggunakan rancangan acak kelompok lengkap (RAKL) yang disusun secara factorial dengan dua faktor. Faktor pertama adalah naungan yang terdiri dari perlakuan tanpa naungan (S0), atap rumbia (S1), atap plastic (S2), dan atap gedeg (S3), sedangkan faktor kedua adalah pupuk nitrogen yang terdiri dari dosis 0 gram Urea/bibit (N0), dosis 2,5 gram Urea/bibit (N1), dosis 5 gram Urea/bibit (N2), dosis 7,5 gram Urea/bibit (N3), dosis 10 gram Urea/bibit (N4). Pengamatan meliputi tinggi tanaman, jumlah daun,ndiameter batang, berat basah tajuk, berat kering tajuk, berat basah akar, berat kering akar.
Perlakuan pemupukan berpengaruh tidak nyata terhadap tinggi tanaman, diameter batang, berat basah akar, berat kering akar, tetapi berpengaru sangat nyata terhadap jumlah daun, berat basah tajuk dan berat kering tajuk. Perlakuan naungan berpengaruh sangat nyata terhadap semua parameter, yaitu tinggi tanaman, jumlah daun, diameter batang, berat basah basah tajuk, berat kering tajuk, berat basah akar dan berat kering akar. Hasil penelitian pengaruh dosis pupuk nitrogrn dan macam naungan tidak terdapt interaksi terhadap pertumbuhan bibit kakao
Kata Kunci : Tanaman kakao, Pupuk nitrogen, Macam naungan
Pemanfaatan Ekstrak Kulit Bawang Merah (Allium Cepa L.) Dalam Berbagai Konsentrasi Pada Tanaman Sawi Pokcoy (Brassica rapa L)
Authors: Pitaloka Lola , Sunarti  , Rustianti Sri 
Published: November 2024

Penelitian ini bertujuan untuk mengetahui respon tanaman sawi pokcoy terhadap pemberian ekstrak kulit bawang merah dalam berbagai konsentrasi yang dibudidayakan secara organik dan untuk mengetahui konsentrasi terbaik dari ekstrak kulit bawang merah yang dapat memberikan merespon pertumbuhan dan hasil tanaman sawi pokcoy yang terbaik. Penelitian dilaksanakan di Jl. Merapi Raya, Kelurahan Padang Nangka. Kecamatan,Singgaran Pati Kota Bengkulu dari bulan September Sampai Desember 2023. Alat yang digunakan dalam penelitian ini adalah : Blender, polybag, cangkul, timbangan digital, gembor, hand sprayer, penggaris, alat tulis, parang/pisau, meteran, waring, dan kamera. Bahan yang digunakan yaitu benih pokchoy, kulit bawang merah, media tanah, pupuk kandang sapi dan air. Percobaan menggunakan Rancangan Acak Lengkap (RAL) faktor tunggal. Sebagai perlakuan adalah konsentrasi limbah kulit bawang merah dan perlakuan diulang sebanyak 3 (tiga) kali. Perlakuan terdiri dari 5 taraf yaitu: K1 : Konsentrasi ekstrak kulit bawang merah 100 g/l air. K2 : Konsentrasi ekstrak kulit bawang merah 150 g/l air. K3 : Konsentrasi limbah kulit bawang merah 200 g/lt air. K4 : Konsentrasi ekstrak kulit bawang merah 250 g/lt air. K5 : Konsentrasi ekstrak kulit bawang merah 300g/lt air. Ulangan 3 kali dan setiap satuan percobaan ada 5 tanaman yang diamati. Total terdapat 75 tanaman yang diamati. Hasil sidik ragam yang bebeda nyata akan diuji lanjut dengan menggunakan Ducan’s Multiple Range Test (DMRT) dengan taraf uji 0,05. Peubah yang diamati adalah Tinggi Tanaman, jumlah daun, Berat basah dan Berat Kering tanaman. Hasil pengamatan menunjukkan bahwa perlakuan ekstrak kulit bawang merah dengan berbagai konsentrasi memberikan pengaruh yang sangat nyata terhadap semua peubah yang diamati (tinggi tanaman minggu ke-2, ke-4, ke-6, jumlah daun minggu ke-2, ke-4, ke-6, berat basah dan berat kering). Perlakuan konsentrasi terbaik didapat pada perlakuan K5 (300 g/l air).
Kata Kunci : Ekstrak kulit bawang merah (Allium cepa L), Pupuk organic cair, Sawi Pokcoy (Brassica rapa L)