bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Perkembangan Teknologi dan Tren Terkini Pada Platform Metaverse dalam Pendidikan: Perspektif Manajerial
Authors: Guspian Iza , Noviyanti Indah , Aryansyah Ary Fakturrachman
Published: January 2025

Seiring dengan berkembangnya dunia virtual, peran metaverse dalam pendidikan semakin meningkat dan memerlukan integrasi yang handal dalam sistem pendidikan untuk mencapai tujuan optimal. Penelitian ini menggunakan analisis bibliometrik untuk mengevaluasi perkembangan dan tren terkini pada platform metaverse dalam konteks pendidikan berdasarkan artikel-artikel yang diterbitkan antara tahun 2007 hingga 2023. Meskipun teknologi dunia virtual imersif dan infrastrukturnya masih dalam tahap pengembangan untuk lintas platform, perhatian penelitian terhadap dampak transformatif metaverse dalam pendidikan terus meningkat. Hasil penelitian menunjukkan bahwa dalam era digital yang semakin cepat berubah, dengan penerapan teknologi metaverse khususnya yang didukung oleh kecerdasan buatan dari prediksi hingga evaluasi, bahwasanya menjadi sangat penting dalam mengatasi tantangan interaksi di lingkungan virtual. Tren saat ini menunjukkan peningkatan penggunaan metaverse dan neural network pada deep learning dan machine learning seperti CNN, ANN, RNN, atau kombinasi ANN-RNN. Selain itu, perspektif manajerial juga melihat bahwa perlunya skenario pembelajaran yang tepat dengan memanfaatkan teknologi metaverse terintegrasi secara efektif agar dirasakan manfaat dalam pendidikan, serta diketahui virtual simulation learning, augmented learning dan collaborative learning banyak digunakan untuk keperluan medis. Penelitian ini memberikan kontribusi penting bagi peneliti dan pendidik dengan meningkatkan pemahaman mengenai platform metaverse dan kecerdasan buatan, serta menawarkan bagaimana menerapkan teknologi ini untuk mencapai hasil pendidikan inovatif yang lebih baik di masa depan.
Analisis Kesalahan Mahasiswa dalam Menyelesaikan Soal Geometri Analitik Ditinjau Dari Prestasi Belajar
Authors: Arwadi Fajar , Asmaun Asmaun , Ruslan Ruslan
Published: January 2025

Penelitian ini bertujuan untuk menganalisis kesalahan mahasiswa dan faktor penyebab kesalahan mahasiswa dalam menyelesaikan soal Geometri Analitik yang ditinjau dari prestasi belajar mahasiswa. Penelitian ini adalah penelitian kualitatif dengan pendekatan deskriptif. Penelitian ini dilakukan di Jurusan Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar pada semester genap tahun 2023/2024. Subjek dalam penelitian ini adalah mahasiswa Jurusan Matematika yang terdiri dari 3 orang yaitu satu orang mahasiswa dengan prestasi belajar tinggi, satu orang mahasiswa dengan prestasi belajar sedang, dan satu orang mahasiswa dengan prestasi belajar rendah. Peneliti mengambil tiga orang subjek untuk masing-masing kategori dengan pertimbangan bahwa tiga orang cukup untuk menjawab tujuan penelitian. Teknik sampling yang digunakan pada penelitian ini yaitu purposive sampling karena peneliti mengambil subjek berdasarkan kriteria yang telah ditetapkan oleh peneliti. Teknik pengumpulan data pada penelitian ini yaitu tes tertulis dan wawancara. Teknik analisis data meliputi kondensasi data, penyajian data, dan penarikan kesimpulan. Kesalahan yang dilakukan oleh mahasiswa dengan IPK atau prestasi belajar tinggi adalah kesalahan dalam melakukan dalam membuat rencana penyelesaian atau model matematika.  Kesalahan yang dilakukan oleh mahasiswa dengan IPK atau prestasi belajar sedang adalah tidak memahami apa yang diketahui pada soal dan kesalahan dalam menuliskan notasi atau simbol matematika. Sedangkan Kesalahan yang dilakukan oleh mahasiswa dengan IPK atau prestasi belajar rendah adalah tidak mampu meneruskan proses penyelesaian atau membuat model atau dengan kata lain, melakukan kesalahan dalam menyelesaikan model matematika.
Analisis dan Penanganan Kemampuan Membaca Al-Qur'an Mahasiswa PGMI Ma'had Al Jami'ah UIN Walisongo Semarang
Authors: Khikmah Nur
Published: January 2025

Profil lulusan program studi PGMI adalah mencetak pendidik yang memiliki komptensi dalam mendidik siswa pada mata pelajaran umum dan agama di sekolah dasar. Salah satu persyaratan pertama pendidik bisa mengajar materi agama adalah memiliki kemampuan membaca Al-Qur'an dengan benar dan lancar. Tujuan dari penelitian ini adalah untuk menilai kemahiran membaca Al-Qur'an mahasiswi PGMI di Ma'had Walisongo, mengidentifikasi intervensi untuk meningkatkan kemahiran membaca Al-Qur'an para mahasiswa ini, dan menguraikan tantangan yang terkait dengan penerapan intervensi tersebut dalam praktik. Penelitian ini merupakan penelitian lapangan dan mengambil bentuk penelitian deskriptif kualitatif. Metode pengumpulan data yang meliputi survei, wawancara, dan observasi. Subjek penelitian adalah mahasiswa PGMI Ma'had angkatan 2023. Hasil penelitian menunjukkan bahwa mahasiswa PGMI Ma'had Al-Jami'ah UIN Walisongo memiliki kemampuan membaca Al-Qur'an yang beragam. Hasil awal menunjukkan bahwa 22 dari 79 siswa masih berada pada taraf Iqro'. Program seperti Shobahul Qur'an dan pembelajaran tajwid juga memiliki dampak yang signifikan, dengan 62 siswa menerima predikat yang baik, 16 siswa menerima predikat yang sangat baik, dan satu siswa menerima predikat yang luar biasa. Namun, masalah tetap ada, seperti siswa yang tidak terlalu terlibat dalam program dan kekurangan fasilitas pendukung, seperti ruang belajar yang tidak nyaman. Hasil ini menunjukkan bahwa kurikulum PGMI harus mengintegrasikan pembelajaran tajwid dan keterampilan membaca Al-Qur'an. Ini dilakukan untuk memastikan bahwa calon guru MI memiliki dasar yang kuat dalam pendidikan keislaman. Untuk membuat pembelajaran lebih efektif, Ma'had harus menyediakan ruang belajar yang nyaman dan memiliki alat peraga seperti papan tulis. Program Ma'had dapat melibatkan orang tua lebih aktif untuk mendukung komitmen siswa. Mengadopsi pendekatan pendidikan modern, seperti penggunaan media digital untuk tajwid dan instruksi bacaan Al-Qur'an, dapat meningkatkan minat dan hasil belajar siswa.
Penalaran Visual Siswa dalam Menyelesaikan Soal Geometri Berbasis Etnomatematika Ukiran Pa’dadu
Authors: Delastri Lusiana , Lebang Agnesia , Langi’ Evy Lalan , Duma Sonny Yalti
Published: January 2025

Penalaran visual merupakan salah satu kompetensi penting dalam pembelajaran matematika sekolah termasuk geometri. Membelajarkan siswa menggunakan media ukiran Toraja diharapkan dapat membantu siswa dalam mengembangkan kemampuan penalaran visual. Penelitian ini bertujuan untuk mendeksripsikan proses penalaran visual siswa dalam menyelesaikan soal geometri berbasis etnomatematika pada motif ukiran Toraja. Jenis penelitian yang digunakan adalah kualitatif. Pengumpulan data diawali dengan memberikan soal geometri yang menampilkan ukiran Pa’dadu kepada siswa kelas IX di salah satu SMPN di Toraja Utara. Berdasarkan jawaban siswa, dipilih dua subjek dalam penelitian ini. Selanjutnya, kedua subjek tersebut diwawancarai untuk mengetahui proses penalaran visualnya. Tahapan análisis data yaitu reduksi data, penyajian data dan penarikan kesimpulan.  Hasil penelitian mengungkapkan bahwa Terdapat tiga tahapan penalaran visual siswa dalam menyelesaikan soal geometri yang ditampilkan dalam ukiran Pa’dadu, yaitu investigasi, interpretasi, dan aplikasi. Bernalar secara visual dimulai ketika siswa secara komunikatif mendeskripsikan hasil identifikasi dan hubungan motif yang ada dalam ukiran Pa’dadu  dengan konsep matematika, menghubungkan antar konsep matematika yang terdapat dalam ukiran, dan selanjutnya digunakan untuk menyelesaikan soal. Dengan demikian, pengintegrasian.
Pengembangan Media Pembelajaran Augmented Reality (AR) untuk Meningkatkan Hasil Belajar Siswa Pada Pelajaran IPA
Authors: Alfarizi Muhadab , Nasihudin Nasihudin , Mahmud Muhammad Rifqi
Published: January 2025

Penelitian ini bertujuan untuk mengembangkan media pembelajaran berbasis Augmented Reality (AR) yang inovatif dan efektif untuk meningkatkan hasil belajar siswa pada mata pelajaran Ilmu Pengetahuan Alam (IPA), khususnya materi organ gerak pada manusia dan hewan. Penelitian menggunakan pendekatan Research and Development (R&D) dengan beberapa tahapan, yaitu analisis kebutuhan, perancangan desain awal, pengembangan, serta implementasi dan evaluasi media pembelajaran. Lokasi penelitian bertempat di SD IT Al-Mumtaz, Kecamatan Cileunyi, Kabupaten Bandung, dengan subjek penelitian siswa kelas V yang terlibat dalam uji coba skala kecil (10 siswa) dan skala besar (25 siswa).  Instrumen penelitian meliputi observasi, angket, wawancara, dan dokumentasi. Data dianalisis menggunakan teknik skala Likert untuk mengukur tingkat efektivitas dan kelayakan media pembelajaran. Hasil penelitian menunjukkan bahwa media pembelajaran berbasis AR ini memiliki tingkat efektivitas yang tinggi, ditunjukkan dengan peningkatan pemahaman siswa terhadap konsep organ gerak manusia dan hewan. Uji coba juga mengungkap bahwa media ini menarik minat siswa dan mendorong motivasi belajar yang lebih tinggi.  Kontribusi penelitian ini terletak pada pengembangan media pembelajaran inovatif yang relevan dengan era digital. Media AR memberikan pengalaman belajar interaktif yang mendukung siswa dalam memahami konsep IPA yang kompleks secara visual dan praktis. Dengan demikian, penelitian ini diharapkan dapat menjadi inspirasi bagi pengembangan media pembelajaran digital lainnya, sekaligus membantu meningkatkan kualitas pendidikan di sekolah dasar.
Pembelajaran Gasing Pada Materi Perkalian Bilangan Bulat: Pengaruh & Dampaknya Terhadap Hasil Belajar Siswa
Authors: Rumajar Jeremia Reinhard , Pulukadang Rosiah Julianti , Manurung Ontang
Published: January 2025

Penelitian ini bertujuan untuk mengetahui adanya pengaruh dengan melihat: Rata-rata hasil belajar peserta didik yang menggunakan pembelajaran Gampang Asyik dan Menyenangkan (GASING) lebih tinggi dari rata-rata hasil belajar peserta didik yang menggunakan pembelajaran. secara langsung atau ceramah. Metode penelitian yang digunakan yaitu jenis eksperimen semu. Populasi penelitian adalah seluruh peserta didik kelas VII SMP Negeri 2 Bitung dengan sampel diambil secara random sampling sebanyak 40 peserta didik yang terbagi menjadi dua kelas yaitu kelas eksperimen dengan perlakuan penggunaan pembelajaran GASING dengan alat peraga konsep gunung dan lembah, sedangkan perlakuan pada kelas kontrol penggunaan pembelajaran secara langsung atau ceramah pada materi perkalian bilangan bulat. Serta desain penelitian yang digunakan adalah control group design. Instrumen penelitian yang digunakan adalah tes (pretest-posttest) berbentuk uraian. Data yang dianalisis adalah data yang diperoleh dari hasil belajar postest kelas eksperimen dan kelas kontrol menggunakan program microsoft excel dengan uji prasyarat normalitas dan homogenitas serta uji-t (two sampel t-tes) dimana diperoleh nilai  maka memenuhi kriteria keputusan uji t. Hasil dari penelitian ini menyatakan bahwa setelah diberikan perlakuan pada kedua kelas tersebut dan diperoleh hasil tes akhir (posttest) menunjukkan bahwa rata-rata hasil belajar pada kelas eksperimen adalah 77,70 lebih tinggi dari rata-rata hasil belajar kelas kontrol adalah 53,15. Maka dapat disimpulkan bahwa ada pengaruh dari pembelajaran GASING terhadap peningkatan hasil belajar matematika peserta didik pada materi perkalian bilangan bulat kelas VII SMP Negeri 2 Bitung. Kontribusi utama dari penelitian ini adalah membuktikan efektivitas metode pembelajaran GASING dalam meningkatkan hasil belajar matematika siswa, khususnya pada materi perkalian bilangan bulat. Sehingga hasil ini menyediakan alternatif metode pembelajaran yang efektif bagi guru matematika, terutama dalam mengajarkan materi perkalian bilangan bulat di tingkat SMP. Selain itu penelitian ini memberikan wawasan baru tentang penerapan metode pembelajaran yang menyenangkan dan interaktif dalam mata pelajaran matematika, yang sering dianggap sulit oleh siswa. Kontribusi-kontribusi ini dapat membantu meningkatkan kualitas pembelajaran matematika dan mendorong pengembangan metode-metode pembelajaran yang lebih efektif di masa depan.
The Role of The English Vocabulary Level Test For ESP Learners: Assessing Students’ Readiness
Authors: Siradjuddin Suharti , Yahrif Muhammad
Published: January 2025

This research aims to determine the student’s readiness to learn English at the tertiary level through vocabulary tests. This research was carried out due to the low English skills at the tertiary level for English-specific purposes in accounting. Students find it difficult to use general English, which is possibly because of a lack of vocabulary. Furthermore, the researchers attempted to investigate this assumption further by using an online vocabulary test through the Oxford online vocabulary test with quantitative data analysis techniques. There were 233 tertiary students from 8 different classes who participated in this research, taking English for Accounting and English for Business as one of the courses in the first semester at Universitas Negeri Makassar.  The tools for collecting data were the Oxford online vocabulary test, survey questionnaires, and observation. Quantitative data were used to collect data through questionnaires. The findings showed that the majority of respondents (38%) at the tertiary level were at A1 or the elementary English vocabulary level, which is inadequate to learn English for ESP at the university level. This research also found that the majority of respondents (50%) have learned English since elementary school which contradicts the vocabulary level test result. It can be concluded that students’ English vocabulary levels are insufficient for academic demands at the university level, particularly in preparing for ESP courses. Moreover, students’ vocabulary development shows inconsistent with the extended period of English learning since elementary with the increase of English vocabulary proficiency. However, integrating learning methods such as social media, online apps, website, games, movies, songs, and novels can be an effective approach for enhancing English learning in the classroom.
Menggali Moderasi Beragama sebagai Pilar Keadilan
Authors: Nasution Riska Khairani , Zubaidah  , Siti Aisa Sanif  , Rahmadani
Published: January 2025

This research examines the role of religious moderation as a pillar of justice in the context of ethics education among postgraduate students of UIN Malang. In an increasingly plural and complex world, religious moderation is expected to be a solution to reduce conflict and promote interfaith harmony. Through a qualitative research method with a case study type, this study conducted in-depth interviews and focus group discussions with postgraduate students to understand their understanding of religious moderation and its application in daily life. The results showed that students have a high awareness of the importance of moderation in maintaining social justice. In addition, ethics education at UIN Malang plays an important role in shaping tolerant and inclusive attitudes among students. This study concludes that the integration of religious moderation in the higher education curriculum can strengthen the values of justice and facilitate constructive interfaith dialogue.
INTESTINAL MICROFLORA OF NORMOTENSIVE PATIENTS WITH VISCERAL OBESITY
Authors:   Republican Center for Hygiene, Epidemiology and Public Health, E. Sukhotskaya , Y. Malinovskaya ,   Republican Center for Hygiene, Epidemiology and Public Health, P. Semizhon ,   Republican Center for Hygiene, Epidemiology and Public Health, M. Chernevskaya ,   Republican Scientific and Practical Center Cardiology, M. Belskaya ,   Republican Scientific and Practical Center Cardiology, O. Pavlova ,   Republican Scientific and Practical Center Cardiology
Published: January 2025

We obtained changed readings in the quantitative composition of certain representatives of the intestinal microflora characteristic of normotensive patients with visceral obesity in comparison with normotensive patients without visceral obesity. They included a decreased pool of commensal bacteria Faecalibacterium spp. (10.51 ± 1.13 vs. 9.5 ± 1.14, p = 0.020), Lactobacillus spp. (9.17 ± 1.74 vs. 8.00 ± 2.52, p = 0.025), Bacteroides spp. (9.02 ± 0.76 vs. 8.46 ± 0.47, p = 0.027), Fusobacterium spp. (13.4 ± 1.01 vs. 12.03 ± 0.92, p < 0,001), Bifidobacterium spp. (7.31 ± 1.16 vs. 5.95 ± 1.82, p = 0.028) respectively. Quantitative content of representatives of opportunistic intestinal microflora Streprococcus spp. (6.31 ± 0.79 vs. 5.87 ± 0.78, p = 0.032) and Staphylococcus spp. (6.67 ± 1.23 vs. 5.98 ± 0.98, p = 0.036) was increased in patients with visceral obesity compared to the group of patients without visceral obesity.
DETERMINANTS OF RECURRENT ISCHEMIC EVENTS WITHIN 30 DAYS IN PATIENTS WITH ACUTE MYOCARDIAL INFARCTION
Authors:   Grodno State Medical University, V. A. Snezhitskiy ,   Grodno State Medical University, S. A. Lialikau ,   Grodno State Medical University
Published: January 2025

Aim. To identify the determinants of recurrent ischemic events within 30 days in patients with acute myocardial infarction (MI). Methods. The prospective observational study included 405 patients, divided into 2 groups based on endpoints. Group 1 included 369 people without events; group 2 included 36 patients with recurrent ischemic events (stent thrombosis, recurrent myocardial infarction, peri-infarction angina). The following studies were performed: multielectrode aggregometry, blood test with platelet indices, enzyme-linked immunosorbent determination of soluble CD40 ligand, sP-selectin, von Willebrand factor and endothelin-1 on days 1–2 of MI, genotyping of CYP2C19, P2RY12, ITGB3, ITGA2, eNOS3 genes. Results. Using step-by-step discriminant analysis, the following equation was constructed: Y = –15,9829 + 0,0211 × X1 + 0,0777 × X2 + 1,1012 × X3 + + 0,0183 × X4++0,1002 × X5 + 0,0455 × Х6 + 0,1653 × Х7 + 0,5568 × Х8 + + 0,1546 × Х9 + 0,3175 × Х10, where: Х1 – age, years; X2 – waist circumference, cm; X3 – NYHA FC; X4 – erythrocyte sedimentation rate in a blood test, mm/h; X5 – the number of leukocytes in a blood test; X6 – ADP-test (U) value of the aggregogram; X7 – fibrinogen level (g/l) in blood plasma; X8 – results of genotyping of the polymorphic marker G681A (*2) of the CYP2C19 gene, where carriage of genotype GG = 0, carriage of genotype GA = 1, carriage of genotype AA = 2; X9 – results of genotyping of the C807T polymorphic marker of the ITGA2 gene, where carriage of genotype CC = 0, carriage of genotype ST = 1, carriage of genotype TT = 2; X10 – results of genotyping of the T786C polymorphic marker of the eNOS3 gene, where carriage of the TT genotype = 0, carriage of the TC genotype = 1, carriage of the CC genotype = 2. If Y > 0, the probability of developing recurrent ischemic events within 30 days from the onset of MI is high. If Y ≤ 0, the probability of developing recurrent ischemic events within 30 days from the onset of MI is low. The diagnostic sensitivity of the model is 77.7%, diagnostic specificity is 80.0%, accuracy is 77.9%, the predictive value of a negative result (favorable prognosis) is 97.6%, the predictive value of a positive result (unfavorable prognosis) is 25.3 %. Conclusions. Short-term prognosis is influenced by age, abdominal obesity, inflammation and insufficient efficacy of clopidogrel, carriage of mutant alleles of the CYP2C19, ITGA2 and eNOS3 genes, the products of which affect the metabolism of clopidogrel and platelet activity.
RHEUMATOID ARTHRITIS: A MODERN LOOK AT PROBLEMATIC NUTRITION ISSUES
Authors:   Belarusian State Medical University, N. A. Martusevich , N. A. Pavlovskaya ,   Belarusian State Medical University, E. I. Kislach ,   Belarusian State Medical University, N. P. Mitkovskaya ,   Belarusian State Medical University
Published: January 2025

The article examines the role of nutrition as an additional factor in the treatment of rheumatoid arthritis (hereinafter – RA). Foodomics data on the mechanisms of nutrition influence on the pathogenesis of RA are presented from the perspective of modulation of immuno-inflammatory processes, changes in the intestinal microbiota, and regulation of gene expression associated with inflammation. The key areas of research are summarized – from individual nutrients to complex dietary approaches. Besides, we present scientific data on the role of nutrients and beverages in reducing RA activity, as well as current recommendations from international rheumatology communities. Special attention is paid to the Mediterranean diet, which has the greatest evidence base.
Harmonisation of sixteen tropospheric ozone satellite data records
Authors: Keppens Arno , Hubert Daan , Granville José , Nath Oindrila , Lambert Jean-Christopher , Wespes Catherine , Coheur Pierre-François , Clerbaux Cathy , Boynard Anne , Siddans Richard , Latter Barry , Kerridge Brian , Di Pede Serena , Veefkind Pepijn , Cuesta Juan , Dufour Gaelle , Heue Klaus-Peter , Coldewey-Egbers Melanie , Loyola Diego , Orfanoz-Cheuquelaf Andrea , Maratt Satheesan Swathi , Eichmann Kai-Uwe , Rozanov Alexei , Sofieva Viktoria F. , Ziemke Jerald R. , Inness Antje , Van Malderen Roeland , Hoffmann Lars
Published: January 2025

Abstract. The first Tropospheric Ozone Assessment Report (TOAR, 2014–2019) encountered several observational challenges that limited the confidence in estimates of the burden, short-term variability, and long-term changes of ozone in the free troposphere. One of these challenges is the difficulty to interpret the consistency of satellite measurements obtained with different techniques from multiple sensors, leading to differences in spatiotemporal sampling, vertical smoothing, a-priori information, and uncertainty characterisation. This motivated the Committee on Earth Observation Satellites (CEOS) to initiate a coordinated activity VC-20-01 on improving the assessment and harmonization of tropospheric ozone measured from space. Here, we report on work that contributes to this CEOS activity, as well as to the ongoing second TOAR assessment (TOAR-II, 2020–2025). Our objective is to harmonise the spatiotemporal perspective of (sixteen) satellite ozone data records, thereby accounting as much as possible for differences in vertical smoothing and sampling. Four harmonisation methods are presented to achieve this goal: two for ozone profiles obtained from nadir sounders (UV-visible, IR, and combined UV-IR), and two for tropospheric ozone column products derived by one of the residual methods (Convective Cloud Differential or Limb-Nadir Matching). We discuss to what extent harmonisation may affect assessments of the spatial distribution, seasonal cycle, and long-term changes in free tropospheric ozone, and we anchor the harmonised profile data to ozonesonde measurements recently homogenised as part of TOAR-II. We find that approaches that use global ozone fields as a transfer standard (here the Copernicus Atmosphere Monitoring Service ReAnalysis, CAMSRA) to constrain the harmonisation generally lead to the largest reduction of the dispersion between satellite datasets. These harmonisation efforts, however, only partially account for the observed discrepancies between the satellite datasets, with a reduction of about 10–40 % of the inter-product dispersion upon harmonisation, depending on the products involved and with strong spatiotemporal dependences. This work therefore provides evidence that it is not only the differences in spatiotemporal smoothing and sampling, but rather the differences in measurement uncertainty that pose the main challenge to the assessment of the spatial distribution and temporal evolution of free tropospheric ozone from satellite observations.
Historical trends of seasonal droughts in Australia
Authors: Grant Matthew O. , Ukkola Anna M. , Vogel Elisabeth , Hobeichi Sanaa , Pitman Andy J. , Borowiak Alex Raymond , Fowler Keirnan
Published: January 2025

Abstract. Australia frequently experiences severe and widespread droughts, causing impacts on food security, the economy, and human health. Despite this, recent research to comprehensively understand the past trends in Australian droughts is lacking. We analyse the past changes in seasonal-scale meteorological, agricultural and hydrological droughts – defined using the 15th percentile threshold of precipitation, soil moisture, and runoff, respectively. We complement these traditional metrics with an impact-based drought indicator built from government drought reports using machine learning. Calculating trends in time and area under drought, for the various drought types, we find that while there have been widespread decreases in Australian droughts since the early 20th century, extensive regions have experienced an increase in recent decades. However, these recent changes largely remain within the range of observed variability, suggesting they are not unprecedented in the context of the historical drought events. The drivers behind these drought trends are multi-faceted and we show that the trends can be driven by both mean and variability changes in the underlying hydrological variable. Additionally, using explainable machine learning techniques, we unpick the key hydrometeorological variables contributing to agricultural and hydrological drought trends. The influence of these variables varies considerably between regions and seasons, with precipitation often shown to be important but rarely the main driver behind observed drought trends. This suggests the need to consider multiple drivers when assessing drought trends.
Characteristics, main sources, health risks of PM2.5-bound perfluoroalkyl acids in Zhengzhou, central China: From seasonal variation perspective
Authors: Zhang Jingshen , Ma Xibin , Li Minzhen , Wang Zichen , Jiang Nan , Wu Fengchang
Published: January 2025

Abstract. Perfluoroalkyl acids (PFAAs) have become the focus due to their physicochemical stability and potential toxicity. In this study, the investigation aimed to characterize the pollution levels, identify the primary sources, and assess the health risks associated with PFAAs in PM2.5. The average concentration range for PFAAs were between 46.68 and 181.63 pg·m-3, with the main components being perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorobutanoic acid. PFAA concentrations in PM2.5 were greatly influenced by the short- and medium-range air masses, and markedly elevated by industrial activities in surrounding urban areas. The results by positive matrix factorization revealed that PFOA-based products (38.2 %) and degradation byproducts of fluorotelomer alcohols (26.7 %) were the predominant sources. The average daily inhalation of 17 PFAAs fluctuated greatly (median: 4.35 × 10-3 to 8.78 pg·(kg·d)-1), showing different seasonal variations with estimated daily intake of PFOA and PFOS reaching peak value in winter (5869.39 pg) and spring (4219.41 pg), respectively. The research indicated that seasonal regulation of PFOA-related manufacturing and joint pollution control with neighboring cities could reduce PFAAs levels in PM2.5. The results provided theoretical support for government to make targeted control plans for PFAAs and basic data for relevant researchers.
Ion beam instability model for the Mercury upstream waves
Authors: Narita Yasuhito , Schmid Daniel , Motschmann Uwe
Published: January 2025

Abstract. An analytic model for the ion beam instability is constructed in view of application to the Mercury upstream waves. Our ion beam instability model determines the frequency and the wavenumber by equating the whistler dispersion relation with the beam resonance condition in favor of planetary foreshock wave excitation. By introducing the Doppler shift in the instability frequency, our model can derive the observer-frame relation of the resonance frequency to the beam velocity and the flow speed. The frequency relation serves as a useful diagnostic tool to the Mercury upstream wave studies in the upcoming BepiColombo observations.
New insights on particle characteristics of previously characterised EGRIP ice core samples via single particle ICP-TOFMS
Authors: Stoll Nicolas Angelo , Clases David , Gonzalez de Vega Raquel , Elinkmann Matthias , Larkman Piers Michael , Bohleber Pascal
Published: January 2025

Abstract. Polar ice cores contain an archive of chemical impurities, which can be used as a proxy for the past climate. State-of-the-art chemical methods increase our knowledge about these impurities, especially when applying a cascade of complementary techniques to the same samples. Single particle inductively coupled plasma-time of flight mass spectrometry (SP ICP-TOFMS) has yet to be fully utilised to study polar ice; only two studies have described its application so far. This is surprising given its capability to access critical physicochemical parameters of insoluble particles, such as number concentration, the mass and size distributions and elemental composition of deposited particles. In this study, we demonstrate the analysis of ice core samples, which have previously been characterised with Raman spectroscopy and laser-ablation inductively coupled plasma mass spectrometry, via SP ICP-TOFMS. By investigating melted samples, new possibilities for the in-depth geochemical analysis of deposited aerosols arise. We analyse nine samples from the EGRIP ice core from different climate periods throughout the last 50 ka. Samples from cold periods, such as Glacial Stadials, generally have the highest particle concentrations, especially when containing cloudy bands. We present an overview of the different particulate elements, which are largely unexplored in deep polar ice cores. We introduce a novel approach to estimating particle size by transferring mineralogy information from Raman spectroscopy, leading to a more accurate particle size representation via SP ICP-TOFMS, especially in the nanometre range. Our results show the largely untapped potential of SP ICP-TOFMS and demonstrate new opportunities to analyse intact particles as proxies for the palaeoclimate. The combination of impurity characterisation methods applied to the same samples empowered us to gain complimentary perspectives on particles and collect a comprehensive data set from the same samples. In view of the ongoing endeavour to retrieve the "Oldest Ice", SP ICP-TOFMS may become a critical tool to access vital information and new depths of insights.
Does Popping and Puffing Improves the Nutritional Profile of Starchy Grains and Makes It Healthier?
Authors: Ms. Muskaan Gupta  , Ms. Pawandeep Kaur Sandhu  , Dr. Rajesh Kumar Vishwakarma  , Er. Rahul Kumar Rout
Published: January 2025

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Machine Learning Techniques for Classifying Indonesian Foods and Drinks by Nutritional Profiles
Authors: Al Qohar Bagus , Tanga Yulizchia Malica Pinkan , Darmawan Aditya Yoga
Published: January 2025

Local ingredients and Indonesia's diverse culinary traditions play an important role in shaping people's health and eating habits. Understanding the nutritional profile of Indonesian food is crucial to promoting healthier food choices. This study aims to classify Indonesian food and beverages based on their nutritional content, with a focus on calories, protein, fat, and carbohydrates. To achieve this, a dataset of 1,346 food items was preprocessed using normalization techniques to improve model performance. Each food item was categorized as High Protein, High Fat, or High Carbohydrate based on its dominant macronutrient content. Five machine learning models which are K-Nearest Neighbors, Decision Trees, Support Vector Machines, Random Forest, and Multilayer Perceptron-were used and compared. Among these models, the Support Vector Machine achieved the highest classification accuracy of 99.1%. These findings demonstrate the potential of machine learning in nutrition research, providing a basis for developing data-driven dietary recommendations tailored to individual nutritional needs. This research bridges traditional dietary research with modern computational approaches, offering insights for public health initiatives and personalized nutrition planning.
Implementation of Loyalty Program Theory Based on Recency Frequency Monetary Score in Information Systems to Increase Customer Loyalty
Authors: Rajagukguk Ricky
Published: January 2025

This study aims to help online retail stores find the right strategy for treating customers through customer segmentation based on Recency, Frequency, and Monetary (RFM) Score. With a quantitative approach, this study uses the K-Means Clustering algorithm to group customers based on their RFM values ​​and applies it within the Loyalty Program Theory framework. The results show that the Best Customers segment has the highest percentage at 26.3%, which emphasizes the importance of retaining high-value customers through exclusive loyalty programs such as VIP access and premium offers. In contrast, the Lost Customers segment at 24.8% requires attention through retargeting and discount programs to attract them back. This study proves that data-based customer segmentation and the implementation of relevant strategies can strengthen long-term relationships with customers, increase loyalty, and ultimately help the development of online retail businesses.
Poverty and Sustainable Development in Africa: Its Implications to Sub-Sahara Countries
Authors: C. E. Ogodogun, , A. M. Otuedon,
Published: January 2025

The study focuses on the linkage between poverty and sustainable development and its implications for Sub-Saharan countries. It examines the interplay between poverty, climate change, and sustainable development in the areas of causes, synergies, trade-offs, and adaptations. Finally, it offers insights into possible pathways to poverty mitigation options for Africa and moves her into the path of poverty sustainable development goal. The study is qualitative. All reviewed works of literature revealed that climate change, population growth, poor policy structures and institutional setting, poor savings, poor rural community libraries, and inequality in resource distributions, amongst others, are poverty panaceas in Africa. The implications of this paper are that it showcased the necessity for governments and the international community to take both proactive and reactive steps towards reducing poverty, which is now a major hindrance to the implementation of SDGs. Another implication is that the study provides a reference for less developed regions to make reasonable and integrated arrangements for their sustainable development. The paper concluded that there is an urgent need by government at all levels to integrate these factors into sustainable development, thereby moving toward the goal of sustainable development for poverty. Summarily, the study recommended that African leaders should stop paying lip service to sustainable development implementation. They should increase expenditure on social services and amenities, and the international community should be genuine in their international assistance to Africa.
Simultaneous Quantification of Berberine and Curcumin in Combined Extract Form and Polyherbal Marketed Formulation
Authors: Kamboj Sonia , Bhargawa Anurag
Published: January 2025

Objective: An RP-HPLC analytical method for the estimation of both herbal markers (berberine and curcumin) was developed by Waters 515 Series pumps connected with an auto sampler, injector with a 20µl ﬁxed loop and a 2998 PDA UV–vis. detector. Method: Separation was performed on an Agilent C-18(2) column (particle size 5µm; 250mm×4.5mm SN-usjab01584). Chromatographic data were recorded and processed by means of an EMPOWER-2 tool and photo diode array (PDA) detector. The mobile phase used was ACN: 20mM KH2PO4 buffer solution (PBS) (adjusted to pH 3.0 with phosphoric acid, H3PO4) (35:65 v/v) of 1.0 mL/min. The elution was measured at 272 nm. Result and Conclusion: The Rt was 3.07 and 5.53 min for berberine and curcumin respectively. The linearity range was from 150-4800 ng/mL and 900-28800 ng/mL for berberine and curcumin respectively. The LOD and LOQ were found to 50 ng/mL and 150 ng/mL for berberine and 300 ng/mL and 900 ng/mL for curcumin. Moreover, reproducibility and repeatability were found within the range i.e., % RSD ≤ 2% for both drugs. The accuracy of berberine and curcumin was 98.15% w/w and 98.57% w/w respectively. The %age purity of marketed herbal formulation was 94.61% w/w and 95.94% w/w for berberine and curcumin respectively.
Review on Drugs Acting on Candida Infection and Their Treatment
Authors: Sawant Vishal V. , Chaudhari Bharatee P. , Redasani Vivekkumar K.
Published: January 2025

Due to the rise in immunocompromised patients, infections caused by Candida species have increased rapidly globally. Clinical practitioners have implemented a number of measures for the prevention and treatment of candidiasis. Fluconazole, amphotericin B, nystatin, and flucytosine are among the many antifungal medications that are frequently used to treat individuals with Candida infection. In addition, numerous efflux pump inhibitors have been developed and examined in various models for the successful treatment of candidiasis. Biomedicines, such as antibodies and polysaccharide-peptide conjugates, may be safer and more effective solutions for treating and preventing diseases than manufactured pharmaceuticals, which can have negative side effects. Additionally, the ability to investigate how genes function in adhesion, penetration, and other processes has been made possible by the availability of genome sequences of Candida albicans and other non-albicans strains. For a considerable amount of time, harmless commensals known as Candida species have been associated with humans. They are frequently observed on human skin, gastrointestinal, and genitourinary tract mucosal surfaces. However, in patients with impaired immune systems, they transform into opportunistic infections. Because they are opportunistic pathogens, they can lead to systemic infections as well as localized mucosal infections. The effective management of candidiasis has faced a significant and daunting challenge as a result, and costs have multiplied.
Mathematical Modeling and Statistical Analysis of Refining Pennisetum glaucum Disease Identification through Hybrid Optimization Strategies
Authors: Chiti Nigam
Published: January 2025

Within the field of agricultural biotechnology, prompt and effective disease detection in crops like Pennisetum glaucum, or pearl millet, is essential to achieving maximum productivity and food security. This work investigates the use of hybrid optimization techniques to improve Pennisetum glaucum illness detection. The accuracy and effectiveness of traditional illness categorization methods are often limited, which makes the investigation of more sophisticated procedures necessary. To build a reliable hybrid model, our method combines many optimization methods, such as artificial neural networks (ANN), particle swarm optimization (PSO), and genetic algorithms (GA). By using the advantages of each distinct approach, the hybrid model improves classification performance as a whole. To train and verify our model, we gathered a large dataset of samples of Pennisetum glaucum afflicted by different diseases. As compared to traditional approaches, the findings show a considerable increase in illness classification accuracy, with the hybrid model obtaining a precision rate of over 95%. Moreover, the computational time needed for model training and prediction was decreased by using hybrid optimization techniques. The present research highlights the capacity of hybrid optimization to revolutionize agricultural disease control strategies, providing farmers and agronomists with a scalable and effective resolution.
Fermatean Picture Fuzzy Sets
Authors: V. Chitra
Published: January 2025

This paper introduces the concept of the Fermatean Picture Fuzzy Set (FPFS). We define several operations on these set. Additionally, we establish the concepts of images and preimages within the context of FPFS. Finally, we extend our discussion to the Fermatean Picture fuzzy topological space and define the properties using the theorems.
A Fuzzy Mathematical Model for the Parathyroid Hormone Secretion in Health Using LOG Gamma Distribution
Authors: S. Prakasam
Published: January 2025

In this paper, the formula for mean and variance of fuzzy log gamma distribution was developed and is used to find the dynamics of parathyroid hormone secretion in health and secondary hyperparathyroidism.Introduction: Mathematical modeling Problems in engineering, computational science and the physical and biological sciences are using gradually more complicated mathematical techniques. PTH secretion is forbidden by the serum calcium concentration, it is also significant to recognize that during its calcemic actions, PTH regulates the serum calcium concentration. The rate of calcium reduces affect the maximal PTH response to hypocalcaemia has been a topic of concentration.  Methods: Probability theory and statistics, the comprehensive multivariate log-gamma (G-MVLG) distribution is a multivariate distribution introduced by Demirhan and Hamurkaroglu in 2011. The G-MVLG is an elastic distribution.  This enables one to manage dispersion of the distribution.Results: The result shows that the fuzzy mean increases in lower alpha cuts and decreases in upper alpha cuts and also the fuzzy variance are increases in lower alpha cuts and decreases in upper alpha cuts for the effect of the linear and episodic induction in serum calcium produced higher PTH values.Conclusions: We exhibit the assessment of dynamics of parathyroid hormones secretion in health and secondary hyperparathyroidism by the guesstimate of expectation and variance with binary parameter Log- Gamma distribution.
The Approximate Solutions of Fractional PDEs with Antagana-Baleanu Operator in Reimann Sense
Authors: Hassan Kamil Jassim
Published: January 2025

This paper discusses the natural homotopy permutation method as follows: definitions, properties pertinent to this study, algorithmic analysis, and applications to solve fractional differential equations using the Atangana-Baleanu operator in the Reimann sense. This specific type of fractional issue responded well to the method, and finally, approximations to the equations were found.
Influence of Soret and Dufour Impacts on Casson Fluid Flow in a Channel Embedded in a Porous Medium
Authors: Azhagu Ramar
Published: January 2025

This research focuses on analyzing the behavior of Casson fluid flow via a porous medium, with a specific emphasis on the effects of thermal diffusion and diffusion-thermo. The primary aim of the study is to understand how these effects influence heat and mass transfer mechanisms within the flow system. To achieve this, the study transforms the governing partial differential equations for momentum, energy, and concentration into ordinary differential equations via similarity transformations. These equations are then numerically solved using the bvp4c solver. The study's methodology involves computing solutions for the velocity, temperature, and concentration under varying conditions of Soret and Dufour effects. Quantitative results are presented via graphs and tables, demonstrating how the presence of Soret and Dufour leads to significant changes in the concentration and temperature outlines within the fluid flow. Specifically, the results indicate that the Soret effect enhances mass transfer, while the Dufour effect contributes to temperature variations. The significance of this study lies in its detailed exploration of the interaction between heat and mass transfer in a Casson fluid within porous media, which has direct applications in fields such as chemical engineering, geothermal energy extraction, and environmental management. The findings have real-time applicability in processes like oil recovery, pollutant transport, and cooling systems where porous structures are involved. The research contributes valuable insights into optimizing these processes by demonstrating how thermal and mass diffusion phenomena can be effectively controlled. By providing a comprehensive quantitative analysis of the Soret and Dufour effects, this study offers practical guidance for engineers and researchers seeking to improve the efficiency of heat and mass transfer in various industrial and environmental applications.
A Bivariate Lognormal Approach to Modeling Prolactin Secretion in Healthy Adults
Authors: Bevara Kondala Rao
Published: January 2025

In this study, we used lognormal distributions, known for their effectiveness in decision sciences, applying a "standardized" form that can also extend to multivariate lognormal distributions. Our focus was on prolactin (PRL) concentrations in healthy individuals, specifically examining gender differences while controlling for factors like employment history, sleep patterns, emotional stress, and medication. The results indicate a correlation between PRL concentrations in men and women, analyzed with an appropriate mathematical model.
Multilingual Language Translator Using ML
Authors: Gopal D. Upadhye
Published: January 2025

This research paper explores the design and development of a Python-based multilingual translation application that leverages various libraries for a robust, user-friendly experience. The application integrates multiple functions such as text translation, speech-to-text, text-to-speech, and PDF text extraction, using libraries like Pyttsx3, PyPDF2, Speech Recognition, Tkinter, and the Google Translate API. The system allows for real-time translations, enhancing communication across different languages and improving accessibility. It enables users to convert PDF content into translated text and provides voice-based input for ease of use, particularly for users with physical limitations. The application’s performance in translation accuracy, speech recognition, and ease of use has been thoroughly tested, yielding positive user feedback. Furthermore, the modular design of the system allows for easy scalability and adaptability for future improvements, such as integrating more languages and enhancing voice recognition. This project demonstrates the effective use of Python’s rich library ecosystem in creating a comprehensive tool to bridge language barriers in various personal, academic, and professional contexts.
An Embedding of Space of Continuous Functions of a Hausdorff, Locally Compact Space
Authors: Amalraj.P
Published: January 2025

Assume X is a Hausdorff, locally compact space. This paper demonstrates the space of continuous functions on K(X), which is, the open sets in the topology of Vietoris on the collection of all compact subspaces of X embedded into K(C(K(X)) with Fell topology. Combining with another embedding theorem, it is confirmed that C(X) is placed within K(C(K(X)))
Smart Traffic Management Analyzing Network Congestion Mitigation Techniques in Vehicular AD-HOC Networks
Authors: Animesh Kumar Jain
Published: January 2025

Vehicle Ad Hoc Networks (VANETs) play a vital role in developing intelligent transportation systems, enhancing traffic efficiency and safety. However, network congestion poses a significant challenge, impacting network performance and reliability. This paper presents a novel algorithm designed to mitigate network congestion in VANETs by leveraging adaptive processing capabilities, context awareness, and real-time processing. The proposed algorithm's performance is evaluated against existing techniques (D-FPAV, VMaSC, and CARPOOL) using key indicators: data throughput, latency, and packet delivery ratio (PDR). Our findings indicate that the proposed algorithm outperforms these solutions, achieving: Data throughput of 850 kbps, Latency of 120ms, and PDR of 95%. This performance is attributed to the algorithm's dynamic adjustment mechanism, multi-metric optimization, and hybrid communication strategies. These improvements ensure efficient data transmission, enhance reliability, and responsiveness of vehicle communications. The practical implications of this research are profound, offering significant enhancements in traffic flow, safety, and scalability for intelligent traffic management systems. Future research directions include: Real-world implementation, enhancing energy efficiency and Integration with emerging technologies (5G and edge computing), Paving the way for a smarter, more adaptable transportation network.