bluuebunny/crossref_metadata_2025_split huggingface dataset:
PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKRIF BERBASIS WEB PADA MATERI BARISAN DAN DERET DENGAN METODE TUTORIAL UNTUK SISWA KELAS X
Authors: Said Muhammad , Sukmawati R. Ati , Sari Delsika Pramata 
Published: November 2024

Penelitian ini bertujuan untuk (1) mengembangkan media pembelajaran interaktif berbasis web pada materi barisan dan deret dengan metode tutorial untuk siswa kelas X dan (2) mengetahui kevalidan media pembelajaran interaktif berbasis web pada materi barisan dan deret dengan metode tutorial untuk kelas X. Penelitian ini menggunakan metode R&D (Reserch and Development) dengan model ADDIE yang sudah dibatasi analisis (analysis), desain (design), pengembangan (development), dan evaluasi (evaluation). Teknik pengumpulan data yang digunakan adalah angket. Instrumen yang digunakan angket validasi materi dan angket validasi media. Hasil dari penelitian ini adalah media pembelajaran pada materi barisan dan deret dengan metode tutorial yang dikembangkan dengan teknologi HTML, CSS, Boostrap, Javascript, JSON, Firebase, Mathjax, Balsamiq Mockups. Penelitian ini menunjukkan bahwa media pembelajaran termasuk valid, karena perolehan persentasi capaian validitas materi sebesar 91,5% dengan kriteria tinggi dan perolehan persentasi capaian validitas media sebesar 76,4% dengan kriteria sedang. Oleh karena itu, media pembelajaran interaktif berbasis web pada materi barisan dan deret dengan metode tutorial untuk siswa kelas X dinyatakan valid digunakan untuk uji coba.
This study aims to (1) develop web-based interactive learning media on row and series material with tutorial methods for grade X students and (2) find out the feasibility of web-based interactive learning media on row and series material with tutorial methods for class X. This research uses the R&D (Research and Development) method with the ADDIE model that has been limited namely analysis, design, development, and evaluation. The data collection techniques used are material validation questionnaires and media validation questionnaires. The result of this study is a learning medium on row and series material with tutorial methods developed with HTML, CSS, Boostrap, Javascript, JSON, Firebase, Mathjax, Balsamiq Mockups. This study shows that learning media is valid, because the percentage of material validity achievement is 91.5% with high criteria and the acquisition of media validity achievement percentage is 76.4% with medium criteria. Therefore, web-based interactive learning media on row and series material with tutorial methods for grade X students is declared valid for trials.
MEDIA PEMBELAJARAN DIGITAL UNTUK MENINGKATKAN MINAT BELAJAR SISWA PADA MATERI TRIGONOMETRI MENGGUNAKAN GOOGLE SLIDE
Authors: Umardiyah Fitri , Hisommudin Muhammad , Khotimah Khusnul 
Published: November 2024

Trigonometri merupakan salah satu mata pelajaran yang berat bagi sebagian besar siswa. Rendahnya minat belajar, menjadi faktor utama yang menyebabkan masalah tersebut muncul. Salah satu upaya yang dapat dilakukan peneliti adalah mengembangkan media pembelajaran meng­gunakan Google Slide dengan tujuan meningkatkan minat belajar siswa pada materi Trigonometri. Penelitian ini dilakukan di MA Balongrejo Sumobito Jombang kelas X-IPA pada tahun ajaran 2022-2023 semester genap. Metode penelitian yang digunakan adalah penelitian dan pengembangan (Research and Development) menggunakan model pengembangan ADDIE. Dari hasil penelitian didapatkan bahwa: 1) Hasil analisis pengisian angket respon minat siswa, terhadap pembelajaran Matematika sebelum menggunakan media pembelajaran Google Slide, didapatkan persentase sebesar 45%. 2) Hasil analisis pengisian angket respon minat siswa, terhadap pembelajaran Matematika setelah menggunakan media pembelajaran Google Slide, didapatkan persentase sebesar 63,19%. Berdasarkan hasil penelitian tersebut, menunjukkan bahwa adanya peningkatan minat siswa dalam pembelajaran Matematika pada materi Trigonometri. Selain itu, didukung dengan hasil tes dan respon siswa terhadap penggunaan media pembelajaran, dengan persentase sebesar 75,39% yang menunjukkan respon baik dan tertarik.
Trigonometry is a tough subject for most students. Low interest in learning is the main factor that causes these problems to arise. One effort that can be done by researchers is to develop learning media using Google Slides with the aim of increasing student interest in Trigonometry material. This research was conducted at MA Balongrejo Sumobito Jombang class X-IPA in the 2022-2023 academic year, even semester. The research method used is research and development (Research and Development) with the ADDIE development model. From the results of the study it was found that: 1) The results of the analysis of filling in the questionnaire on student interest responses, towards learning Mathematics before using Google Slides learning media, obtained a percentage of 45%. 2) The results of the analysis of filling in the questionnaire on students' interest in learning Mathematics after using Google Slides learning media, obtained a percentage of 63.19%. Based on the results of this study, it shows that there is an increase in students' interest in learning Mathematics on Trigonometry material. In addition, it is supported by test results and student responses to the use of instructional media, with a percentage of 75.39% showing good and interested responses.
Hemoglobin Variants as Targets for Stabilizing Drugs
Authors: Žoldáková Miroslava , Novotný Michal , Khakurel Krishna P. , Žoldák Gabriel 
Published: November 2024

Hemoglobin is a vital protein in red blood cells primarily responsible for transporting oxygen from the lungs to tissues. It binds to various ligands, including oxygen, carbon dioxide, carbon monoxide, and nitric oxide, influencing its function and regulation. Genetic mutations of Hb can lead to variants causing disorders like sickle cell disease and thalassemias, which present significant clinical challenges. Recent advances in therapies, such as allosteric modulators, pharmacological chaperones, and antioxidant treatments, have improved the management of hemoglobinopathies by enhancing hemoglobin stability and increasing oxygen affinity. According to the UniProt database (as of 7th August 2024), there are currently 819 variants of the -hemoglobin subunit and 771 variants of the -hemoglobin subunit. Over 116 hemoglobin subunit variants are classified as unstable, highlighting the need to further develop variant-specific hemoglobin-stabilizing molecules. In addition to several small-molecule binders, a potential in the engineering of proteins with hemoglobin-binding capabilities, e.g. falcilysin, lama-derived nanobodies, -hemoglobin-stabilizing proteins and others, offer promising options for further development. Continued research is essential for developing personalized treatments that consider the genetic diversity of hemoglobin variants, offering hope for more targeted therapies, improved management, and potential cures for hemoglobin-related disorders.
Thoracolumbar Fracture
Authors: Striano Brendan M. , Crawford Alexander M. , Gong Jonathan , Desai Vineet , Gabriel Daniel C. , Bellamy J. Taylor , Mukorombindo Tino , Cohen Lara L. , Simpson Andrew K. , Schoenfeld Andrew J. 
Published: November 2024

Background:
Fractures of the thoracic and lumbar spine are increasingly common. Although it is known that such fractures may elevate the risk of near-term morbidity, the natural history of patients who sustain such injuries remains poorly described. We sought to characterize the natural history of patients treated for thoracolumbar fractures and to understand clinical and sociodemographic factors associated with survival.

Methods:
Patients treated for acute thoracic or lumbar spine fractures within a large academic health-care network between 2015 and 2021 were identified. Clinical, radiographic, and mortality data were obtained from medical records and administrative charts. Survival was assessed using Kaplan-Meier curves. We used multivariable logistic regression to evaluate factors associated with survival, while adjusting for confounders. Results were expressed as odds ratios (ORs) and 95% confidence intervals (CIs).

Results:
The study included 717 patients (median age, 66 years; 59.8% male; 69% non-Hispanic White). The mortality rate was 7.0% (n = 50), 16.2% (n = 116), and 20.4% (n = 146) at 3, 12, and 24 months following injury, respectively. In adjusted analysis, patients who died within the first year following injury were more likely to be older (OR = 1.03; 95% CI = 1.01 to 1.05) and male (OR = 1.67; 95% CI = 1.05 to 2.69). A higher Injury Severity Score, lower Glasgow Coma Scale score, and higher Charlson Comorbidity Index at presentation were also influential factors. The final model explained 81% (95% CI = 81% to 83%) of the variation in survival.

Conclusions:
We identified a previously underappreciated fact: thoracolumbar fractures are associated with a mortality risk comparable with that of hip fractures. The risk of mortality is greatest in elderly patients and those with multiple comorbidities. The results of our model can be used in patient and family counseling, informed decision-making, and resource allocation to mitigate the potential risk of near-term mortality in high-risk individuals.

Level of Evidence:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Review of Outcomes After Peripheral Nerve Transfers for Motor Nerve Injury in the Upper Extremity
Authors: Fisher Marlie H. , Le Elliot L.H. , Wong Daniel E. , Ducic Ivica , Iorio Matthew L. 
Published: November 2024

Background:
Modern nerve-to-nerve transfers are a significant advancement in peripheral nerve surgery. Nerve transfers involve transferring donor nerves or branches to recipient nerves close to the motor end unit, leading to earlier reinnervation and preservation of the musculotendinous units in proximal nerve injuries. After nerve reinnervation, function may be superior to traditional tendon transfer techniques in terms of strength and independent motion. Nerve transfer surgery has emerged as a promising treatment option for many cases of nerve injury that were previously expected to result in poor outcomes, such as proximal injuries, long nerve gaps, or unavailability of the proximal injured segment.

Methods:
A review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Publications that focused on upper extremity nerve transfers were included, and functional motor and sensory recovery was analyzed. Technique reports, case reports, brachial plexus injuries, and reports on multiple nerve injuries were excluded.

Results:
A total of 48 relevant articles were identified with search criteria, and we discuss functional outcomes on nerve transfers for ulnar nerve injury, musculocutaneous nerve injury, median nerve injury, and radial nerve injury that met inclusion criteria.

Conclusions:
Nerve transfers are an option for restoring hand and forearm function in patients with peripheral nerve injuries adversely affecting their ability to function. The literature demonstrates positive functional outcomes after nerve transfer operations, and thus, the utility and variations have increased. We aim to provide an overview of the outcomes of current nerve transfer techniques for ulnar, radial, median, and musculocutaneous acquired/traumatic mononeuropathies in the hand and upper extremity.
An examination of daily CO2 emissions prediction through a comparative analysis of Machine learning, Deep learning, and Statistical models
Authors: Ajala Adewole Adetoro , Adeoye Oluwatosin Lawrence , Salami Olawale Moshood , Jimoh Yusuf Ayoola 
Published: November 2024

Abstract

Human-induced global warming, primarily attributed to the rise in atmospheric CO2, poses a substantial risk to the survival of humanity. While most research focuses on predicting annual CO2 emissions, which are crucial for setting long-term emission mitigation targets, the precise prediction of daily CO2 emissions is equally vital for setting short-term targets. This study examines the performance of 14 models in predicting daily CO2 emissions data from 1/1/2022 to 30/9/2023 across the top four polluting regions (China, USA, India, and EU27&UK). The 14 models used in the study comprise four statistical models (ARMA, ARIMA, SARMA, and SARIMA), three machine learning models (Support Vector Machine - SVM, Random Forest - RF, and Gradient Boosting - GB), and seven deep learning models (Artificial Neural Network - ANN, Recurrent Neural Network variations such as Gated Recurrent Unit - GRU, Long Short-Term Memory - LSTM, Bidirectional-LSTM - BILSTM, and three hybrid combinations of CNN-RNN). Performance evaluation employs four metrics (R2, MAE, RMSE, MAPE). The results show that machine learning (ML) and deep learning (DL) models, with higher R2 (0.714–0.932) and l ower RMSE (0.480 − 0.247) values, respectively, outperformed the statistical model, which had R2 (-0.060–0.719) and RMSE (1.695 − 0.537) values, in predicting daily CO2 emissions across all four regions. The performance of ML and DL models was further enhanced by differencing, a technique that improves accuracy by ensuring stationarity and creating additional features and patterns the model can learn from. Additionally, applying ensemble techniques such as bagging and voting improved the performance of ML models by about 9.6%, while hybrid combinations of CNN-RNN enhanced the performance of RNN models. In summary, the performance of both ML and DL models was relatively similar. However, due to the high computational requirements associated with DL models, the recommended models for daily CO2 emission prediction are ML models using the ensemble technique of voting and bagging. This model can assist in accurately forecasting daily emissions, aiding authorities in setting targets for CO2 emissions reduction.
Creep behavior of slip zone considering the rivalry between soil hardening and damage: case study of a giant colluvial landslide
Authors: Huang Mengshuang , Tang Huiming , Tan Qinwen , Fan Zhiqiang , Li Chun , Li Changdong , Niu Yikai , Huang Zhongzhu , Liu Xuan 
Published: November 2024

Abstract

Large colluvial landslides often exhibit creep characteristics influenced by slip zones, whose behavior is closely related to their inherent structure and stress conditions. To investigate this, a triaxial compression creep test on undisturbed slip zone soil was conducted. The results revealed that the soil exhibited a short period of attenuation creep following temporary deformation, then quickly transitioned into the steady creep stage. A rivalry mechanism between hardening and damage effects was suggested to explain and quantitatively characterize the various stages of creep. On this purpose, a three-dimensional constitutive model (H-D3D) was constructed to effectively capture the staged creep behavior, meanwhile a sophisticated approach to solving model parameters was also put forth, considering well the characteristics of each creep stage. After that, the H-D3D model was implemented in FLAC3D through secondary development to numerically solve the complex creep behavior of slip zones and landslides. The results demonstrate that employment of the suggested model successful represents the staged deforming behavior of the targeted landslide that is influenced by fluctuating water levels, confirming the accuracy as well as applicability of the proposed model. Therefore, this research introduces a critical theoretical framework and computational tool for analyzing the deformation behavior of colluvial landslides.
An adaptive fault diagnosis method for rotating machinery based on GCN deep feature extraction and OptGB
Authors: Wang Linjun , Wu Zhenxiong , Wu Haihua , Yang Xifa , Xie Youxiang 
Published: November 2024

Abstract

Detecting faults in bearings and gears is pivotal for smooth machinery and equipment operation, as well as in preventing potentially catastrophic accidents. However, the fault diagnosis method using deep learning is highly dependent on the correlation between the extracted vibration signal features, while the original graph convolutional network (GCN) cannot accurately identify the fault type of rotating machinery and is sensitive to the noise. To solve the above problems, this paper proposes a new fault diagnosis model for rotating machinery based on GCN deep feature extraction and LightGBM optimized by Optuna (GCN-OptGBM). Firstly, in the graph-building stage, the mutual information is used to filter the features and reduce the complexity of the subsequent graph model. Secondly, the weighted Minkowski distance is used to convert the feature matrix into the graph data, then the feature matrix and graph data are input into the GCN together, and the feature extraction is carried out through three graph convolution layers and two rule layers. Finally, the extracted feature data are input into the LightGBM optimized by the Optuna algorithm to achieve the adaptive fault diagnosis and obtain the optimal fault identification results. Experiments are performed on the public dataset of bearings and gears, and the experimental results show that compared with other models, GCN-OptGBM has higher recognition accuracy, better noise immunity and robustness.
Cancer stem cell populations are resistant to 5-aminolevulinic acid- photodynamic therapy (5-ALA-PDT)
Authors: Rice Chantel PJ , Chelakkot Vipin Shankar , Conohan Noah , Hirasawa Kensuke 
Published: November 2024

Abstract

Photodynamic therapy (PDT) is a minimally invasive treatment approved for many types of cancers. PDT involves the administration of photoactive substances called photosensitizers (PS) that selectively accumulate in cancer cells and are subsequently excited/activated by irradiation with specific wavelengths of light. Activated PS leads to the generation of singlet oxygen and reactive oxygen species (ROS), promoting cancer cell death. 5-aminolevulinic acid (5-ALA) is a naturally occurring PS precursor, which is metabolically converted to the PS, protoporphyrin IX (PPIX). Although 5-ALA-PDT is effective at killing cancer cells, we normally observed in in vitro experiments that approximately 5–10% of cells survive 5-ALA-PDT. Identifying the mechanisms of resistance to 5-ALA-PDT-mediated cell death is important to prevent tumor recurrence following 5-ALA-PDT. Previously, we reported that oncogenic activation of Ras/MEK promotes PPIX efflux and reduces cellular sensitivity to 5-ALA-PDT through increased expression of ABCB1 transporter. As cancer stem cells (CSCs) are known to drive resistance to other cancer treatments and have high efflux of chemotherapeutic agents via ABC-family transporters, we hypothesize that CSCs underlie 5-ALA-PDT resistance. In this study, we determined 1) if CSCs are resistant to 5-ALA-PDT and 2) if CSCs play roles in establishing resistant populations of 5-ALA-PDT. When we compared CSC populations before and after 5-ALA-PDT, we found that CSCs were less susceptible to 5-ALA-PDT. Moreover, we found that the CSC population was enriched in 5-ALA-PDT-resistant cell lines compared to the parental cell line. Our results indicate that CSCs are not sensitive to 5-ALA-PDT, which may contribute to establishment of 5-ALA-PDT resistance.
Constraining Genetic Symbolic Regression via Semantic Backpropagation
Authors: Reissmann Maximilian , Fang Yuan , Ooi Andrew S.H. , Sandberg Richard 
Published: November 2024

Abstract

Evolutionary symbolic regression approaches are powerful tools that can approximate an explicit mapping between input features and observation for various problems. However, ensuring that explored expressions maintain consistency with domain-specific constraints remains a crucial challenge. While neural networks are able to employ additional information like conservation laws to achieve more appropriate and robust approximations, the potential remains unrealized within genetic algorithms. This disparity is rooted in the inherent discrete randomness of recombining and mutating to generate new mapping expressions, making it challenging to maintain and preserve inferred constraints or restrictions in the course of the exploration. To address this limitation, we propose an approach centered on semantic backpropagation incorporated into the Gene Expression Programming (GEP), which integrates domain-specific properties in a vector representation as corrective feedback during the evolutionary process. By creating backward rules akin to algorithmic differentiation and leveraging pre-computed subsolutions, the mechanism allows the enforcement of any constraint within an expression tree by determining the misalignment and propagating desired changes back. To illustrate the effectiveness of constraining GEP through semantic backpropagation, we take the constraint of physical dimension as an example. This framework is applied to discover physical equations from the Feynman lectures. Results have shown not only an increased likelihood of recovering the original equation but also notable robustness in the presence of noisy data.
Association between allergen-specific immunoglobulin E positivity, allergic rhinitis symptoms, and quality of life in school-aged children
Authors: Watanabe Daisuke , Otawa Sanae , Kushima Megumi , Yui Hideki , Shinohara Ryoji , Yamagata Zentaro , Sakurai Daiju , Miyake Kunio 
Published: November 2024

Abstract

This study aimed to investigate the relationship between allergen-specific immunoglobulin E (IgE) sensitization and allergic rhinitis (AR) symptoms in school-aged children in Japan and to understand the current severity of AR symptoms and the quality of life (QOL) among children with AR. We analyzed data from 8-year-old children who participated in the Yamanashi Adjunct Study of the Japan Environment and Children's Study, focusing on those with complete information o on specific IgE levels and AR (1,229 for perennial AR [PAR] and 1,196 for seasonal AR [SAR]). Sensitization was determined when allergen-specific IgE levels were class 2 (0.70 U/mL) or higher. Among those who tested positive for house dust mite (HDM)-specific IgE, 656 (53.4%) children were identified, including 362 (60.6%) boys and 294 (46.5%) girls. For Japanese cedar pollen (JCP)-specific IgE, 820 (68.6%) children were sensitized, with 430 (73.1%) boys and 390 (64.1%) girls. Among children with AR, 38.3% of those with PAR and 76.2% of those with SAR experienced moderate to severe nasal symptoms. This study highlighted the high prevalence of JCP-specific IgE sensitization among school-aged children in Japan and provided insights into the severity of AR symptoms and the impact on QOL in these children.