bluuebunny/crossref_metadata_2025 huggingface dataset:
Geomorphic imprint of high-mountain floods: insights from the 2022 hydrological extreme across the upper Indus River catchment in the northwestern Himalayas
Authors: Kashyap Abhishek , Cook Kristen L. , Behera Mukunda Dev
Published: February 2025

Abstract. The interaction of tectonics, surface processes, and climate extremes impacts how the landscape responds to extreme hydrological events. In 2022, an anomalous precipitation event occurred during the monsoon season along the lower–middle reaches of the upper Indus River, resulting in short-lived high-magnitude flooding and socioeconomic disruption downstream. To understand the spatial relationship between the geomorphic response and climatic controls of this flood event, as well as their primary triggers, we performed a landscape analysis using topographic metrics and quantified the causal association between hydroclimatic variables. Temperature anomalies in upstream glaciated subcatchments had a considerable impact on snow cover distribution, based on our observations. As snow cover changed, glacial-melt runoff rose, contributing to increased fluvial stream power after traversing higher-order reaches. The higher-order reaches of the upper Indus River received an anomalously high amount of precipitation, which, when combined with substantial glacial-melt discharge, contributed to an extreme flood across the high-relief, steep-gradient channels. The flood-affected regions had high mean basin ksn (normalized steepness index) values and stream length–gradient (SL) index values, with numerous spikes in their magnitudes along their channel profiles downstream. To determine how the lower–middle reaches of the upper Indus River responded to this flood event, we employed the enhanced vegetation index (EVI) and the normalized difference water index (NDWI) as change indicator metrics. We observed an inverse causal influence of the NDWI on the EVI and a statistically significant relationship between anomalous stream power and the relative EVI, suggesting that the downstream channel morphology changed rapidly during this episodic event and highlighting the EVI as a useful indicator of geomorphic change. We suggest that this extreme flood event resulted from the interaction of anomalous glacial melt and anomalous precipitation over a high-relief landscape, with a certain causal connection to anomalous temperature observed over the event duration. The synoptic observations suggest that this meteorological condition involves the interaction of the Indian summer monsoon (ISM) and western-disturbance (WD) moisture fluxes. However, the geomorphic consequences of such anomalous monsoon periods, as well as their influence on long-term landscape change, are still unclear.
Investigating uncertainty and parameter sensitivity in bedform analysis by using a Monte Carlo approach
Authors: Reich Julius , Winterscheid Axel
Published: February 2025

Abstract. Precise and reliable information about bedforms regarding geometry and dynamics is relevant for many applications – such as ensuring safe conditions for navigation along the waterways, parameterizing the roughness of the riverbed in numerical models, or improving bedload measurement and monitoring techniques. There are many bedform analysis tools to extract this information from bathymetrical data. However, most of these tools require the setting of various input parameters, for which specific values have to be selected. How these settings influence the resulting bedform characteristics has not yet been comprehensively investigated. We therefore developed a workflow to quantify this influence by performing a Monte Carlo simulation. By repeating the calculations many times with varying input parameter settings, the possible range of results is revealed, and thus the procedure-specific uncertainties can be quantified. We implemented a combination of the widely used zero-crossing procedure to determine bedform geometries and a cross-correlation analysis to determine bedform dynamics. Both methods are well known and established, which ensures the transferability and value of the findings. In order to increase the robustness of the workflow, we implemented a wavelet analysis based on Bedforms-ATM (Guitierrez et al., 2018), which is carried out before the zero-crossing procedure. This provides further orientation and accuracy by identifying predominant bedform lengths in a given bed elevation profile. The workflow has a high degree of automation, which allows the processing of large amounts of data. We applied the workflow to a test dataset from the Lower Rhine in Germany that was collected by the German Federal Waterways and Shipping Administration in February 2020. We found that bedform parameters reacted with different sensitivity to varying input parameter settings. Uncertainties of up to 35 % and up to 50 % were identified for bedform heights and bedform lengths, respectively. The setting of a window size in the zero-crossing procedure (especially for the superimposed small-scale bedforms in cases where they are present) was identified to be the most decisive input parameter. Here, however, the wavelet analysis offers orientation by providing a range of plausible input window sizes, and it thus allows for a reduction in uncertainty. Concurrently, the time difference between two successive measurements has been proven to have a significant influence on the determination of bedform dynamics. For the test dataset, the faster-migrating small-scale bedforms were no longer traceable for intervals longer than 2 h. At the same time, they contributed to up to 90 % of the total bedload transport, highlighting the need for measurements at high temporal resolution in order to avoid a severe underestimation.
Development of a high-order global dynamical core using the discontinuous Galerkin method for an atmospheric large-eddy simulation (LES) and proposal of test cases: SCALE-DG v0.8.0
Authors: Kawai Yuta , Tomita Hirofumi
Published: February 2025

Abstract. Focusing on the future global atmospheric simulations with a grid spacing of O(10–100 m), we developed a global nonhydrostatic atmospheric dynamical core with high-order accuracy by applying a discontinuous Galerkin method (DGM) for horizontal and vertical discretization. Furthermore, considering a global large-eddy simulation (LES), a Smagorinsky–Lilly turbulence model was introduced to the proposed global dynamical core in the DGM framework. By conducting several tests with various polynomial (p) orders, the impact of the high-order DGM on the accuracy of the numerical simulations of atmospheric flows was investigated. To show high-order numerical convergence, a few modifications were made in the experimental setup of existing test cases. In addition, we proposed an idealized test case to verify global-LES models, which is a global extension of an idealized planetary boundary layer (PBL) turbulence experiment performed in our previous studies. The error norms from the deterministic test cases, such as the linear-advection and gravity-wave tests, showed an optimal convergence rate achieved by an approximately p+1-order spatial accuracy when the temporal and round-off errors were sufficiently small. In the climatic test cases, such as the Held–Suarez test, the kinetic energy spectra indicated the advantage of effective resolution when large polynomial orders were used. In the LES experiment, the global model provided a reasonable vertical structure of the PBL and energy spectra because the results under shallow-atmosphere approximation reproduced those obtained in the plane computational domain well.
Expected annual minima from an idealized moving-average drought index
Authors: Stagge James H. , Sung Kyungmin , Munyejuru Irenee Felix , Haidar Md Atif Ibne
Published: February 2025

Abstract. Numerous drought indices originate from the Standardized Precipitation Index (SPI) and use a moving-average structure to quantify drought severity by measuring normalized anomalies in hydroclimate variables. This study examines the theoretical probability of annual minima based on such a process. To accomplish this, we derive a stochastic model and use it to simulate 10 ×106 years of daily or monthly SPI values in order to determine the distribution of annual exceedance probabilities. We believe this is the first explicit quantification of annual extreme exceedances from a moving-average process where the moving-average window is proportionally large (5 %–200 %) relative to the year, as is the case for many moving-window drought indices. The resulting distribution of annual minima follows a generalized normal distribution rather than the generalized extreme-value (GEV) distribution, as would be expected from extreme-value theory. From a more applied perspective, this study provides the expected annual return periods for the SPI or related drought indices with common accumulation periods (moving-window length), ranging from 1 to 24 months. We show that the annual return period differs depending on both the accumulation period and the temporal resolution (daily or monthly). The likelihood of exceeding an SPI threshold in a given year decreases as the accumulation period increases. This study provides clarification and a caution for the use of annual return period terminology (e.g. the 100-year drought) with the SPI and a further caution for comparing annual exceedances across indices with different accumulation periods or resolutions. The study also distinguishes between theoretical values, as calculated here, and real-world exceedance probabilities, where there may be climatological autocorrelation beyond that created by the moving average.
Turbulent heat flux dynamics along the Dotson and Getz ice-shelf fronts (Amundsen Sea, Antarctica)
Authors: Jacob Blandine , Queste Bastien Y. , du Plessis Marcel D.
Published: February 2025

Abstract. In coastal polynyas, where sea-ice formation and melting occur, it is crucial to have accurate estimates of heat fluxes in order to predict future sea-ice dynamics. The Amundsen Sea Polynya is a coastal polynya in Antarctica that remains poorly observed by in situ observations because of its remoteness. Consequently, we rely on models and reanalysis that are un-validated against observations to study the effect of atmospheric forcing on polynya dynamics. We use austral summer 2022 shipboard data to understand the turbulent heat flux dynamics in the Amundsen Sea Polynya and evaluate our ability to represent these dynamics in ERA5. We show that cold- and dry-air outbreaks from Antarctica enhance air–sea temperature and humidity gradients, triggering episodic heat loss events. The ocean heat loss is larger along the ice-shelf front, and it is also where the ERA5 turbulent heat flux exhibits the largest biases, underestimating the flux by up to 141 W m−2 due to its coarse resolution. By reconstructing a turbulent heat flux product from ERA5 variables using a nearest-neighbor approach to obtain sea surface temperature, we decrease the bias to 107 W m−2. Using a 1D model, we show that the mean co-located ERA5 heat loss underestimation of 28 W m−2 led to an overestimation of the summer evolution of sea surface temperature (heat content) by +0.76 °C (+8.2×107 J) over 35 d. By obtaining the reconstructed flux, the reduced heat loss bias (12 W m−2) reduced the seasonal bias in sea surface temperature (heat content) to −0.17 °C (−3.30 × 107 J) over the 35 d. This study shows that caution should be applied when retrieving ERA5 turbulent flux along the ice shelves and that a reconstructed flux using ERA5 variables shows better accuracy.
A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems
Authors: Garfinkel Chaim I. , Lawrence Zachary D. , Butler Amy H. , Dunn-Sigouin Etienne , Statnaia Irina , Karpechko Alexey Y. , Koren Gerbrand , Abalos Marta , Ayarzagüena Blanca , Barriopedro David , Calvo Natalia , de la Cámara Alvaro , Charlton-Perez Andrew , Cohen Judah , Domeisen Daniela I. V. , García-Serrano Javier , Hindley Neil P. , Jucker Martin , Kim Hera , Lee Robert W. , Lee Simon H. , Osman Marisol , Palmeiro Froila M. , Polichtchouk Inna , Rao Jian , Richter Jadwiga H. , Schwartz Chen , Son Seok-Woo , Taguchi Masakazu , Tyrrell Nicholas L. , Wright Corwin J. , Wu Rachel W.-Y.
Published: February 2025

Abstract. Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.
Generative AI Use in an EdD Program
Authors: Buss Ray , Markos Amy , Marsh Josephine
Published: February 2025

Generative AI has emerged as a tool to assist doctoral students as they conduct academic research and writing. In this study, we explored two ways AI has been used by students in our EdD program—informally and independently and in a more formalized, guided manner. First, we found students have been engaged in self-directed, informal, independent use of AI tools like Grammarly and Wordtune to aid them with writing. Other students used AI to summarize information from research studies and locate research articles. To be competitive, they believed that they needed to learn more about AI and its use. Second, we obtained data for students’ use of AI as they searched for theories to inform their research efforts. They were more confident to try out and utilize AI when instructors introduced it. Results indicated students found this use to be extremely helpful and a necessary tool for students in EdD programs.
Navigating New Frontier
Authors: Schroeder Mubina Khan , Alcruz Joanna
Published: February 2025

The landscape of generative AI in Education Doctorate (EdD) programs is multifaceted and rapidly evolving, demonstrating a significant impact on educational methodologies and student engagement. In the Molloy University ​​EdD program, AI is leveraged extensively for a range of purposes, from assessment tools like Perusall to advanced platforms like Roshi.ai. These technologies not only streamline the assessment process but also offer a personalized learning experience. Furthermore, AI's role in assisting student research is pivotal, providing sophisticated data analysis, trend prediction, and comprehensive literature review capabilities. The use of AI for writing assistance further exemplifies its utility in enhancing academic rigor and student productivity. This integration of AI tools within the EdD curriculum represents a forward-thinking approach, preparing educators and leaders to harness the power of AI in their future professional practices.
Empowering Educational Leadership Research with Generative AI
Authors: Wilder Corrie , Calderone Shannon
Published: February 2025

This study explores the integration of generative artificial intelligence (AI) into qualitative research within a higher education context. Through a collaborative self-study, a doctoral candidate and their dissertation supervisor examined the application of Google’s Gemini 1.5 to analyze interview data from a dissertation of practice (DiP) focused on interinstitutional partnerships. The findings demonstrate that AI can enhance the depth and efficiency of qualitative analysis, revealing hidden complexities and patterns while augmenting the researcher's analytical skills and fostering reflexivity. However, challenges related to data integrity, potential biases, and the need for careful human oversight are also discussed. This research offers insights into the transformative potential of AI in qualitative research, particularly within doctoral education, while raising important ethical considerations and prompting a re-evaluation of traditional dissertation practices in the context of emerging technologies.
Framework for Integrating Generative AI Into Statistical Training in Doctor of Education Programs
Authors: Eith Christine , Zawada Denise
Published: February 2025

This paper proposes a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. The rigorous demands of doctoral education, coupled with the challenges of learning complex statistical software and coding language, often lead to anxiety and frustration among students, particularly those in part-time or online programs. This article explores how generative AI can serve as a scaffold for learning, potentially mitigating statistics anxiety and enhancing students’ abilities to focus on core statistical concepts rather than software intricacies. The proposed framework, grounded in constructivist learning theory, outlines a process for faculty to facilitate dialogues using generative AI tools that support students in developing research questions, selecting appropriate statistical tests, checking assumptions, and conducting statistical analyses. By leveraging AI as a dialogic partner, students can engage in self-regulated learning and enhance critical thinking skills essential for practitioner-scholars. This approach has the potential to improve statistical training in EdD programs, producing more competent translators of research who can effectively apply and interpret statistical methods in their professional practice. The article concludes by discussing implications for EdD programs and suggestions for improving the curriculum that includes statistical training.
The afterlife of François Le Moyne’s Annunciation on eighteenth-century Portuguese azulejos
Authors: Salema de Carvalho Rosário
Published: February 2025

Considered lost until a few years ago, the Annunciation painted by François Le Moyne in 1727 (and turned into a print, in the following year, by Laurent Cars) was widely copied, both in paintings and prints. But while the paintings – some of them thought to have originated in Le Moyne’s own workshop – are well documented, the same cannot be said of the prints. Nonetheless, these works remain highly significant, as they were the main vehicles for the dissemination of images in the 18th century. In Portugal (and Brazil), researchers have found 34 eighteenth-century azulejo panels inspired by this composition. Based on these findings, they concluded that the model launched by Le Moyne’s painting and promoted by Cars’ print became highly popular from the 1740s on, and even more so with the rise of the Rococo style. In fact, it ended up replacing the previous models, thereby putting an end to the pictorial diversity that had characterized former depictions of the Annunciation in azulejo.
Apariciones y desapariciones en las imágenes de la práctica artística
Authors: Sanjuan Ruth
Published: February 2025

Miramos las imágenes, pero también ellas nos miran. Las imágenes, al igual que los textos, exigen ser leídas y traducidas por el/la lectora. Quieren comunicarse con el deseo de reactivarse en cada mirada y en cada imaginación. En las imágenes, como en los textos, la información no siempre es evidente, en ocasiones se encuentra oculta, encriptada, esperando ser decodificada y rescatada. Las imágenes en el contexto de la práctica artística, especialmente las que se van a abordar en este texto, las autobiográficas, hablan de apariciones y desapariciones, un juego que implica aceptar que las cosas -o los cuerpos- puede ir de un lado a otro, estar y no estar al mismo tiempo, como espectros o fantasmas que aparecen porque nos quieren decir algo, porque dejaron algo pendiente por contar y a eso vuelven, para eso se -nos- aparecen. Podemos declarar que tenemos una visión cuando las miramos, cuando nos enfrentamos a las imágenes autobiográficas que nos ofrecen estos trabajos.
The Virtues and Vices of Association Health Plans
Authors: Mendoza Roger
Published: February 2025

This is a study about the non-group and small group market segments of health insurance in the United States. Association health plans (AHPs) under the Affordable Care Act (ACA) allow small firms to gain access to affordable healthcare by pooling similar risk groups and taking advantage of significant cost savings typically available only to large employers and their large group plans. Controversy arose after the U.S. Department of Labor (DOL) permitted the self-employed and made it easier for small firms to join AHPs that can be treated as large group health plans, exempt from the protections and standards of non-group and small group plans under the ACA. This study examines why and how regulatory policy might allow these beneficiaries to gain the advantages of large group AHPs and avoid the responsibilities of non-group and small group coverage. It adapts a transaction cost approach to analyze legislative intent, market risks, and regulatory alternatives and implications. Because transaction costs are considerably present, one set of jurisdictional rights could be deemed more efficient on the basis of the regulatory framework upheld by an impartial arbiter and the policy consequences — whether intended or not — that it anticipates in dispute resolution. In the presence of multiple and reciprocal transaction costs, the study suggests that litigating and adjudicating AHP regulatory policy may be optimal compared to other means that the contending parties could possibly arrive at themselves. The prospect of an adverse judgment may also incentivize at least one party to negotiate, if not withdraw from, contestation.
Abstracts of Significant Cases Bearing on the Regulation of Insurance: 2024
Authors: Myers Olivea
Published: February 2025

Review of significant court cases of interest in 2024 concerning insurance regulation.
Persepsi Siswa SMK Negeri 1 Tanjung Batu terhadap Pekerjaan di Sektor Pertanian
Authors: Rahmad Ramdhani  , Sari Komala , M. Ardi Kurniawan
Published: February 2025

Penelitian ini bertujuan untuk mengidentifikasi dan menganalisis karakteristik siswa di SMK Negeri 1 Tanjung Batu terhadap pekerjaan di sektor pertanian dan menganalisis persepsi siswa di SMK Negeri 1 Tanjung Batu terhadap pekerjaan di sektor pertanian.Berdasarkan hasil yang didapatkan dari penelitian ini maka dapat ditarik beberapa kesimpulan Karakteristik Siswa-Siswi SMK N 1 Tanjung Batu adalah : a) Jurusan bahwa terdapat dua jurusan, yaitu Teknik Komputer Jaringan dan Agribisnis Tanaman Perkebunan, b) Jenis kelamin terdapat berjenis kelamin laki-laki berjumlah 31 siswa dan berjenis kelamin perempuan berjumlah 33 siswi, c) Aktivitas organisasi terdapat dengan persentase 45,31% tidak aktif dalam berorganisasi, d) Pekerjaan orang tua terdapat dengan persentase 53,13% bekerja di bidang non pertanian, e) Pendidikan orang tua yang paling banyak berada pada taraf SMA/Sederajat yaitu dengan persentase 39.06%, f) Pendapatan orang tua bahwa terdapat 59, 38% siswa yang memiliki orang tua berpenghasilan kurang dari Rp1.000.000, g) Kepemilikan lahan pertanian orang tua terdapat 64,06 % siswa memilki lahan pertanian yang dimiliki orang tua kurang dari 1 hektar. h) Aktivitas pertanian terdapat 23,44% siswa tidak pernah terlibat diusaha tani orang tua, 20.31% siswa tidak pernah mendapatkan pengarahan dan informasi mengenai pekerjaan di sektor petanian, dan 51,56% siswa berada dilingkungan keluarga yang sebagian adalah petani. Rata-rata skor responden terhadap persepsi siswa dalam pekerjaan disektor pertanian. Terletak pada kriteria sedang dengan kisaran rata-rata skor yaitu 22,94. Persepsi yang sedang tersebut muncul dari indikator aspek ekonomis yang berada pada kriteria rendah yaitu 6,55 dan indikator aspek sosial dan aspek teknis yang berada pada kriteria sedang yaitu 8,72, dan 7,67.
Analisis Perbedaan Pendapatan Petani Padi yang Menggunakan Pupuk Subsidi dan Pupuk Non Subsidi di Desa Cahya Maju Kec. Lempuing OKI Kab. OKI
Authors: Ika Rahma Fitriyani  , Ekanopi Aktiva  , Manisah
Published: February 2025

Penelitian ini membahas  pendapatan petani padi pengguna pupuk subsidi dan non subsidi di Desa Cahya Maju Kecamatan Lempuing Kabupaten Ogan Komering Ilir dalam satu kali musim tanam. Penelitian ini merupakan penelitian survey dengan sampel sebanyak 64 orang petani, yang terbagi menjadi 32 petani pengguna pupuk subsidi dan 32 petani yang pengguna pupuk non subsidi, yang diambil menggunakan metode disproportioned stratified random sampling, dikarenakan jumlah poplasi nya tidak seimbang. Hasil  penelitian menunjukkan rata-rata biaya yang dikeluarkan petani padi pengguna pupuk subsidi adalah sebesar 9.508.748/Ha/Mt sedangkan rata-rata biaya yang dikeluarkan petani non pengguna pupuk subbsidi adalah sebesar 9.835.180,5/Ha/Mt. Hasil dari analisis uji t student menunjukkan bahwa nilai t hitung hitung (2,840) dari t-tabel (2,388) artinya H0 ditolak dan diterima H1. Rata-rata penerimaan yang diterima oleh petani padi pengguna pupuk subsidi adalah sebesar 42.983.437,5/Ha/Mt. Sedangkan rata-rata penerimaan yang diterima oleh petani non pengguna pupuk subsidi adalah sebesar 26.134.613,1/Ha/Mt. pendapatan usahatani padi petani pengguna pupuk subsidi adalah sebesar 33.594.942,5/Ha/Mt Sedangkan rata-rata pendapatan petani non pengguna pupuk subsidi adalah sebesar 16.370.805,6/Ha/Mt. Hasil analisis uji t student untuk mengetahui apakah terdapat perbedaan biaya produksi menunjukkan bahwa nilai t hitung (-2,840) lebih besar dari t tabel (2,388), maka H0 ditolak dan diterima H1. Hasil analisis uji t student untuk mengetahui apakah terdapat perbedaan pendapatan menunjukkan bahwa nilai t hitung (7,707) lebih besar dari t tabel (2,388), maka H0 ditolak dan H1 diterima artinya terdapat perbedaan pendapatan petani padi pengguna pupuk subsidi dengan petani non pengguna pupuk subsidi di Desa Cahya Maju Kec. Lempuing Kab. OKI dengan taraf kepercayaan 99%.
A DEMATEL method for identifying supply chain complexity drivers of footwear industry
Authors: Woldassilas Tekalign Lemma , Lemu Hirpa G. , Gutema Endalkachew Mosisa
Published: February 2025

This study aims to investigate the key drivers of supply chain complexity in the footwear industry business sector. After conducting extensive literature review and consultation with experts, complexity drivers in the context of the footwear business sector were identified. The content validity of the identified drivers was checked by 13 experts using content validity ratio (CVR), which were used as the basis to select 20 key Supply Chain complexity drivers. Using a multi-criteria decision-making DEMATEL approach the cause and effect drivers were investigated. The findings of the study investigated 12 cause and 8 effect drivers in the footwear sector. Among the cause drivers, four linkage drivers that have strong driving power and dependency were identified. This study is the first in the developing county footwear business sector using DEMATEL approach to identify the key supply chain complexity drivers and their interrelationship. The study identified complexity drivers in the context of the footwear business sector that were not explored before in the existing studies. The outcome of this study will help SC complexity decision-makers in that case sector to control and manage the cause and effect drivers and thus improve the efficiency and effectiveness of their SC performance.
Unusual Lipoma Arborescens of the Knee with Mechanical Locking Symptoms: A Case Report
Authors:   Department of Orthopedic Surgery, Beijing United Family Hospital, No 2 Jiangtai Road, Chaoyang District, Beijing, 10016, China., Jike Lu
Published: February 2025

Lipoma arborescens is a rare and benign intra-articular lesion characterized by villous lipomatous proliferation of the synovium, usually involving the suprapatellar pouch of the knee joint. It is an uncommon cause of intra-articular masses that presenting as slowly progressive painless swelling of the joint, which persists for many years and is accompanied by intermittent effusions.
Otsu Multi-level Adaptive Thresholding with Deep Convolution Neural Network for Diabetic Retinopathy Segmentation and Classification
Authors: Bhavani H
Published: February 2025

Diabetic Retinopathy (DR) is eye disease caused through the retinal damage induced through long-term diabetes mellitus illness. In the initial stage, DR has minor vision difficulties or no symptoms but it outputs in vision loss if it is not treated early. However, overfitting occurs when a model learns noise or specific features from a small dataset which leading to poor generalization. To solve this issue, this research proposed an Otsu Multi-level Adaptive Thresholding with Deep Convolution Neural Network (OMAT+DCNN) approach for DR segmentation and classification. The Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for preprocessing input image which enhances the contrast level and image visibility without amplifying noise. The OMAT is used for segmenting the affected regions and ResNet50 is used for extracting Deep Learning (DL) features. Then, relevant features are selected through Multi-Verse Optimizer (MVO) and DCNN is used for classification. The OMAT improves segmentation accuracy by considering multiple thresholds which adopts to local intensity variations within the image, even when the dataset is limited. DCNN capturing intricate patterns and spatial hierarchies within images and its deep architecture allows to learn complex representations which leads to enhance accuracy. The parameters like dice coefficient, Intersection over Union (IoU), Mean IoU (MIoU), precision, accuracy, f1-score and sensitivity are used for assessing performance. The OMAT+DCNN reaches 0.993 of accuracy when compared to existing techniques such as Convolutional Transformer Network (CTNet) and Residual Attention Network (RAN).
Artificial Intelligence-Driven Personalized Consent Form for Transurethral Resection of the Prostate (TURP): Development and Validation
Authors: Dede Onur
Published: February 2025

The informed consent process is a fundamental component of patient-centered care, yet traditional consent forms often fail to address individual patient needs comprehensively. This study explores the development and implementation of an AI-driven personalized consent form for Transurethral Resection of the Prostate (TURP). By leveraging machine learning algorithms trained on clinical data from 12,000 patients, the tool provides tailored risk assessments and patient-specific recommendations. The model demonstrated high predictive accuracy (AUC: 0.89) for complications such as bleeding, retrograde ejaculation, and urinary incontinence. Comparative analysis revealed that AI-driven consent forms significantly enhanced patient comprehension, satisfaction, and shared decision-making compared to standard practices. These findings underscore the transformative potential of AI in urology, aligning with contemporary guidelines from the European Association of Urology (EAU) and the American Urological Association (AUA). The study highlights the importance of integrating advanced technologies into routine clinical workflows to optimize patient outcomes and foster a new era of precision medicine.
Buffalo whey proteins as innovative raw material for nanoparticles building
Authors: Solis Cizek Pablo A. , Crudeli Gustavo A. , Spelzini Darío , Vasile Franco E.
Published: February 2025

Buffalo whey is the most important byproduct of the cheese industry. Whey proteins are fascinating from a technological and economic point of view. In the presence of polysaccharides (PS), proteins (PR) can form complexes in the na-noscale. The study of PS and PR interactions constitutes a key aspect in building nanomaterials, particularly when the use of scarcely studied protein sources such as Buffalo (Bubalus bubalis) whey is intended. In this sense, the objective of this work was to study the formation of biopolymeric structures by electrostatic interactions from buffalo whey proteins (BWPC) and Arabic gum (GA). An aqueous suspension containing BWPC (0.1% w/v) and GA (0.05% w/v) was prepared for this purpose. For comparative purposes, the behavior of mixtures containing cow whey (WPC) and GA, and the single components were also studied. The pH of biopolymeric dispersions was adjusted to 5.5 to 2.5 with HCl. The interactions were monitored through turbidimetric analysis (absorbance by spectrometry at 600 nm), zeta-potential and particle size distribution (by dynamic light scattering), and relative viscosity (in a Cannon-Fenske capillary viscometer). Analytical trials were performed at least in triplicate. Analysis of variance (ANOVA) was performed to find statistical differences among samples. The significance level was defined at p> 0.05 (confidence interval of 95%). While GA suspensions did not show changes in the absorbance, both BWPC and WPC displayed a maximum between pH 4 and 4.5, attributable to their isoelectric points. Comparatively, mixtures of BWPC-GA and WPC-GA showed higher turbidity values than single-component suspensions (p<0.05), which could indicate the occurrence of attractive interactions. The gradual increase in the absorbance, intended as the formation of soluble complexes, was verified for BWPC-GA from pH 5, reaching a maximum of 4. In contrast, for WPC-GA, it occurred between 5.5 and 4.5. In the range of formation of conjugates, PS-PR showed intermediate zeta-potential values to the single components, being -27 and -50 mV for BWPC-GA and WPC-GA, respectively. In these conditions, the particles showed a monomodal size distribution centered at 250 nm for both systems. The interaction between biopolymers at the different pH values did not evidence appreciable changes in the rheological properties (p>0.05). Obtained results allow us to consider that BWPC can undergo associative interactions with GA, resulting in soluble nano complexes with good colloidal valuable stability for the nutraceutical industry. The use of BWPC as nano-structured components constitutes a promising alternative for adding value to this byproduct, contributing to the economic benefit of dairy industries, and minimizing the polluting effect of this effluent.
Implementation of Inclusive Education, Teacher Motivation and Teacher Resources Among Secondary School Teachers in Malaysia
Authors: Salleh Siti Fatimah , Omar Mustaffar Che
Published: February 2025

This study focuses on the validity and reliability of constructs related to the implementation of the Inclusive Education Program (IEP), teacher motivation, and resource teacher needs among secondary school teachers in Malaysia. The national education system aims to provide an inclusive educational framework for all students, including those with special educational needs (SEN). However, challenges persist in addressing the diverse needs of students at different educational levels, particularly at the secondary level where the curriculum becomes more complex and students face public examinations. Without the necessary support, students with SEN may encounter academic difficulties, leading to frustration, failure, and missed opportunities. Inclusive education, as emphasized by international guidelines, requires a student-centered approach that incorporates co-teaching methods to address the specific needs of SEN students. This approach leads to better curriculum mastery for these students. Resource teachers play a crucial role in supporting the effective implementation of the IEP, which aligns with the Ministry of Education's objectives. The primary aim of this research is to develop and validate an instrument that measures the implementation of the IEP, focusing on teacher knowledge, attitude, collaborative strategies, teaching methods, teacher training, and motivation (intrinsic and extrinsic), as well as the resource teacher needs in Malaysian secondary schools. The study employs quantitative research methods, utilizing Structural Equation Modeling (SEM) to examine the relationships between the various variables. Exploratory Factor Analysis (EFA) is conducted prior to SEM to confirm the suitability of the items within the research instrument. The results of this study demonstrate that the validity and reliability of the constructs evaluated through measures such as Kaiser-Meyer-Olkin (KMO), Total Variance Explained (TVE), Factor Loading (FL), and Cronbach’s Alpha (CA) meet the required standards.
Vegetation Biomass and Carbon Stock Assessment of Tree Species, Sawai Mansingh Sanctuary, Rajasthan
Authors: Dadhich Pragya , Malav Anita , Jaiswal Poonam
Published: February 2025

Out of the many benefits we receive from forests, two major global environmental benefits are biodiversity conservation and carbon sequestration. Tropical forests dominate the role of forests in the global carbon flux and stocks, and therefore it is required for researchers and policymakers to estimate the carbon stock and sequestration potential. Carbon stored in the aboveground biomass of the trees typically constitutes the largest pool and is followed by below-ground biomass and then by litter, soil etc. The carbon stock potential of a forest is directly affected by deforestation and degradation. Carbon stock assessment projects helps us to check the ability of any particular forest to store carbon or to act as a carbon sink. The current study was carried out in Sawai Mansingh Sanctuary of southeast Rajasthan. For sampling and nondestructive field measurement of biomass carbon sequestration, a total of 24 quadrates measuring 100 m by 100 m were randomly laid out. Every tree species was recognized, and confirmed, and data were gathered in the form of diameter at breast height. Forty six tree species were identified in the research region; including Butea monosperma (Lam.) Taubert exhibits the best capacity for sequestering carbon and Anogeissus pendula Edgewis the most dominant. There is 2462447 kg of stored biomass in the area.
Effect of Weed Management Practices on Weed Prevalence, Crop Productivity and Profitability in pearl millet (Pennisetum glaucum L.)
Authors: Dokala Mounika , Rajput Pradeep , Sathya Swaroop Naik Badigi Rajavath , Kr. Kanaujiya Pradeep , Kr. Gautam Sandip
Published: February 2025

A field experiment was conducted during kharif season of 2023 at Crop Research centre-1 School of Agriculture, ITM University, Gwalior (M.P.) India to investigate the impact of weed management strategies on weed prevalence, crop productivity and profitability in pearl millet (Pennisetum glaucum L.). The experiment was set up in a randomized block design with ten treatments and three replications. The data revealed that the pre-emergence application of Pendimethalin 0.75 kg/ha and Atrazine 0.75 kg/ha (POE) recorded less narrow leaf weeds (3.78 no. m2 ), broad leaf weeds (4.71 no. m2 ), sedges (46.24 no. m2 ), total weed density (54.72 no. m2 ), and weed dry matter accumulation (26.87 g/m2 ) at 60 DAS, higher weed control efficiency (83.44%), and higher yield and yield attributes of pearl millet. The pre-emergence application of Pendimethalin 0.75 kg/ha and atrazine 0.75 kg/ha as post-emergence resulted in the highest economics (net return of Rs. 76326 ha-1 and benefit-cost ratio of Rs. 2.48).
A Phytosociological Survey on Weed Flora and Diversity in Garden Land Fields of Annamalai Nagar
Authors: Swaraj Kumar Panuganti , S. Kalaisudarson  , A. Sundari
Published: February 2025

A phyto sociological survey was conducted in order to evaluate the diversity and variety of weed flora in the garden land fields of the Annamalainagar in Tamilnadu, India. Annamalai nagar has a sub-tropical environment with the mean of yearly rainfall of 1200 to 1500 mm. The study was conducted during Marghazipattam, 2022 to ascertain the weed flora, species composition, density, frequency and important value index (IVI). To forecast which weed species are primarily affecting the ecosystems found in garden land fields is the main objective of the study. Five grasses, four broad-leaved weeds and one sedge were found overall. The most common type of weed flora in the garden land fields of Annamalainagar is grass. According to the findings, the most prominent weeds in garden land fields are Cyperus rotondus and Cyanodon dactylon, closely followed by Trianthema portulcastrum, Dactylactium aegyptium, Phyllanthus niruri, Panicum repens and Digiteria sangulensis.
Efficacy of Arbuscular Mycorrhizal Fungi in Bioremediation of Copper Polluted Soil at Viraganoor, Madurai
Authors: Pandi Sakthieaswari , Rajasekar Judith Gloriah
Published: February 2025

Toxic heavy metal pollution is a major environmental issue that has intensified due to increased industrial activities. Bioremediation, which utilizes microorganisms or their enzymes to transform harmful heavy metals into less toxic forms, offers a potential solution. However, microbe-based bioremediation has limitations, including the production of hazardous metabolites. Strategies for metal resistance include expelling metal ions from cells, biosorption to cell walls, trapping in extracellular capsules, precipitation, and converting heavy metal ions to less harmful forms. Arbuscular Mycorrhizal Fungi (AMF), mutualistic symbionts of most plant roots, is critical for phytoremediation due to their extensive hyphal networks, which enhance the absorption of water, heavy metals, and nutrients from the soil. These hyphae can sequester heavy metals within plant roots. Understanding the role of AMF in plant interactions is crucial for optimizing plant distribution to restore degraded ecosystems. This study explores the potential of AMF as bioremediation agents for heavy metals in soil.
Temporal and Spatial variations in Certain Heavy Metals Accumulated in the Fishery Resources in Sasthamkotta Lake, Kerala, India
Authors: Lekshmi L.  , Sheeba S.  , Murali S. Munisha
Published: February 2025

The concentration of trace metals was determined in selected Freshwater fishes of Sasthamkotta Lake, Kerala. The distribution of heavy metals in fishes were in the order copper > zinc > lead > chromium > cadmium. Zinc, copper and chromium concentration were high during premonsoon. Lead and cadmium accumulation was high during monsoon. The bioaccumulation of heavy metals was more in Etroplus maculatus. There is no remarkable variation in all metals at different stations. The present investigation revealed the presence of toxic metals in fishes is within the permissible limit.
Metodología para el aprendizaje de la traducción con enfoque colaborativo
Authors: Carbajal  Roberto Vladimir
Published: February 2025

En el presente ensayo se enfoca en el trabajo de traducción e interpretación vinculado con los métodos de enseñanza que se desarrolla a nivel de educación superior  y se plantea el enfoque colaborativo el  cual  se basa en la interacción social donde existe un espacio de exploración que lleva a un grupo ya sea individual o colectivo a un objetivo de aprendizaje común donde cada uno aporta y enriquece dicho aprendizaje. El proceso de enseñanza-aprendizaje es estructurado por el profesor, pero la principal responsabilidad de aprendizaje recae sobre el estudiante.
En este artículo se propone un enfoque colaborativo donde los participantes buscan mejorar su aprendizaje a través del trabajo conjunto lo cual estimula el pensamiento crítico , el autoestima y la responsabilidad. Así como también se hace una reseña histórica sobre los diferentes métodos de enseñanza -aprendizaje de una lengua y su influencia en la traducción e interpretación.
El trabajo de interpretación y traducción conlleva no solamente el dominio del idioma meta sino que también se integran una series de técnicas y estrategias que contribuyen a un mejor desempeño del traductor e intérprete lo que hace que la adquisición de estas y en especial la de enfoque colaborativo hace que se mejore el desempeño antes señalado.
Educación para el trabajo o para el desarrollo humano
Authors: Lobos Rivera Marlon Elías , Flamenco Cortez Marvin Josué
Published: February 2025

La educación y el trabajo son dos constructos que se relacionan entre sí ya que permiten un buen desarrollo económico tanto del individuo como de la sociedad. El propósito de este trabajo es analizar el papel de la universidad en el contexto actual y destacar su tendencia en la formación para el mercado laboral en detrimento de la formación para el desarrollo humano. Se discuten elementos como el papel de la universidad en la preparación de profesionales para el mercado laboral y los retos de la educación superior en la formación profesional. Se concluye que la visión de la educación debe surgir de la dicotomía de una formación para el trabajo o humanística, donde no debe existir un conflicto entre ambas.
Economy in the digital age: A blended learning-based digital mindset training model at the manager level of banking institutions
Authors: Isneniwati Carlia , Situmorang Robinson , Kustandi Cecep
Published: February 2025

Blended learning-based digital mindset training models at the managerial level of banking institutions are integral to economic development. In the economic field, digital transformation has become a business model phenomenon in conducting business renewal. Thus, the business world is encouraged to carry out digital transformation as an economic demand in the digital era. One of the business fields that continues to transform is the banking industry. In Indonesia, ASK Learning is one of the training centers for banking institutions. Therefore, to encourage the connectivity of digital transformation with the banking world, a digital mindset is needed. This study aims to analyze the blended learning-based digital mindset training model at the managerial level of banking institutions. This research collaborates with 10 participants who have a work background in the banking sector. Data collection techniques in this study were carried out through observation, in-depth interviews, and documentation. The interviews were conducted for 120 minutes for each participant. In-depth interviews were structured and conducted three times over four consecutive months. Data analysis was conducted by researchers through three stages: reduction, data presentation, and conclusion drawing. The results of this study show that a digital mindset is an approach that can be used by the banking industry to understand and utilize existing data. Thus, with the blended learning-based digital mindset training, the banking industry can conduct market and audience analysis through various social media platforms. In addition, this research has implications for technological innovation in banking services by improving banking services and operations through technology. Furthermore, this research concludes that digital mindset training is the basis for the banking industry to build digital collaboration and networks in banking leadership.