bluuebunny/crossref_metadata_2025_split huggingface dataset:
Penggunaan Aplikasi Canva pada Guru Sekolah Dasar sebagai Upaya Menciptakan Media Pembelajaran yang Kreatif
Authors: Dwicahyani Alfin , Bhaktiyana Arif Kiyat , Suhendra Didi , Usifa Krisantus Pius , Wahyuningtyas Neni 
Published: July 2024

Peserta didik akan lebih mudah mengingat dan memahami pelajaran yang disampaikan guru ketika mereka menggunakan media pembelajaran yang menarik seperti tayangan atau tampilan yang dihasilkan dari media pembelajaran. Canva adalah alat desain grafis yang memfasilitasi pembuatan berbagai konten artistik online. materi pelatihan canva sebagai inovasi dalam pembuatan media pembelajaran yang kreatif dipilih oleh peneliti sebagai langkah mewujudkan mutu pendidikan yang berkualitas dan sesuai dengan zaman yang serba teknologi ini. Sehingga tujuan adanya pelatihan ini adalah sebagai upaya menciptakan media pembelajaran yang kreatif dan inovatif melalui bantuan aplikasi canva pada guru SDN 1 Banjarejo Malang.. Metode yang digunakan yaitu melalui ceramah, simulasi dan demonstrasi dalam bentuk penyuluhan dan pelatihan. Pelatihan dilakukan dengan memberikan materi kepada seluruh peserta serta dengan demonstrasi mengenai pembuatan modul ajar, Power Point, Video animasi, brosur, pamflet PPDB dan lain sebagainya.Berdasarkan hasil pelatihan Canva yang telah dilakukan, dapat disimpulkan bahwa pelatihan mengenai penggunaan aplikasi Canva memberikan dampak yang signifikan terhadap pemahaman dan kreativitas para guru.
Kata kunci: Canva; media pembelajaran; kreativitas
The Usage of Canva Application for Elementary School Teachers to Create Creative Learning Media
Students will more easily remember and understand the lessons delivered by the teacher when they use interesting learning media such as broadcasts or displays produced from learning media. Canva is a graphic design tool that facilitates the creation of various artistic content online. Canva training materials as an innovation in creating creative learning media were chosen by researchers as a step to realizing quality education that is in line with this technological era. So, the aim of this training is as an effort to create creative and innovative learning media with the help of the Canva application for teachers at SDN 1 Banjarejo Malang. The method used is through lectures, simulations and demonstrations in the form of counseling and training. The training was carried out by providing material to all participants as well as demonstrations regarding the creation of teaching modules, Power Points, animated videos, brochures, PPDB pamphlets and so on. Based on the results of the Canva training that has been carried out, it can be concluded that the training regarding the use of the Canva application has had a significant impact on the understanding and creativity of teachers.
Keywords: Canva; instructional media; creativity
Metastatic GIST with a TWIST of RCC: A case report
Authors: Ganesan Vaishnavi , Kesari Mrunal , Patil Yoganand , Bhattacharya Indranil 
Published: July 2024

Gastrointestinal Stromal Tumors (GIST) is a tumor of mesenchymal origin in the digestive tract, arising from Interstitial cells of Cajal. Majorly, they are an incidental finding in people of older age group (&#62;60 years) with very rare bone metastasis. Our aim is to understand the role of genetic mutations in metastasis of GIST and coexistence of other malignancy in the same patient. We present an unusual case of a 75-year-old male with jejunal GIST, managed with resection of the tumor and imatinib, who 15 years later presented with subsequent liver, rare femoral head metastases and coexisting Renal Cell Carcinoma in left kidney. GIST cases can be associated with different syndromes and malignancies. This necessitates additional work up and long term follow up.
Well Trajectory Optimization under Geological Uncertainties Assisted by a New Deep Learning Technique
Authors: Yousefzadeh Reza , Ahmadi Mohammad 
Published: July 2024

Summary
The large number of geological realizations and well trajectory parameters make field development optimization under geological uncertainty a time-consuming task. A novel deep learning-based surrogate model with a novel well trajectory parametrization technique is proposed in this study to optimize the trajectory of wells under geological uncertainty. The proposed model is a deep neural network with ConvLSTM layers to extract the most salient features from highly channelized and layered reservoirs efficiently. ConvLSTM layers are used because they can extract spatiotemporal features simultaneously since layered reservoirs can be regarded as a time series of spatially distributed reservoir properties. The proposed surrogate model could predict the individual objective function with a coefficient of determination of 0.96. After verifying the validity of the surrogate model, four approaches were used to optimize well trajectories. Two of the approaches consumed all available realizations (surrogate model-based and simulation-based approaches), while the remaining two used a subset of realizations. The selection of the subset was based on the cumulative oil production (COP) and the diffusive time of flight (DTOF). Results showed that although the surrogate model used all realizations, it could provide similar results to the simulation-based optimization with only a 5% computational cost of the simulation-based approach. The novelty of this work lies in its proposal of an innovative surrogate model to improve the analysis of channelized and layered reservoirs and its introduction of a novel well trajectory optimization framework that effectively addresses the challenge of optimizing well trajectories in complex three-dimensional spaces, a problem not adequately tackled in previous works.
Metabolic syndrome and associated factors among females of reproductive age in Wakiso district, central Uganda: A cross sectional study
Authors: Lubogo David , Wamani Henry , Mayega Roy William , Mutungi Gerald , Ssenyonga Ronald , Orach Christopher Garimoi 
Published: July 2024

Abstract

Background The prevalence of Metabolic Syndrome (MetS) in sub-Saharan African countries including Uganda is on the rise. Females of reproductive age (15–49 years) are more affected by MetS than males leading to adverse maternal and perinatal outcomes. This study assessed the prevalence of Metabolic Syndrome and associated factors among females of reproductive age in Wakiso district, central Uganda to inform policy. Methods We conducted a community-based cross-sectional study among 697 women of reproductive age in Wakiso district, using multistage sampling method. In the first stage, 32 clusters/enumeration areas were randomly selected from a list of all Uganda National Bureau of Statistics enumeration areas in Wakiso district. In the second stage, 25 households were randomly selected from each cluster, totaling 800 households. In the third stage, one female respondent aged between 15–49 years was selected from each household. Quantitative data were collected on socio-demographic factors, behavioral risk factors, and physical (blood pressure, waist circumference, height and weight) and biochemical (High Density Lipoprotein (HDL) cholesterol, triglycerides, and fasting blood glucose levels) measures using a structured questionnaire. MetS was defined by the Joint Interim Statement criterion. Modified Poisson regression with robust standard error estimates was fitted to obtain crude and adjusted prevalence ratios associated with the presence of MetS. All results were weighted based on sampling probabilities. Results The overall prevalence of MetS was (17.8%: 95% CI 13.2–23.6). The risk factors significantly associated with MetS included being overweight (APR: 3.21, 95% CI 1.88–5.45, p = < 0.001), obesity (APR: 5.33, 95% CI 3.35–9.12, p = < 0.001) and breastfeeding of most recent baby (APR: 0.55, 95% CI 0.37–0.82, p = 0.002). Conclusions Nearly one in five women of reproductive age in Wakiso district are affected by Metabolic Syndrome. Overweight and obese women were more likely to have Metabolic Syndrome. Breastfeeding offered protection against Metabolic Syndrome. Our findings suggest the need to promote breastfeeding and appropriate interventions towards reduction and management of overweight and obesity amongst reproductive age women in the communities. Interventions incorporating physical activity, nutrition education, counselling, and preventive screenings may have potential to effectively reduce weight and obesity. Further research should be undertaken to elucidate the best strategies towards reducing and managing overweight and obesity among women in the study settings.
Decomposing geographical and universal aspects of human mobility
Authors: Lehmann Sune , Boucherie Louis , Maier Benjamin 
Published: July 2024

Abstract

Driven by access to large volumes of detailed movement data, the study of human mobility has grown rapidly over the past decade. This body of work has argued that human mobility is scale-free, it has proposed models to generate scale-free moving distance distributions, and explained how the scale-free distribution arises from aggregating displacements across scales. The field of human mobility, however, has not explicitly addressed how mobility is structured by the constraints set by geography -- that mobility is shaped by the outlines of landmasses, lakes, and rivers; by the placement of buildings, roadways, and cities. Based on unique datasets capturing millions of moves between precise locations, we show how separating the effect of geography from mobility choices, reveals a universal power law spanning five orders of magnitude (10m to 1,000,000m). To do so we incorporate geography via the `pair distribution function', a fundamental quantity from condensed matter physics that encapsulates the structure of locations on which mobility occurs. We show that this distribution captures the constraints that geography places on human mobility across length scales. Our description conclusively addresses debates between distance-based and opportunity-based perspectives on human mobility: By showing how the spatial distribution of human settlements shapes human mobility, we provide a novel perspective that bridges the gap between these previously opposing ideas.
Photothermal Sensitive Nanocomposite Hydrogel for Infectious Bone Defects
Authors: Liao Jinfeng , Wu Yanting , Xie Xi , Luo Guowen , Xie Jing , Ye Xiuwen , Gu Wanrong , Mo Anchun , Qian Zhiyong , Zhou Chenchen 
Published: July 2024

Abstract

Infectious bone defects, a significant challenge in clinical settings, often need advanced therapeutic interventions. This study introduces a novel treatment system combining a photothermal therapy hydrogel with a pulsed drug release mechanism. The system employs a hydrogel matrix that is sensitive to the thermal fluctuations characteristic of bone defect sites, enables controlled and localized drug release. The key component of this system is the integration of mild photothermal agents, which are activated within 40-43°C to improve the precision and effectiveness of drug delivery. Our results indicate that the photothermal response significantly improves the localized delivery of therapeutic agents, reducing systemic side effects and enhancing efficacy at the defect site. The pulsed release with mild PTT addresses both infection control and bone regeneration. This innovative approach marks a substantial improvement in bone defect treatments, offering a more targeted, effective, and patient-friendly alternative to conventional methods. Our research aims to expand its applicability to a broader range of tissue regeneration scenarios, underscoring its potential in the field of regenerative medicine.
A Deep Learning Based Hybrid Recommendation Model for Internet Users
Authors: Sami Amany , Adrousy Waleed El , Sarhan Shahenda , Elmougy Samir 
Published: July 2024

Abstract

Recommendation Systems (RS) are essential for personalized item suggestions, but traditional approaches face limitations in accuracy, scalability, efficiency, and cold-start problems. This paper introduces the HRS-IU-DL model, a hybrid RS that leverages advanced techniques to enhance accuracy and relevance. The model integrates user-based and item-based Collaborative Filtering (CF) to analyze user-item interactions, Neural Collaborative Filtering (NCF) to capture non-linear interactions, and Recurrent Neural Networks (RNN) to identify sequential patterns in user behavior. Additionally, Content-Based Filtering (CBF) using Term Frequency-Inverse Document Frequency (TF-IDF) is employed to analyze item attributes. By combining CF, NCF, RNN, and CBF, the HRS-IU-DL model addresses challenges such as data sparsity, the cold-start problem, and the need for personalized recommendations. The proposed model utilizes N-Sample techniques to recommend the top 10 similar items based on user-specified genre, employing methods like Cosine Similarity, Singular Value Decomposition (SVD), and TF-IDF. Evaluation of the HRS-IU-DL model is conducted on the publicly available Movielens 100k dataset using train and test sets. Performance metrics, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Precision, and Recall, are employed to assess the model's performance. The results demonstrate that the HRS-IU-DL model outperforms state-of-the-art methods and achieves significant improvements across these metrics.
Does the first impression matter? Inconclusive evidence favoring anchoring effects in cognitive load assessment
Authors: Krieglstein Felix , Schmitz Manuel , Wesenberg Lukas , Spitzer Markus Wolfgang Hermann , Rey Günter Daniel 
Published: July 2024

Abstract

The anchoring effect is a psychological phenomenon wherein individuals heavily rely on a previously presented anchor when making decisions. This anchor, often a numerical cue presented at the beginning, influences the perception and evaluation of subsequent information by serving as a reference point. The extent to which this effect plays a role in the assessment of cognitive load in educational psychology is not yet known. Particularly, when students need to indicate cognitive load multiple times during problem-solving, they may use heuristics to simplify the cognitively demanding assessment process. Therefore, the purpose of this work was to determine whether the cognitive heuristic of anchoring biases the assessment of cognitive load. In three experiments (N1 = 100, N2 = 87, N3 = 80), participants were asked to assess the complexity of a task environment with task units varying in complexity (low, moderate, and high) multiple times during problem-solving. In each experiment, the sequence of complexity was varied to investigate whether the first impression of complexity affects the immediately following assessment. The results are ambivalent, as the first impression of complexity did not have the expected influence on the immediately following assessment in Experiments 1 and 2. However, the hypothesized anchoring effect was demonstrated in Experiment 3. The results suggest that the anchoring effect occurs only when students are initially confronted with a highly complex task and that this has the strongest influence on the subsequent assessment.
Experimental Study on Grouting Diffusion and Reinforcement Law of Grouting Backfilling mining in Caving Zone
Authors: Li Zhihua , Zou Enlong , Yang Ke , Geng Qian , Ma Guojun , Qi Jiawei , Yang Zhi 
Published: July 2024

Abstract

Grouting filling in a caving zone has always been a "black box" project due to its complexity and unpredictability. The filling space, slurry flow characteristics, and the bearing capacity of the mixture formed by broken rock mass and slurry in the caving zone after grouting filling are difficult to visually express. To investigate these issues, experiments were conducted on the flow characteristics of fly ash slurry under different gangue particle grading schemes and confined compression tests before and after grouting in various gangue particle gradation scenarios. The research results indicate the following: 1) Under different gradation schemes, the theoretically calculated porosity is similar to the measured porosity, providing a preliminary means to assess the filling space. The injection amount of fly ash slurry is proportional to the porosity of the gangue bulk, but high slurry concentration or close particle combination within the gangue may lead to grouting infiltration. 2) Under different gradation schemes, the stress-strain curve of both gangue bulk and gangue-slurry mixture follows an exponential relationship. The maximum strain value in both gangue bulk and mixture tests is influenced by porosity and the proportion of large particle size gangue. 3) The internal energy changes of gangue bulk and mixture exhibit pronounced time series characteristics. The energy change in the early and late stages of the gangue bulk is relatively weak, while the medium-term shows a strong change trend, indicating that the internal structure adjustment in the initial and end stages is relatively gentle, and the energy fluctuation in the intermediate stage is more significant. 4) Creep tests on the mixture show a gradual axial strain change during the stable stress stage, suggesting that the mixture has better stability and bearing capacity.
Eigen-Factors a Bilevel Optimization for Back-end Plane SLAM of 3D Point Clouds
Authors: Ferrer Gonzalo , Iarosh Dmitrii , Kornilova Anastasiia 
Published: July 2024

Abstract

Modern depth sensors can generate a huge number of 3D points in few seconds to be later processed by Localization and Mapping algorithms.Ideally, these algorithms should handle efficiently large sizes of Point Clouds (PC) under the assumption that using more points implies more information available.The Eigen Factors (EF) is a new algorithm that solves PC SLAM by using planes as the main geometric primitive. To do so, EF exhaustively calculates the error of all points at complexity {\em O(1)}, thanks to the {\em Summation matrix S} of homogeneous points.
The solution of EF is a bilevel optimization where the {\em lower-level} problem estimates the plane variables in closed-form, and the {\em upper-level} non-linear problem uses second order optimization to estimate sensor poses (trajectory).We provide a direct analytical solution for the gradient and Hessian based on the homogeneous point-plane constraint. In addition, two variants of the EF are proposed: one pure analytical derivation and a second one approximating the problem to an alternating optimization showing better convergence properties.
We evaluate EF and other state-of-the-art plane SLAM back-end algorithms in a synthetic environment, and extended to ICL dataset (RGBD) and LiDAR KITTI datasets. EF demonstrates superior robustness and accuracy of the estimated trajectory and improved map metrics.Code is publicly available at \texttt{https://github.com/prime-slam/EF-plane-SLAM} with python bindings and pip package.
TL-SNN: Event-Driven Visual-Tactile Learning with Temporal and Location Spiking Neurons
Authors: Yang Jing , Yin Baofan , Li Shaobo , Su Zhidong , Zhang Zhaohu 
Published: July 2024

Abstract

With the continuous development of neuromorphic sensors and spiking neural networks, there is increasing attention on event-driven perception learning in both vision and tactile domains. However, due to the limited information representation capability of existing spiking neurons and the high spatio-temporal complexity of event-driven visual and tactile data, we focus on exploring the application potential of visual and tactile perception in event-driven datasets. We propose an innovative spiking neural network method for integrating visual and tactile perception, aiming to significantly enhance the perceptual and information integration capabilities of the fusion network. Our approach enables the extraction of features from both time and position dimensions, thereby more effectively capturing the spatio-temporal dependencies in event data. Additionally, we introduce a weighted spike loss function to optimize model performance and meet specific task requirements. Experimental results demonstrate that the proposed visual and tactile fusion spiking neural network achieves superior performance compared to baseline algorithms on object recognition, container detection, and slip detection datasets.
Advanced Nano-Enhanced Therapies: The Role of Phenolic Acid-Infused(Syringic Acid, Sinapic Acid, and o-Coumaric Acid) Guar-Gum nanoformulation in Antimicrobial and Anti-inflammatory Wound Care
Authors: Mandal Debojyoti , Sarmah Jayanta K , Gupta Jeena 
Published: July 2024

Abstract

The skin functions as a crucial defensive barrier against external dangers, and any harm to it leads to the development of wounds, which can range in seriousness from immediate to long-lasting and may include tissue loss. Microbial infections, including those produced by Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa, frequently hinder the wound healing process, resulting in delayed recovery and harmful consequences. Utilizing natural chemicals and advanced delivery technologies has become a viable approach to address microbial infections and improve wound healing. Guar gum, which is biocompatible, biodegradable, and mucoadhesive, is perfect for developing nanoformulations for promoting wound healing. The aim of the present study is to develop guar gum-based nanoformulations encapsulating bioactives i.e. Syringic acid, Sinapic acid, or o-coumaric acid for treating wound healing-related microbial infections. The nanoformulations' particle size distribution (around 15-25nm) and zeta potential values (-16 mV to -24 mV) made them stable and suitable for targeted medication administration. Antimicrobial activity testing showed concentration-dependent suppression of Staphylococcus aureus (S. aureus), Escherichia coli (E. coli), and Candida albicans(C. albicans), proving the formulations' efficiency against wound infections. At lower concentrations, the nanoformulations showed negligible cytotoxicity in HaCaT cells, proving their wound treatment safety and biocompatibility. Furthermore, the developed nanoformulations successfully reduce inflammation by lowering TNF-α and Cox-II levels in normal as well as LPS treated condition. Therefore, nanoformulations offer a new path to wound care drugs with better antibacterial activity and low cytotoxicity. In vivo and human trials are needed to confirm their efficacy and safety for wound treatment.